Normalize base-model inheritance

* feat(models): add coding benchmarks and weights

* feat(models): add more coding benchmarks

* feat(models): add agent benchmark scores

* feat(models): normalize benchmark metadata

.github/workflows/deploy.yml

@@ -10,6 +10,7 @@ concurrency: ${{ github.workflow }}-${{ github.ref }}
 
 jobs:
   deploy:
+    if: github.repository == 'anomalyco/models.dev'
     runs-on: ubuntu-latest
     steps:
       - name: Checkout code
@@ -35,3 +36,4 @@ jobs:
       - run: bun sst deploy --stage=dev
         env:
           CLOUDFLARE_API_TOKEN: ${{ secrets.CLOUDFLARE_API_TOKEN }}
+          CLOUDFLARE_DEFAULT_ACCOUNT_ID: ${{ secrets.CLOUDFLARE_DEFAULT_ACCOUNT_ID }}

.github/workflows/sync-models.yml

@@ -0,0 +1,112 @@
+name: Sync Model Catalogs
+
+on:
+  schedule:
+    - cron: "17 * * * *"
+  workflow_dispatch:
+
+permissions:
+  contents: write
+  issues: write
+  pull-requests: write
+
+concurrency: ${{ github.workflow }}-${{ github.ref }}
+
+jobs:
+  providers:
+    if: github.repository == 'anomalyco/models.dev'
+    runs-on: ubuntu-latest
+    outputs:
+      matrix: ${{ steps.providers.outputs.matrix }}
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5
+        with:
+          ref: dev
+
+      - name: Setup Bun
+        uses: oven-sh/setup-bun@f4d14e03ff726c06358e5557344e1da148b56cf7
+        with:
+          bun-version: latest
+
+      - name: Install dependencies
+        run: bun install
+
+      - name: List sync providers
+        id: providers
+        run: |
+          matrix="$(bun models:sync --list-providers)"
+          echo "matrix=$matrix" >> "$GITHUB_OUTPUT"
+
+  sync:
+    needs: providers
+    if: github.repository == 'anomalyco/models.dev'
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix: ${{ fromJSON(needs.providers.outputs.matrix) }}
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5
+        with:
+          ref: dev
+
+      - name: Setup Bun
+        uses: oven-sh/setup-bun@f4d14e03ff726c06358e5557344e1da148b56cf7
+        with:
+          bun-version: latest
+
+      - name: Install dependencies
+        run: bun install
+
+      - name: Sync model catalogs
+        run: bun models:sync ${{ matrix.provider }}
+        env:
+          OPENROUTER_API_KEY: ${{ secrets.OPENROUTER_API_KEY }}
+          GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
+          GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }}
+          GOOGLE_GENERATIVE_AI_API_KEY: ${{ secrets.GOOGLE_GENERATIVE_AI_API_KEY }}
+          XAI_API_KEY: ${{ secrets.XAI_API_KEY }}
+          CLOUDFLARE_WORKERS_AI_SYNC_ACCOUNT_ID: ${{ secrets.CLOUDFLARE_WORKERS_AI_SYNC_ACCOUNT_ID }}
+          CLOUDFLARE_WORKERS_AI_SYNC_API_TOKEN: ${{ secrets.CLOUDFLARE_WORKERS_AI_SYNC_API_TOKEN }}
+
+      - name: Validate models
+        run: bun validate
+
+      - name: Create pull request
+        env:
+          GH_TOKEN: ${{ github.token }}
+          BRANCH: automation/sync-models-${{ matrix.provider }}
+          LABELS: automation,model-sync,provider:${{ matrix.provider }}
+          TITLE: "chore(sync): update ${{ matrix.name }} model catalog"
+        run: |
+          if [ -z "$(git status --porcelain -- providers)" ]; then
+            echo "No model catalog changes found."
+            exit 0
+          fi
+
+          git config user.name "github-actions[bot]"
+          git config user.email "41898282+github-actions[bot]@users.noreply.github.com"
+          git fetch --no-tags --depth=1 origin "+refs/heads/$BRANCH:refs/remotes/origin/$BRANCH" || true
+          git checkout -B "$BRANCH"
+          git add providers
+          git commit -m "$TITLE"
+          git push --force-with-lease origin "$BRANCH"
+
+          label_args=()
+          IFS=',' read -ra labels <<< "$LABELS"
+          for label in "${labels[@]}"; do
+            gh label create "$label" --color "0E8A16" --description "Automated model catalog sync" >/dev/null 2>&1 || true
+            label_args+=(--label "$label")
+          done
+
+          pr_number="$(gh pr list --head "$BRANCH" --base dev --json number --jq '.[0].number')"
+          if [ -n "$pr_number" ]; then
+            gh pr edit "$pr_number" --title "$TITLE" --body-file .sync/model-sync-report.md
+            for label in "${labels[@]}"; do
+              gh pr edit "$pr_number" --add-label "$label"
+            done
+          else
+            gh pr create --base dev --head "$BRANCH" --title "$TITLE" --body-file .sync/model-sync-report.md "${label_args[@]}"
+          fi

.gitignore

@@ -3,6 +3,7 @@
 .idea
 dist
 .DS_Store
+.sync/
 node_modules
 data/tokenspeed-monitor.sqlite
 data/tokenspeed-monitor.sqlite-shm

.opencode/package-lock.json

@@ -0,0 +1,380 @@
+{
+  "name": ".opencode",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "dependencies": {
+        "@opencode-ai/plugin": "1.15.13"
+      }
+    },
+    "node_modules/@msgpackr-extract/msgpackr-extract-darwin-arm64": {
+      "version": "3.0.4",
+      "resolved": "https://registry.npmjs.org/@msgpackr-extract/msgpackr-extract-darwin-arm64/-/msgpackr-extract-darwin-arm64-3.0.4.tgz",
+      "integrity": "sha512-LCkGo6JDfaBhgST7UpPWgNgLINpcpabaHfyz5OBx75nUYxBsaEPxjnyNjWpeb/xBup/682QnBfRBy2/LvPutZQ==",
+      "cpu": [
+        "arm64"
+      ],
+      "license": "MIT",
+      "optional": true,
+      "os": [
+        "darwin"
+      ]
+    },
+    "node_modules/@msgpackr-extract/msgpackr-extract-darwin-x64": {
+      "version": "3.0.4",
+      "resolved": "https://registry.npmjs.org/@msgpackr-extract/msgpackr-extract-darwin-x64/-/msgpackr-extract-darwin-x64-3.0.4.tgz",
+      "integrity": "sha512-zExlW9zUJKZH/tOtVMttwjKa4Xm/3KcNjnE3dPN92uCktwavMxpgCA3MoJK/DOnTWsQgo224OaST27/mPNAf+w==",
+      "cpu": [
+        "x64"
+      ],
+      "license": "MIT",
+      "optional": true,
+      "os": [
+        "darwin"
+      ]
+    },
+    "node_modules/@msgpackr-extract/msgpackr-extract-linux-arm": {
+      "version": "3.0.4",
+      "resolved": "https://registry.npmjs.org/@msgpackr-extract/msgpackr-extract-linux-arm/-/msgpackr-extract-linux-arm-3.0.4.tgz",
+      "integrity": "sha512-Tg3yX65f5GbtXLkrYEHE5oibZG9epyYWas7FogTTEJeDEF9JlXJzKgXaNhT3UXlTOeA+AfZpYZYZ0uPj7Cfquw==",
+      "cpu": [
+        "arm"
+      ],
+      "license": "MIT",
+      "optional": true,
+      "os": [
+        "linux"
+      ]
+    },
+    "node_modules/@msgpackr-extract/msgpackr-extract-linux-arm64": {
+      "version": "3.0.4",
+      "resolved": "https://registry.npmjs.org/@msgpackr-extract/msgpackr-extract-linux-arm64/-/msgpackr-extract-linux-arm64-3.0.4.tgz",
+      "integrity": "sha512-dgX0P/9wGPJeHFBG+ZmhgE6bmtMt7NP5CRBGyyktpopdk/mW4POnrpQsSLtKI1dwpc+pPLuXHDh6vvskyQE/sw==",
+      "cpu": [
+        "arm64"
+      ],
+      "license": "MIT",
+      "optional": true,
+      "os": [
+        "linux"
+      ]
+    },
+    "node_modules/@msgpackr-extract/msgpackr-extract-linux-x64": {
+      "version": "3.0.4",
+      "resolved": "https://registry.npmjs.org/@msgpackr-extract/msgpackr-extract-linux-x64/-/msgpackr-extract-linux-x64-3.0.4.tgz",
+      "integrity": "sha512-8TNXMEjJc3QEy7R/x1INhgiU+XakDAFUzBhaz7+Rbrs8NH5UQeHQxxmzsSBJGyV6I1jW79undiQm8tOI+D+8FQ==",
+      "cpu": [
+        "x64"
+      ],
+      "license": "MIT",
+      "optional": true,
+      "os": [
+        "linux"
+      ]
+    },
+    "node_modules/@msgpackr-extract/msgpackr-extract-win32-x64": {
+      "version": "3.0.4",
+      "resolved": "https://registry.npmjs.org/@msgpackr-extract/msgpackr-extract-win32-x64/-/msgpackr-extract-win32-x64-3.0.4.tgz",
+      "integrity": "sha512-CmCXPQrkbwExx3j946/PtHWHbYJiCRBRDl4BlkRQcJB/YOwQxJRTpoo7aTsortjgoJ1x7opzTSxn7C+ASSLVjQ==",
+      "cpu": [
+        "x64"
+      ],
+      "license": "MIT",
+      "optional": true,
+      "os": [
+        "win32"
+      ]
+    },
+    "node_modules/@opencode-ai/plugin": {
+      "version": "1.15.13",
+      "resolved": "https://registry.npmjs.org/@opencode-ai/plugin/-/plugin-1.15.13.tgz",
+      "integrity": "sha512-NFwZGhmxIPijtfz9swPJXDmhOpq4UWP8WjEE7GEMr7FwtJrK/hv6v36nFimed5+OKk+pQCrTJn/vhRW7Io72IA==",
+      "license": "MIT",
+      "dependencies": {
+        "@opencode-ai/sdk": "1.15.13",
+        "effect": "4.0.0-beta.66",
+        "zod": "4.1.8"
+      },
+      "peerDependencies": {
+        "@opentui/core": ">=0.2.16",
+        "@opentui/keymap": ">=0.2.16",
+        "@opentui/solid": ">=0.2.16"
+      },
+      "peerDependenciesMeta": {
+        "@opentui/core": {
+          "optional": true
+        },
+        "@opentui/keymap": {
+          "optional": true
+        },
+        "@opentui/solid": {
+          "optional": true
+        }
+      }
+    },
+    "node_modules/@opencode-ai/sdk": {
+      "version": "1.15.13",
+      "resolved": "https://registry.npmjs.org/@opencode-ai/sdk/-/sdk-1.15.13.tgz",
+      "integrity": "sha512-4TwojIoQ8EG6/mVBuUVYZXiFcwNmiiytEnjnvyuvSJjGwFIlw2YIBFxtSVC3FbwwbwHT63teh1RHiQUUC4U5xw==",
+      "license": "MIT",
+      "dependencies": {
+        "cross-spawn": "7.0.6"
+      }
+    },
+    "node_modules/@standard-schema/spec": {
+      "version": "1.1.0",
+      "resolved": "https://registry.npmjs.org/@standard-schema/spec/-/spec-1.1.0.tgz",
+      "integrity": "sha512-l2aFy5jALhniG5HgqrD6jXLi/rUWrKvqN/qJx6yoJsgKhblVd+iqqU4RCXavm/jPityDo5TCvKMnpjKnOriy0w==",
+      "license": "MIT"
+    },
+    "node_modules/cross-spawn": {
+      "version": "7.0.6",
+      "resolved": "https://registry.npmjs.org/cross-spawn/-/cross-spawn-7.0.6.tgz",
+      "integrity": "sha512-uV2QOWP2nWzsy2aMp8aRibhi9dlzF5Hgh5SHaB9OiTGEyDTiJJyx0uy51QXdyWbtAHNua4XJzUKca3OzKUd3vA==",
+      "license": "MIT",
+      "dependencies": {
+        "path-key": "^3.1.0",
+        "shebang-command": "^2.0.0",
+        "which": "^2.0.1"
+      },
+      "engines": {
+        "node": ">= 8"
+      }
+    },
+    "node_modules/detect-libc": {
+      "version": "2.1.2",
+      "resolved": "https://registry.npmjs.org/detect-libc/-/detect-libc-2.1.2.tgz",
+      "integrity": "sha512-Btj2BOOO83o3WyH59e8MgXsxEQVcarkUOpEYrubB0urwnN10yQ364rsiByU11nZlqWYZm05i/of7io4mzihBtQ==",
+      "license": "Apache-2.0",
+      "optional": true,
+      "engines": {
+        "node": ">=8"
+      }
+    },
+    "node_modules/effect": {
+      "version": "4.0.0-beta.66",
+      "resolved": "https://registry.npmjs.org/effect/-/effect-4.0.0-beta.66.tgz",
+      "integrity": "sha512-4arEr62cziFa8BBVDUwJCJJmaVepXf/kRg7KtC0h8+bufngscrHbwWFhr9c+HonwOF+31U3iD3xUJmw9KzX7Dw==",
+      "license": "MIT",
+      "dependencies": {
+        "@standard-schema/spec": "^1.1.0",
+        "fast-check": "^4.6.0",
+        "find-my-way-ts": "^0.1.6",
+        "ini": "^6.0.0",
+        "kubernetes-types": "^1.30.0",
+        "msgpackr": "^1.11.9",
+        "multipasta": "^0.2.7",
+        "toml": "^4.1.1",
+        "uuid": "^13.0.0",
+        "yaml": "^2.8.3"
+      }
+    },
+    "node_modules/fast-check": {
+      "version": "4.8.0",
+      "resolved": "https://registry.npmjs.org/fast-check/-/fast-check-4.8.0.tgz",
+      "integrity": "sha512-GOJ158CUMnN6cSahsv4+ExARvIDuzzinFjkp0E9WtiBa5zcVeLozVkWaE4IzFcc+Y48Wp1EDlUZsXRyAztQcSg==",
+      "funding": [
+        {
+          "type": "individual",
+          "url": "https://github.com/sponsors/dubzzz"
+        },
+        {
+          "type": "opencollective",
+          "url": "https://opencollective.com/fast-check"
+        }
+      ],
+      "license": "MIT",
+      "dependencies": {
+        "pure-rand": "^8.0.0"
+      },
+      "engines": {
+        "node": ">=12.17.0"
+      }
+    },
+    "node_modules/find-my-way-ts": {
+      "version": "0.1.6",
+      "resolved": "https://registry.npmjs.org/find-my-way-ts/-/find-my-way-ts-0.1.6.tgz",
+      "integrity": "sha512-a85L9ZoXtNAey3Y6Z+eBWW658kO/MwR7zIafkIUPUMf3isZG0NCs2pjW2wtjxAKuJPxMAsHUIP4ZPGv0o5gyTA==",
+      "license": "MIT"
+    },
+    "node_modules/ini": {
+      "version": "6.0.0",
+      "resolved": "https://registry.npmjs.org/ini/-/ini-6.0.0.tgz",
+      "integrity": "sha512-IBTdIkzZNOpqm7q3dRqJvMaldXjDHWkEDfrwGEQTs5eaQMWV+djAhR+wahyNNMAa+qpbDUhBMVt4ZKNwpPm7xQ==",
+      "license": "ISC",
+      "engines": {
+        "node": "^20.17.0 || >=22.9.0"
+      }
+    },
+    "node_modules/isexe": {
+      "version": "2.0.0",
+      "resolved": "https://registry.npmjs.org/isexe/-/isexe-2.0.0.tgz",
+      "integrity": "sha512-RHxMLp9lnKHGHRng9QFhRCMbYAcVpn69smSGcq3f36xjgVVWThj4qqLbTLlq7Ssj8B+fIQ1EuCEGI2lKsyQeIw==",
+      "license": "ISC"
+    },
+    "node_modules/kubernetes-types": {
+      "version": "1.30.0",
+      "resolved": "https://registry.npmjs.org/kubernetes-types/-/kubernetes-types-1.30.0.tgz",
+      "integrity": "sha512-Dew1okvhM/SQcIa2rcgujNndZwU8VnSapDgdxlYoB84ZlpAD43U6KLAFqYo17ykSFGHNPrg0qry0bP+GJd9v7Q==",
+      "license": "Apache-2.0"
+    },
+    "node_modules/msgpackr": {
+      "version": "1.11.12",
+      "resolved": "https://registry.npmjs.org/msgpackr/-/msgpackr-1.11.12.tgz",
+      "integrity": "sha512-RBdJ1Un7yGlXWajrkxcSa93nvQ0w4zBf60c0yYv7YtBelP8H2FA7XsfBbMHtXKXUMUxH7zV3Zuozh+kUQWhHvg==",
+      "license": "MIT",
+      "optionalDependencies": {
+        "msgpackr-extract": "^3.0.2"
+      }
+    },
+    "node_modules/msgpackr-extract": {
+      "version": "3.0.4",
+      "resolved": "https://registry.npmjs.org/msgpackr-extract/-/msgpackr-extract-3.0.4.tgz",
+      "integrity": "sha512-4kmO/MdyUIkLIvTPr8VHLil4AtoKIoniWPIEk5+CDy0xnWC84azhSFmuJ7PxZdsYtiP5kEeQsORAVIeMgxT+Hw==",
+      "hasInstallScript": true,
+      "license": "MIT",
+      "optional": true,
+      "dependencies": {
+        "node-gyp-build-optional-packages": "5.2.2"
+      },
+      "bin": {
+        "download-msgpackr-prebuilds": "bin/download-prebuilds.js"
+      },
+      "optionalDependencies": {
+        "@msgpackr-extract/msgpackr-extract-darwin-arm64": "3.0.4",
+        "@msgpackr-extract/msgpackr-extract-darwin-x64": "3.0.4",
+        "@msgpackr-extract/msgpackr-extract-linux-arm": "3.0.4",
+        "@msgpackr-extract/msgpackr-extract-linux-arm64": "3.0.4",
+        "@msgpackr-extract/msgpackr-extract-linux-x64": "3.0.4",
+        "@msgpackr-extract/msgpackr-extract-win32-x64": "3.0.4"
+      }
+    },
+    "node_modules/multipasta": {
+      "version": "0.2.7",
+      "resolved": "https://registry.npmjs.org/multipasta/-/multipasta-0.2.7.tgz",
+      "integrity": "sha512-KPA58d68KgGil15oDqXjkUBEBYc00XvbPj5/X+dyzeo/lWm9Nc25pQRlf1D+gv4OpK7NM0J1odrbu9JNNGvynA==",
+      "license": "MIT"
+    },
+    "node_modules/node-gyp-build-optional-packages": {
+      "version": "5.2.2",
+      "resolved": "https://registry.npmjs.org/node-gyp-build-optional-packages/-/node-gyp-build-optional-packages-5.2.2.tgz",
+      "integrity": "sha512-s+w+rBWnpTMwSFbaE0UXsRlg7hU4FjekKU4eyAih5T8nJuNZT1nNsskXpxmeqSK9UzkBl6UgRlnKc8hz8IEqOw==",
+      "license": "MIT",
+      "optional": true,
+      "dependencies": {
+        "detect-libc": "^2.0.1"
+      },
+      "bin": {
+        "node-gyp-build-optional-packages": "bin.js",
+        "node-gyp-build-optional-packages-optional": "optional.js",
+        "node-gyp-build-optional-packages-test": "build-test.js"
+      }
+    },
+    "node_modules/path-key": {
+      "version": "3.1.1",
+      "resolved": "https://registry.npmjs.org/path-key/-/path-key-3.1.1.tgz",
+      "integrity": "sha512-ojmeN0qd+y0jszEtoY48r0Peq5dwMEkIlCOu6Q5f41lfkswXuKtYrhgoTpLnyIcHm24Uhqx+5Tqm2InSwLhE6Q==",
+      "license": "MIT",
+      "engines": {
+        "node": ">=8"
+      }
+    },
+    "node_modules/pure-rand": {
+      "version": "8.4.0",
+      "resolved": "https://registry.npmjs.org/pure-rand/-/pure-rand-8.4.0.tgz",
+      "integrity": "sha512-IoM8YF/jY0hiugFo/wOWqfmarlE6J0wc6fDK1PhftMk7MGhVZl88sZimmqBBFomLOCSmcCCpsfj7wXASCpvK9A==",
+      "funding": [
+        {
+          "type": "individual",
+          "url": "https://github.com/sponsors/dubzzz"
+        },
+        {
+          "type": "opencollective",
+          "url": "https://opencollective.com/fast-check"
+        }
+      ],
+      "license": "MIT"
+    },
+    "node_modules/shebang-command": {
+      "version": "2.0.0",
+      "resolved": "https://registry.npmjs.org/shebang-command/-/shebang-command-2.0.0.tgz",
+      "integrity": "sha512-kHxr2zZpYtdmrN1qDjrrX/Z1rR1kG8Dx+gkpK1G4eXmvXswmcE1hTWBWYUzlraYw1/yZp6YuDY77YtvbN0dmDA==",
+      "license": "MIT",
+      "dependencies": {
+        "shebang-regex": "^3.0.0"
+      },
+      "engines": {
+        "node": ">=8"
+      }
+    },
+    "node_modules/shebang-regex": {
+      "version": "3.0.0",
+      "resolved": "https://registry.npmjs.org/shebang-regex/-/shebang-regex-3.0.0.tgz",
+      "integrity": "sha512-7++dFhtcx3353uBaq8DDR4NuxBetBzC7ZQOhmTQInHEd6bSrXdiEyzCvG07Z44UYdLShWUyXt5M/yhz8ekcb1A==",
+      "license": "MIT",
+      "engines": {
+        "node": ">=8"
+      }
+    },
+    "node_modules/toml": {
+      "version": "4.1.1",
+      "resolved": "https://registry.npmjs.org/toml/-/toml-4.1.1.tgz",
+      "integrity": "sha512-EBJnVBr3dTXdA89WVFoAIPUqkBjxPMwRqsfuo1r240tKFHXv3zgca4+NJib/h6TyvGF7vOawz0jGuryJCdNHrw==",
+      "license": "MIT",
+      "engines": {
+        "node": ">=20"
+      }
+    },
+    "node_modules/uuid": {
+      "version": "13.0.2",
+      "resolved": "https://registry.npmjs.org/uuid/-/uuid-13.0.2.tgz",
+      "integrity": "sha512-vzi9uRZ926x4XV73S/4qQaTwPXM2JBj6/6lI/byHH1jOpCzb0zDbfytgA9LcN/hzb2l7WQSQnxITOVx5un/wGw==",
+      "funding": [
+        "https://github.com/sponsors/broofa",
+        "https://github.com/sponsors/ctavan"
+      ],
+      "license": "MIT",
+      "bin": {
+        "uuid": "dist-node/bin/uuid"
+      }
+    },
+    "node_modules/which": {
+      "version": "2.0.2",
+      "resolved": "https://registry.npmjs.org/which/-/which-2.0.2.tgz",
+      "integrity": "sha512-BLI3Tl1TW3Pvl70l3yq3Y64i+awpwXqsGBYWkkqMtnbXgrMD+yj7rhW0kuEDxzJaYXGjEW5ogapKNMEKNMjibA==",
+      "license": "ISC",
+      "dependencies": {
+        "isexe": "^2.0.0"
+      },
+      "bin": {
+        "node-which": "bin/node-which"
+      },
+      "engines": {
+        "node": ">= 8"
+      }
+    },
+    "node_modules/yaml": {
+      "version": "2.9.0",
+      "resolved": "https://registry.npmjs.org/yaml/-/yaml-2.9.0.tgz",
+      "integrity": "sha512-2AvhNX3mb8zd6Zy7INTtSpl1F15HW6Wnqj0srWlkKLcpYl/gMIMJiyuGq2KeI2YFxUPjdlB+3Lc10seMLtL4cA==",
+      "license": "ISC",
+      "bin": {
+        "yaml": "bin.mjs"
+      },
+      "engines": {
+        "node": ">= 14.6"
+      },
+      "funding": {
+        "url": "https://github.com/sponsors/eemeli"
+      }
+    },
+    "node_modules/zod": {
+      "version": "4.1.8",
+      "license": "MIT",
+      "funding": {
+        "url": "https://github.com/sponsors/colinhacks"
+      }
+    }
+  }
+}

AGENTS.md

@@ -31,26 +31,25 @@
 ## Model Configuration
 
 - Model `id` is **auto-injected** from filename (minus `.toml`) — never put `id` in TOML files
-- Models may reuse another model's definition via `extends` (see below); otherwise the full definition must be present in the file
+- Provider models may reuse provider-agnostic facts from `models/` via `base_model`; otherwise the full provider model definition must be present in the file
 - Schema uses `.strict()` — extra fields cause validation errors
 
-### `[extends]` (inheritance between models)
-- Syntax — a table at the top of the TOML:
+### Model metadata and `base_model`
+- Provider-agnostic model facts live under `models/<provider>/<model>.toml`
+- Provider TOMLs can inherit those facts with:
   ```toml
-  [extends]
-  from = "<provider-id>/<model-id>"   # required
-  omit = ["experimental.modes.fast"]  # optional, dot-path strings
+  base_model = "<provider-id>/<model-id>"
+  base_model_omit = ["limit.input"] # optional, dot-path strings
   ```
-  Example: `from = "anthropic/claude-opus-4-6"`
-- Resolved at parse time in `generate()`; the final JSON output contains **no** `extends` field — it exists only to cut duplication in the TOMLs
+  Example: `base_model = "anthropic/claude-opus-4-6"`
+- Resolved at parse time in `generate()`; the final provider JSON output contains **no** `base_model` or `base_model_omit` fields
 - Merge semantics:
-  - Plain objects (`[cost]`, `[limit]`, `[modalities]`, `[provider]`, `[experimental]`, …) are **deep-merged**
+  - Plain objects from metadata and provider TOML (`[limit]`, `[modalities]`, …) are **deep-merged**
   - Arrays (e.g. `modalities.input`) and primitives are **replaced** wholesale by the child
-  - Any field the child omits is inherited verbatim from the base
-- `omit` runs **after** the merge and deletes each dot-path from the result (used when the child needs to *remove* something the base defines, e.g. a provider-specific experimental mode). Every listed path must exist in the merged model, else an error is thrown. Ancestor tables that become empty as a result are also pruned, so `omit = ["experimental.modes.fast"]` yields no `experimental` key in the final JSON when `fast` was the only mode.
-- Chains are allowed (A extends B extends C); cycles throw
-- The base model must exist; `[extends.from]` pointing at a missing provider/model is an error
-- The `extends` table is stripped before schema validation, so the merged result must still satisfy the strict `Model` schema
+  - Any provider field omitted is inherited verbatim from model metadata
+  - `cost`, `provider`, `experimental`, `reasoning_options`, `interleaved`, and `status` are provider-specific and must be declared in provider TOMLs when needed
+- `base_model_omit` runs **after** the merge and deletes each dot-path from the result. Missing paths are ignored. Ancestor tables that become empty as a result are also pruned.
+- The base model metadata file must exist; `base_model` pointing at a missing `models/` entry is an error
 
 ### Bedrock Naming Patterns
 - Dated models: `-v1:0` suffix (`anthropic.claude-3-5-sonnet-20241022-v1:0.toml`)
@@ -72,4 +71,4 @@
 | `attachment`, `reasoning`, `tool_call`, `open_weights` | Yes | Boolean capabilities |
 | `cost`, `limit`, `modalities` | Yes | Objects with their own required fields |
 | `family`, `knowledge`, `temperature`, `structured_output` | No | Optional metadata |
-| `status` | No | Use for `"alpha"`, `"beta"`, `"deprecated"` lifecycle |
+| `status` | No | Use for `"alpha"`, `"beta"`, `"deprecated"` lifecycle |

README.md

@@ -24,6 +24,18 @@ curl https://models.dev/api.json
 
 Use the **Model ID** field to do a lookup on any model; it's the identifier used by [AI SDK](https://ai-sdk.dev/).
 
+Provider-agnostic model metadata is available separately:
+
+```bash
+curl https://models.dev/models.json
+```
+
+Use this for facts about the model itself, independent of where it is served. If you need both provider endpoints and model-only metadata in one response:
+
+```bash
+curl https://models.dev/catalog.json
+```
+
 ### Logos
 
 Provider logos are available as SVG files:
@@ -40,7 +52,71 @@ The data is stored in the repo as TOML files; organized by provider and model. T
 
 We need your help keeping the data up to date.
 
-### Adding a New Model
+### Adding Model Metadata
+
+Model-only facts live in `models/`, using the same path-style IDs as provider models. For example, `models/openai/gpt-5.toml` defines metadata for the underlying GPT-5 model, while `providers/openai/models/gpt-5.toml` defines OpenAI-specific serving details such as pricing.
+
+Use model metadata for provider-agnostic facts:
+
+- `name`, `family`, `release_date`, `last_updated`, `knowledge`
+- `attachment`, `reasoning`, `tool_call`, `structured_output`, `temperature`
+- `[limit]` defaults like context, input, and output token limits
+- `[modalities]` defaults
+- `open_weights`, `license`, `links`, `weights`, and `benchmarks`
+
+Example:
+
+```toml
+name = "GPT-5"
+family = "gpt"
+release_date = "2025-08-07"
+last_updated = "2025-08-07"
+attachment = true
+reasoning = true
+temperature = false
+tool_call = true
+structured_output = true
+open_weights = false
+
+[limit]
+context = 400_000
+input = 272_000
+output = 128_000
+
+[modalities]
+input = ["text", "image"]
+output = ["text"]
+
+[[benchmarks]]
+name = "Benchmark Name"
+score = 72.5
+metric = "accuracy"
+source = "https://example.com/results"
+
+[[weights]]
+label = "Model weights"
+url = "https://huggingface.co/example/model"
+format = "safetensors"
+```
+
+Provider TOMLs can inherit these facts with `base_model` and then keep only provider-specific fields or overrides:
+
+```toml
+base_model = "openai/gpt-5"
+
+[cost]
+input = 1.25
+output = 10.00
+cache_read = 0.125
+
+[limit]
+context = 200_000 # optional provider override
+output = 32_000
+```
+
+Provider fields win over model metadata during generation. Use this when the underlying model is the same but a provider serves it with different context limits, modalities, features, or pricing.
+
+### Adding a New Provider Model
 
 To add a new model, start by checking if the provider already exists in the `providers/` directory. If not, then:
 
@@ -120,6 +196,32 @@ output = ["text"]           # Supported output modalities
 field = "reasoning_content" # Name of the interleaved field "reasoning_content" or "reasoning_details"
 ```
 
+#### 3a. Reuse Model Metadata with `base_model`
+
+For wrapper providers that mirror an existing model, prefer referencing the model-only metadata instead of duplicating provider-agnostic fields.
+
+Use `base_model` when the provider serves the same underlying model and only provider-specific fields differ.
+
+```toml
+base_model = "anthropic/claude-opus-4-6"
+
+[cost]
+input = 5.00
+output = 25.00
+```
+
+Rules:
+
+- `base_model` must point to a TOML file in `models/` using `<provider>/<model-id>`.
+- You can override any top-level model field locally.
+- If you override a nested table like `[cost]`, `[limit]`, or `[modalities]`, include the full values needed for that table.
+- `base_model_omit` is optional and removes inherited model metadata fields after local overrides are merged. Use dot-path strings, for example `base_model_omit = ["limit.input"]`.
+- `id` still comes from the filename; do not add it to the TOML.
+
+Use `base_model` when the wrapper model is materially the same as the source model and only differs by provider-specific pricing, limits, modalities, provider request shape, or lifecycle flags.
+
+Sync and generator scripts should preserve existing `base_model` / `base_model_omit` fields when updating provider TOMLs. Do not use legacy `[extends]` tables.
+
 #### 4. Submit a Pull Request
 
 1. Fork this repo
@@ -136,9 +238,17 @@ There's a GitHub Action that will automatically validate your submission against
 - Values are within acceptable ranges
 - TOML syntax is valid
 
+When moving existing provider fields into model metadata, compare generated output before and after the change:
+
+```bash
+bun run compare:migrations
+```
+
+This prints a diff for each changed model TOML so you can confirm the generated JSON only changed where you intended.
+
 ### Schema Reference
 
-Models must conform to the following schema, as defined in `app/schemas.ts`.
+Models must conform to the following schema, as defined in `packages/core/src/schema.ts`.
 
 **Provider Schema:**
 

bun.lock

@@ -5,7 +5,7 @@
     "": {
       "name": "models.dev",
       "dependencies": {
-        "@cloudflare/workers-types": "^4.20250801.0",
+        "@cloudflare/workers-types": "^4.20260424.1",
         "sst": "3.17.23",
       },
     },
@@ -32,6 +32,7 @@
     "packages/web": {
       "name": "@models.dev/web",
       "dependencies": {
+        "@tanstack/virtual-core": "^3.14.0",
         "hono": "^4.8.0",
         "models.dev": "workspace:*",
       },
@@ -49,7 +50,7 @@
     "zod": "3.24.2",
   },
   "packages": {
-    "@cloudflare/workers-types": ["@cloudflare/workers-types@4.20250801.0", "", {}, "sha512-BQmMdoOGClY23TesgkR1PeGrPvPsSFD/zW7pDzWZHkOEsqkPk2A91h52bP8GbtKYTl1vdaYjQgJlGsP6Ih4G0w=="],
+    "@cloudflare/workers-types": ["@cloudflare/workers-types@4.20260424.1", "", {}, "sha512-0DLJ9yEk1KKzPbqop80Gw/P1wkKKzawmipULiJWdBXIBCoMvE0OVWms3IrL/Q/G7tfmPop9yF4XlZ69k9JLYng=="],
 
     "@modelcontextprotocol/sdk": ["@modelcontextprotocol/sdk@1.6.1", "", { "dependencies": { "content-type": "^1.0.5", "cors": "^2.8.5", "eventsource": "^3.0.2", "express": "^5.0.1", "express-rate-limit": "^7.5.0", "pkce-challenge": "^4.1.0", "raw-body": "^3.0.0", "zod": "^3.23.8", "zod-to-json-schema": "^3.24.1" } }, "sha512-oxzMzYCkZHMntzuyerehK3fV6A2Kwh5BD6CGEJSVDU2QNEhfLOptf2X7esQgaHZXHZY0oHmMsOtIDLP71UJXgA=="],
 
@@ -57,9 +58,11 @@
 
     "@models.dev/web": ["@models.dev/web@workspace:packages/web"],
 
+    "@tanstack/virtual-core": ["@tanstack/virtual-core@3.14.0", "", {}, "sha512-JLANqGy/D6k4Ujmh8Tr25lGimuOXNiaVyXaCAZS0W+1390sADdGnyUdSWNIfd49gebtIxGMij4IktRVzrdr12Q=="],
+
     "@tsconfig/bun": ["@tsconfig/bun@1.0.8", "", {}, "sha512-JlJaRaS4hBTypxtFe8WhnwV8blf0R+3yehLk8XuyxUYNx6VXsKCjACSCvOYEFUiqlhlBWxtYCn/zRlOb8BzBQg=="],
 
-    "@types/bun": ["@types/bun@1.2.16", "", { "dependencies": { "bun-types": "1.2.16" } }, "sha512-1aCZJ/6nSiViw339RsaNhkNoEloLaPzZhxMOYEa7OzRzO41IGg5n/7I43/ZIAW/c+Q6cT12Vf7fOZOoVIzb5BQ=="],
+    "@types/bun": ["@types/bun@1.3.0", "", { "dependencies": { "bun-types": "1.3.0" } }, "sha512-+lAGCYjXjip2qY375xX/scJeVRmZ5cY0wyHYyCYxNcdEXrQ4AOe3gACgd4iQ8ksOslJtW4VNxBJ8llUwc3a6AA=="],
 
     "@types/node": ["@types/node@22.13.9", "", { "dependencies": { "undici-types": "~6.20.0" } }, "sha512-acBjXdRJ3A6Pb3tqnw9HZmyR3Fiol3aGxRCK1x3d+6CDAMjl7I649wpSd+yNURCjbOUGu9tqtLKnTGxmK6CyGw=="],
 
@@ -79,7 +82,7 @@
 
     "buffer": ["buffer@4.9.2", "", { "dependencies": { "base64-js": "^1.0.2", "ieee754": "^1.1.4", "isarray": "^1.0.0" } }, "sha512-xq+q3SRMOxGivLhBNaUdC64hDTQwejJ+H0T/NB1XMtTVEwNTrfFF3gAxiyW0Bu/xWEGhjVKgUcMhCrUy2+uCWg=="],
 
-    "bun-types": ["bun-types@1.2.16", "", { "dependencies": { "@types/node": "*" } }, "sha512-ciXLrHV4PXax9vHvUrkvun9VPVGOVwbbbBF/Ev1cXz12lyEZMoJpIJABOfPcN9gDJRaiKF9MVbSygLg4NXu3/A=="],
+    "bun-types": ["bun-types@1.3.0", "", { "dependencies": { "@types/node": "*" }, "peerDependencies": { "@types/react": "^19" } }, "sha512-u8X0thhx+yJ0KmkxuEo9HAtdfgCBaM/aI9K90VQcQioAmkVp3SG3FkwWGibUFz3WdXAdcsqOcbU40lK7tbHdkQ=="],
 
     "bytes": ["bytes@3.1.2", "", {}, "sha512-/Nf7TyzTx6S3yRJObOAV7956r8cr2+Oj8AC5dt8wSP3BQAoeX58NoHyCU8P8zGkNXStjTSi6fzO6F0pBdcYbEg=="],
 
@@ -325,8 +328,6 @@
 
     "http-errors/statuses": ["statuses@2.0.1", "", {}, "sha512-RwNA9Z/7PrK06rYLIzFMlaF+l73iwpzsqRIFgbMLbTcLD6cOao82TaWefPXQvB2fOC4AjuYSEndS7N/mTCbkdQ=="],
 
-    "models.dev/@types/bun": ["@types/bun@1.3.0", "", { "dependencies": { "bun-types": "1.3.0" } }, "sha512-+lAGCYjXjip2qY375xX/scJeVRmZ5cY0wyHYyCYxNcdEXrQ4AOe3gACgd4iQ8ksOslJtW4VNxBJ8llUwc3a6AA=="],
-
     "opencontrol/@tsconfig/bun": ["@tsconfig/bun@1.0.7", "", {}, "sha512-udGrGJBNQdXGVulehc1aWT73wkR9wdaGBtB6yL70RJsqwW/yJhIg6ZbRlPOfIUiFNrnBuYLBi9CSmMKfDC7dvA=="],
 
     "opencontrol/hono": ["hono@4.7.4", "", {}, "sha512-Pst8FuGqz3L7tFF+u9Pu70eI0xa5S3LPUmrNd5Jm8nTHze9FxLTK9Kaj5g/k4UcwuJSXTP65SyHOPLrffpcAJg=="],
@@ -334,11 +335,5 @@
     "openid-client/jose": ["jose@4.15.9", "", {}, "sha512-1vUQX+IdDMVPj4k8kOxgUqlcK518yluMuGZwqlr44FS1ppZB/5GWh4rZG89erpOBOJjU/OBsnCVFfapsRz6nEA=="],
 
     "bun-types/@types/node/undici-types": ["undici-types@7.8.0", "", {}, "sha512-9UJ2xGDvQ43tYyVMpuHlsgApydB8ZKfVYTsLDhXkFL/6gfkp+U8xTGdh8pMJv1SpZna0zxG1DwsKZsreLbXBxw=="],
-
-    "models.dev/@types/bun/bun-types": ["bun-types@1.3.0", "", { "dependencies": { "@types/node": "*" }, "peerDependencies": { "@types/react": "^19" } }, "sha512-u8X0thhx+yJ0KmkxuEo9HAtdfgCBaM/aI9K90VQcQioAmkVp3SG3FkwWGibUFz3WdXAdcsqOcbU40lK7tbHdkQ=="],
-
-    "models.dev/@types/bun/bun-types/@types/node": ["@types/node@24.0.3", "", { "dependencies": { "undici-types": "~7.8.0" } }, "sha512-R4I/kzCYAdRLzfiCabn9hxWfbuHS573x+r0dJMkkzThEa7pbrcDWK+9zu3e7aBOouf+rQAciqPFMnxwr0aWgKg=="],
-
-    "models.dev/@types/bun/bun-types/@types/node/undici-types": ["undici-types@7.8.0", "", {}, "sha512-9UJ2xGDvQ43tYyVMpuHlsgApydB8ZKfVYTsLDhXkFL/6gfkp+U8xTGdh8pMJv1SpZna0zxG1DwsKZsreLbXBxw=="],
   }
 }

models/alibaba/qwen-flash.toml

@@ -0,0 +1,18 @@
+name = "Qwen Flash"
+family = "qwen"
+release_date = "2025-07-28"
+last_updated = "2025-07-28"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2024-04"
+open_weights = false
+
+[limit]
+context = 1_000_000
+output = 32_768
+
+[modalities]
+input = ["text"]
+output = ["text"]

models/alibaba/qwen-max.toml

@@ -0,0 +1,25 @@
+name = "Qwen Max"
+family = "qwen"
+release_date = "2024-04-03"
+last_updated = "2025-01-25"
+attachment = false
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2024-04"
+open_weights = false
+
+[limit]
+context = 32_768
+output = 8_192
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 21.8
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-01-28"

models/alibaba/qwen-omni-turbo.toml

@@ -0,0 +1,18 @@
+name = "Qwen-Omni Turbo"
+family = "qwen"
+release_date = "2025-01-19"
+last_updated = "2025-03-26"
+attachment = false
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2024-04"
+open_weights = false
+
+[limit]
+context = 32_768
+output = 2_048
+
+[modalities]
+input = ["text", "image", "audio", "video"]
+output = ["text", "audio"]

models/alibaba/qwen-plus.toml

@@ -0,0 +1,18 @@
+name = "Qwen Plus"
+family = "qwen"
+release_date = "2024-01-25"
+last_updated = "2025-09-11"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2024-04"
+open_weights = false
+
+[limit]
+context = 1_000_000
+output = 32_768
+
+[modalities]
+input = ["text"]
+output = ["text"]

models/alibaba/qwen-turbo.toml

@@ -1,20 +1,17 @@
-name = "Qwen: Qwen-Turbo"
+name = "Qwen Turbo"
+family = "qwen"
 release_date = "2024-11-01"
-last_updated = "2026-03-15"
+last_updated = "2025-04-28"
 attachment = false
-reasoning = false
+reasoning = true
 temperature = true
 tool_call = true
+knowledge = "2024-04"
 open_weights = false
 
-[cost]
-input = 0.0325
-output = 0.13
-cache_read = 0.01
-
 [limit]
-context = 131072
-output = 8192
+context = 1_000_000
+output = 16_384
 
 [modalities]
 input = ["text"]

models/alibaba/qwen-vl-max.toml

@@ -1,19 +1,17 @@
-name = "Qwen: Qwen VL Max"
+name = "Qwen-VL Max"
+family = "qwen"
 release_date = "2024-04-08"
 last_updated = "2025-08-13"
-attachment = true
+attachment = false
 reasoning = false
 temperature = true
 tool_call = true
+knowledge = "2024-04"
 open_weights = false
 
-[cost]
-input = 0.8
-output = 3.2
-
 [limit]
-context = 131072
-output = 32768
+context = 131_072
+output = 8_192
 
 [modalities]
 input = ["text", "image"]

models/alibaba/qwen-vl-plus.toml

@@ -0,0 +1,18 @@
+name = "Qwen-VL Plus"
+family = "qwen"
+release_date = "2024-01-25"
+last_updated = "2025-08-15"
+attachment = false
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2024-04"
+open_weights = false
+
+[limit]
+context = 131_072
+output = 8_192
+
+[modalities]
+input = ["text", "image"]
+output = ["text"]

models/alibaba/qwen2-5-vl-72b-instruct.toml

@@ -0,0 +1,22 @@
+name = "Qwen2.5-VL 72B Instruct"
+family = "qwen"
+release_date = "2024-09"
+last_updated = "2024-09"
+attachment = false
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2024-04"
+open_weights = true
+
+[limit]
+context = 131_072
+output = 8_192
+
+[modalities]
+input = ["text", "image"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/Qwen/Qwen2.5-VL-72B-Instruct"

models/alibaba/qwen3-235b-a22b.toml

@@ -0,0 +1,36 @@
+name = "Qwen3 235B-A22B"
+family = "qwen"
+release_date = "2025-04"
+last_updated = "2025-04"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2025-04"
+open_weights = true
+
+[limit]
+context = 131_072
+output = 16_384
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/Qwen/Qwen3-235B-A22B"
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 59.6
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-05-09"
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 21.41
+metric = "resolve rate"
+dataset = "public"
+source = "https://labs.scale.com/leaderboard/swe_bench_pro_public"

models/alibaba/qwen3-32b.toml

@@ -0,0 +1,29 @@
+name = "Qwen3 32B"
+family = "qwen"
+release_date = "2025-04"
+last_updated = "2025-04"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2025-04"
+open_weights = true
+
+[limit]
+context = 131_072
+output = 16_384
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/Qwen/Qwen3-32B"
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 40.0
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-05-08"

models/alibaba/qwen3-coder-30b-a3b-instruct.toml

@@ -0,0 +1,43 @@
+name = "Qwen3-Coder 30B-A3B Instruct"
+family = "qwen"
+release_date = "2025-04"
+last_updated = "2025-04"
+attachment = false
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2025-04"
+open_weights = true
+
+[limit]
+context = 262_144
+output = 65_536
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct"
+
+[[benchmarks]]
+name = "Artificial Analysis Coding Index"
+score = 19.4
+metric = "index"
+source = "https://openrouter.ai/qwen/qwen3-coder-30b-a3b-instruct/benchmarks"
+date = "2026-06-02"
+
+[[benchmarks]]
+name = "SciCode"
+score = 27.8
+metric = "percent correct"
+source = "https://openrouter.ai/qwen/qwen3-coder-30b-a3b-instruct/benchmarks"
+date = "2026-06-02"
+
+[[benchmarks]]
+name = "Terminal-Bench Hard"
+score = 15.2
+metric = "success rate"
+source = "https://openrouter.ai/qwen/qwen3-coder-30b-a3b-instruct/benchmarks"
+date = "2026-06-02"

models/alibaba/qwen3-coder-480b-a35b-instruct.toml

@@ -0,0 +1,29 @@
+name = "Qwen3-Coder 480B-A35B Instruct"
+family = "qwen"
+release_date = "2025-04"
+last_updated = "2025-04"
+attachment = false
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2025-04"
+open_weights = true
+
+[limit]
+context = 262_144
+output = 65_536
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/Qwen/Qwen3-Coder-480B-A35B-Instruct"
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 38.7
+metric = "resolve rate"
+dataset = "public"
+source = "https://labs.scale.com/leaderboard/swe_bench_pro_public"

models/alibaba/qwen3-coder-flash.toml

@@ -1,19 +1,16 @@
-name = "GLM 4.5 Air Derestricted Steam"
+name = "Qwen3 Coder Flash"
+family = "qwen"
 release_date = "2025-07-28"
 last_updated = "2025-07-28"
 attachment = false
 reasoning = false
-tool_call = false
-structured_output = false
+temperature = true
+tool_call = true
+knowledge = "2025-04"
 open_weights = false
 
-[cost]
-input = 0.306
-output = 0.306
-
 [limit]
-context = 220_600
-input = 220_600
+context = 1_000_000
 output = 65_536
 
 [modalities]

models/alibaba/qwen3-coder-plus.toml

@@ -1,21 +1,17 @@
-name = "Qwen3 Coder 480B A35B Instruct"
+name = "Qwen3 Coder Plus"
 family = "qwen"
 release_date = "2025-07-23"
-last_updated = "2025-10-04"
+last_updated = "2025-07-23"
 attachment = false
 reasoning = false
 temperature = true
-knowledge = "2025-04"
 tool_call = true
+knowledge = "2025-04"
 open_weights = false
 
-[cost]
-input = 0.40
-output = 1.80
-
 [limit]
-context = 262144
-output = 66536
+context = 1_048_576
+output = 65_536
 
 [modalities]
 input = ["text"]

models/alibaba/qwen3-max.toml

@@ -0,0 +1,39 @@
+name = "Qwen3 Max"
+family = "qwen"
+release_date = "2025-09-23"
+last_updated = "2025-09-23"
+attachment = false
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2025-04"
+open_weights = false
+
+[limit]
+context = 262_144
+output = 65_536
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[benchmarks]]
+name = "Artificial Analysis Coding Index"
+score = 26.4
+metric = "index"
+source = "https://openrouter.ai/qwen/qwen3-max/benchmarks"
+date = "2026-05-30"
+
+[[benchmarks]]
+name = "SciCode"
+score = 38.3
+metric = "percent correct"
+source = "https://openrouter.ai/qwen/qwen3-max/benchmarks"
+date = "2026-05-30"
+
+[[benchmarks]]
+name = "Terminal-Bench Hard"
+score = 20.5
+metric = "success rate"
+source = "https://openrouter.ai/qwen/qwen3-max/benchmarks"
+date = "2026-05-30"

models/alibaba/qwen3-next-80b-a3b-instruct.toml

@@ -0,0 +1,22 @@
+name = "Qwen3-Next 80B-A3B Instruct"
+family = "qwen"
+release_date = "2025-09"
+last_updated = "2025-09"
+attachment = false
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2025-04"
+open_weights = true
+
+[limit]
+context = 131_072
+output = 32_768
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/Qwen/Qwen3-Next-80B-A3B-Instruct"

models/alibaba/qwen3-next-80b-a3b-thinking.toml

@@ -0,0 +1,22 @@
+name = "Qwen3-Next 80B-A3B (Thinking)"
+family = "qwen"
+release_date = "2025-09"
+last_updated = "2025-09"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2025-04"
+open_weights = true
+
+[limit]
+context = 131_072
+output = 32_768
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/Qwen/Qwen3-Next-80B-A3B-Thinking"

models/alibaba/qwen3-vl-plus.toml

@@ -1,22 +1,18 @@
-name = "Qwen3 Max"
+name = "Qwen3-VL Plus"
 family = "qwen"
 release_date = "2025-09-23"
 last_updated = "2025-09-23"
 attachment = false
-reasoning = false
+reasoning = true
 temperature = true
-knowledge = "2025-04"
 tool_call = true
+knowledge = "2025-04"
 open_weights = false
 
-[cost]
-input = 0.34
-output = 1.37
-
 [limit]
 context = 262_144
-output = 65_536
+output = 32_768
 
 [modalities]
-input = ["text"]
+input = ["text", "image"]
 output = ["text"]

models/alibaba/qwen3.5-122b-a10b.toml

@@ -0,0 +1,28 @@
+name = "Qwen3.5 122B-A10B"
+family = "qwen"
+release_date = "2026-02-23"
+last_updated = "2026-02-23"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = true
+open_weights = true
+
+[limit]
+context = 262_144
+output = 65_536
+
+[modalities]
+input = ["text", "image", "video", "audio"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/Qwen/Qwen3.5-122B-A10B"
+
+[[benchmarks]]
+name = "SWE-Bench Verified"
+score = 72
+metric = "resolved"
+source = "https://huggingface.co/Qwen/Qwen3.5-122B-A10B"

models/alibaba/qwen3.5-27b.toml

@@ -0,0 +1,28 @@
+name = "Qwen3.5 27B"
+family = "qwen"
+release_date = "2026-02-23"
+last_updated = "2026-02-23"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = true
+open_weights = true
+
+[limit]
+context = 262_144
+output = 65_536
+
+[modalities]
+input = ["text", "image", "video", "audio"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/Qwen/Qwen3.5-27B"
+
+[[benchmarks]]
+name = "SWE-Bench Verified"
+score = 72.4
+metric = "resolved"
+source = "https://huggingface.co/Qwen/Qwen3.5-27B"

models/alibaba/qwen3.5-35b-a3b.toml

@@ -0,0 +1,22 @@
+name = "Qwen3.5 35B-A3B"
+family = "qwen"
+release_date = "2026-02-23"
+last_updated = "2026-02-23"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = true
+open_weights = true
+
+[limit]
+context = 262_144
+output = 65_536
+
+[modalities]
+input = ["text", "image", "video", "audio"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/Qwen/Qwen3.5-35B-A3B"

models/alibaba/qwen3.5-397b-a17b.toml

@@ -0,0 +1,28 @@
+name = "Qwen3.5 397B-A17B"
+family = "qwen"
+release_date = "2026-02-15"
+last_updated = "2026-02-15"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = true
+open_weights = true
+
+[limit]
+context = 262_144
+output = 65_536
+
+[modalities]
+input = ["text", "image", "video", "audio"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/Qwen/Qwen3.5-397B-A17B"
+
+[[benchmarks]]
+name = "SWE-Bench Verified"
+score = 76.4
+metric = "resolved"
+source = "https://huggingface.co/Qwen/Qwen3.5-397B-A17B"

models/alibaba/qwen3.5-plus.toml

@@ -1,18 +1,14 @@
-name = "Qwen 3.5 Plus"
+name = "Qwen3.5 Plus"
 family = "qwen"
 release_date = "2026-02-16"
 last_updated = "2026-02-16"
 attachment = false
 reasoning = true
 temperature = true
-knowledge = "2025-04"
 tool_call = true
+knowledge = "2025-04"
 open_weights = false
 
-[cost]
-input = 0.11
-output = 0.66
-
 [limit]
 context = 1_000_000
 output = 65_536

models/alibaba/qwen3.6-27b.toml

@@ -0,0 +1,28 @@
+name = "Qwen3.6 27B"
+family = "qwen"
+release_date = "2026-04-22"
+last_updated = "2026-04-22"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = true
+open_weights = true
+
+[limit]
+context = 262_144
+output = 65_536
+
+[modalities]
+input = ["text", "image", "video", "audio"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/Qwen/Qwen3.6-27B"
+
+[[benchmarks]]
+name = "SWE-Bench Verified"
+score = 77.2
+metric = "resolved"
+source = "https://huggingface.co/Qwen/Qwen3.6-27B"

models/alibaba/qwen3.6-35b-a3b.toml

@@ -0,0 +1,28 @@
+name = "Qwen3.6 35B-A3B"
+family = "qwen"
+release_date = "2026-04-17"
+last_updated = "2026-04-17"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = true
+open_weights = true
+
+[limit]
+context = 262_144
+output = 65_536
+
+[modalities]
+input = ["text", "image", "video", "audio"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/Qwen/Qwen3.6-35B-A3B"
+
+[[benchmarks]]
+name = "SWE-Bench Verified"
+score = 73.4
+metric = "resolved"
+source = "https://huggingface.co/Qwen/Qwen3.6-35B-A3B"

models/alibaba/qwen3.6-flash.toml

@@ -1,21 +1,17 @@
-name = "Nova Premier"
-family = "nova"
-release_date = "2024-12-03"
-last_updated = "2024-12-03"
+name = "Qwen3.6 Flash"
+family = "qwen3.6"
+release_date = "2026-04-27"
+last_updated = "2026-04-27"
 attachment = true
 reasoning = true
 temperature = true
-knowledge = "2024-10"
 tool_call = true
+structured_output = true
 open_weights = false
 
-[cost]
-input = 2.50
-output = 12.50
-
 [limit]
 context = 1_000_000
-output = 16_384
+output = 65_536
 
 [modalities]
 input = ["text", "image", "video"]

models/alibaba/qwen3.6-max-preview.toml

@@ -0,0 +1,18 @@
+name = "Qwen3.6 Max Preview"
+family = "qwen"
+release_date = "2026-04-20"
+last_updated = "2026-04-20"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2025-04"
+open_weights = false
+
+[limit]
+context = 262_144
+output = 65_536
+
+[modalities]
+input = ["text"]
+output = ["text"]

models/alibaba/qwen3.6-plus.toml

@@ -0,0 +1,18 @@
+name = "Qwen3.6 Plus"
+family = "qwen"
+release_date = "2026-04-02"
+last_updated = "2026-04-02"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2025-04"
+open_weights = false
+
+[limit]
+context = 1_000_000
+output = 65_536
+
+[modalities]
+input = ["text", "image", "video"]
+output = ["text"]

models/alibaba/qwen3.7-max.toml

@@ -0,0 +1,17 @@
+name = "Qwen3.7 Max"
+family = "qwen"
+release_date = "2026-05-21"
+last_updated = "2026-05-21"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+open_weights = false
+
+[limit]
+context = 1_000_000
+output = 65_536
+
+[modalities]
+input = ["text"]
+output = ["text"]

models/alibaba/qwen3.7-plus.toml

@@ -0,0 +1,18 @@
+name = "Qwen3.7 Plus"
+family = "qwen"
+release_date = "2026-06-02"
+last_updated = "2026-06-02"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2025-04"
+open_weights = false
+
+[limit]
+context = 131_072
+output = 16_384
+
+[modalities]
+input = ["text"]
+output = ["text"]

models/alibaba/qwq-plus.toml

@@ -1,22 +1,18 @@
-name = "Qwen3-235B-A22B"
+name = "QwQ Plus"
 family = "qwen"
-release_date = "2024-12-01"
-last_updated = "2025-09-05"
+release_date = "2025-03-05"
+last_updated = "2025-03-05"
 attachment = false
 reasoning = true
 temperature = true
-knowledge = "2024-12"
 tool_call = true
+knowledge = "2024-04"
 open_weights = false
 
-[cost]
-input = 0.0
-output = 0.0
-
 [limit]
 context = 131_072
 output = 8_192
 
 [modalities]
 input = ["text"]
-output = ["text"]
+output = ["text"]

models/anthropic/claude-3-5-haiku-20241022.toml

@@ -0,0 +1,25 @@
+name = "Claude Haiku 3.5"
+family = "claude-haiku"
+release_date = "2024-10-22"
+last_updated = "2024-10-22"
+attachment = true
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2024-07-31"
+open_weights = false
+
+[limit]
+context = 200_000
+output = 8_192
+
+[modalities]
+input = ["text", "image", "pdf"]
+output = ["text"]
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 28.0
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2024-12-21"

models/anthropic/claude-3-5-sonnet-20241022.toml

@@ -0,0 +1,25 @@
+name = "Claude Sonnet 3.5 v2"
+family = "claude-sonnet"
+release_date = "2024-10-22"
+last_updated = "2024-10-22"
+attachment = true
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2024-04-30"
+open_weights = false
+
+[limit]
+context = 200_000
+output = 8_192
+
+[modalities]
+input = ["text", "image", "pdf"]
+output = ["text"]
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 51.6
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-01-17"

models/anthropic/claude-3-7-sonnet-20250219.toml

@@ -6,19 +6,20 @@ attachment = true
 reasoning = true
 temperature = true
 tool_call = true
-knowledge = "2024-01"
+knowledge = "2024-10-31"
 open_weights = false
 
-[cost]
-input = 15.00
-output = 75.00
-cache_read = 1.50
-cache_write = 18.75
-
 [limit]
 context = 200_000
-output = 128_000
+output = 64_000
 
 [modalities]
 input = ["text", "image", "pdf"]
 output = ["text"]
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 64.9
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-02-24"

models/anthropic/claude-haiku-4-5-20251001.toml

@@ -1,19 +1,16 @@
-name = "Claude 3.7 Sonnet Thinking (8K)"
-release_date = "2025-02-24"
-last_updated = "2025-02-24"
+name = "Claude Haiku 4.5"
+family = "claude-haiku"
+release_date = "2025-10-15"
+last_updated = "2025-10-15"
 attachment = true
 reasoning = true
+temperature = true
 tool_call = true
-structured_output = true
+knowledge = "2025-02-28"
 open_weights = false
 
-[cost]
-input = 2.992
-output = 14.994
-
 [limit]
 context = 200_000
-input = 200_000
 output = 64_000
 
 [modalities]

models/anthropic/claude-haiku-4-5.toml

@@ -0,0 +1,25 @@
+name = "Claude Haiku 4.5 (latest)"
+family = "claude-haiku"
+release_date = "2025-10-15"
+last_updated = "2025-10-15"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2025-02-28"
+open_weights = false
+
+[limit]
+context = 200_000
+output = 64_000
+
+[modalities]
+input = ["text", "image", "pdf"]
+output = ["text"]
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 39.45
+metric = "resolve rate"
+dataset = "public"
+source = "https://labs.scale.com/leaderboard/swe_bench_pro_public"

models/anthropic/claude-opus-4-0.toml

@@ -0,0 +1,25 @@
+name = "Claude Opus 4 (latest)"
+family = "claude-opus"
+release_date = "2025-05-22"
+last_updated = "2025-05-22"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2025-03-31"
+open_weights = false
+
+[limit]
+context = 200_000
+output = 32_000
+
+[modalities]
+input = ["text", "image", "pdf"]
+output = ["text"]
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 72.0
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-05-25"

models/anthropic/claude-opus-4-1-20250805.toml

@@ -5,18 +5,14 @@ last_updated = "2025-08-05"
 attachment = true
 reasoning = true
 temperature = true
-tool_call = false
+tool_call = true
 knowledge = "2025-03-31"
 open_weights = false
 
-[cost]
-input = 0
-output = 0
-
 [limit]
-context = 80_000
-output = 16_000
+context = 200_000
+output = 32_000
 
 [modalities]
-input = ["text", "image"]
+input = ["text", "image", "pdf"]
 output = ["text"]

models/anthropic/claude-opus-4-1.toml

@@ -1,4 +1,4 @@
-name = "Claude Opus 4.1"
+name = "Claude Opus 4.1 (latest)"
 family = "claude-opus"
 release_date = "2025-08-05"
 last_updated = "2025-08-05"
@@ -9,12 +9,6 @@ tool_call = true
 knowledge = "2025-03-31"
 open_weights = false
 
-[cost]
-input = 16.50
-output = 82.50
-cache_read = 1.50
-cache_write = 18.75
-
 [limit]
 context = 200_000
 output = 32_000

models/anthropic/claude-opus-4-20250514.toml

@@ -0,0 +1,25 @@
+name = "Claude Opus 4"
+family = "claude-opus"
+release_date = "2025-05-22"
+last_updated = "2025-05-22"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2025-03-31"
+open_weights = false
+
+[limit]
+context = 200_000
+output = 32_000
+
+[modalities]
+input = ["text", "image", "pdf"]
+output = ["text"]
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 72.0
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-05-25"

models/anthropic/claude-opus-4-5-20251101.toml

@@ -0,0 +1,25 @@
+name = "Claude Opus 4.5"
+family = "claude-opus"
+release_date = "2025-11-01"
+last_updated = "2025-11-01"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2025-03-31"
+open_weights = false
+
+[limit]
+context = 200_000
+output = 64_000
+
+[modalities]
+input = ["text", "image", "pdf"]
+output = ["text"]
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 45.89
+metric = "resolve rate"
+dataset = "public"
+source = "https://labs.scale.com/leaderboard/swe_bench_pro_public"

models/anthropic/claude-opus-4-5.toml

@@ -0,0 +1,18 @@
+name = "Claude Opus 4.5 (latest)"
+family = "claude-opus"
+release_date = "2025-11-24"
+last_updated = "2025-11-24"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2025-03-31"
+open_weights = false
+
+[limit]
+context = 200_000
+output = 64_000
+
+[modalities]
+input = ["text", "image", "pdf"]
+output = ["text"]

models/anthropic/claude-opus-4-6.toml

@@ -0,0 +1,94 @@
+name = "Claude Opus 4.6"
+family = "claude-opus"
+release_date = "2026-02-05"
+last_updated = "2026-03-13"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2025-05-31"
+open_weights = false
+
+[limit]
+context = 1_000_000
+output = 128_000
+
+[modalities]
+input = ["text", "image", "pdf"]
+output = ["text"]
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 51.9
+metric = "resolve rate"
+dataset = "public"
+source = "https://labs.scale.com/leaderboard/swe_bench_pro_public"
+
+[[benchmarks]]
+name = "SWE-Atlas Codebase QnA"
+score = 33.3
+metric = "score"
+harness = "Claude Code"
+source = "https://labs.scale.com/leaderboard/sweatlas-qna"
+
+[[benchmarks]]
+name = "SWE-Atlas Codebase QnA"
+score = 30
+metric = "score"
+harness = "Mini-SWE-Agent"
+source = "https://labs.scale.com/leaderboard/sweatlas-qna"
+
+[[benchmarks]]
+name = "SWE-Atlas Refactoring"
+score = 35.58
+metric = "score"
+harness = "Claude Code"
+source = "https://labs.scale.com/leaderboard/sweatlas-refactoring"
+
+[[benchmarks]]
+name = "SWE-Atlas Test Writing"
+score = 36.67
+metric = "score"
+harness = "Claude Code"
+source = "https://labs.scale.com/leaderboard/sweatlas-tw"
+
+[[benchmarks]]
+name = "SWE-Atlas Test Writing"
+score = 36.08
+metric = "score"
+harness = "Mini-SWE-Agent"
+source = "https://labs.scale.com/leaderboard/sweatlas-tw"
+
+[[benchmarks]]
+name = "Artificial Analysis Coding Agent Index"
+score = 51.3
+metric = "average pass@1"
+harness = "Claude Code"
+variant = "medium"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "SWE-Atlas Codebase QnA"
+score = 71.9
+metric = "pass@1"
+harness = "Claude Code"
+variant = "medium"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 11.8
+metric = "pass@1"
+harness = "Claude Code"
+variant = "medium"
+dataset = "hard-aa"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "Terminal-Bench"
+score = 70.2
+metric = "pass@1"
+harness = "Claude Code"
+variant = "medium"
+version = "2.1"
+source = "https://artificialanalysis.ai/agents/coding-agents"

models/anthropic/claude-opus-4-7.toml

@@ -0,0 +1,143 @@
+name = "Claude Opus 4.7"
+family = "claude-opus"
+release_date = "2026-04-16"
+last_updated = "2026-04-16"
+attachment = true
+reasoning = true
+temperature = false
+tool_call = true
+knowledge = "2026-01-31"
+open_weights = false
+
+[limit]
+context = 1_000_000
+output = 128_000
+
+[modalities]
+input = ["text", "image", "pdf"]
+output = ["text"]
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 64.3
+metric = "resolve rate"
+source = "https://www.anthropic.com/news/claude-opus-4-8"
+date = "2026-05-28"
+
+[[benchmarks]]
+name = "Terminal-Bench"
+score = 66.1
+metric = "success rate"
+harness = "Terminus-2"
+version = "2.1"
+source = "https://www.anthropic.com/news/claude-opus-4-8"
+date = "2026-05-28"
+
+[[benchmarks]]
+name = "SWE-Atlas Refactoring"
+score = 48.57
+metric = "score"
+harness = "Claude Code"
+source = "https://labs.scale.com/leaderboard/sweatlas-refactoring"
+
+[[benchmarks]]
+name = "Artificial Analysis Coding Agent Index"
+score = 66.6
+metric = "average pass@1"
+harness = "Claude Code"
+variant = "max"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "SWE-Atlas Codebase QnA"
+score = 81
+metric = "pass@1"
+harness = "Claude Code"
+variant = "max"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 44.9
+metric = "pass@1"
+harness = "Claude Code"
+variant = "max"
+dataset = "hard-aa"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "Terminal-Bench"
+score = 73.8
+metric = "pass@1"
+harness = "Claude Code"
+variant = "max"
+version = "2.1"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "Artificial Analysis Coding Agent Index"
+score = 61.2
+metric = "average pass@1"
+harness = "Cursor CLI"
+variant = "medium"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "SWE-Atlas Codebase QnA"
+score = 78.4
+metric = "pass@1"
+harness = "Cursor CLI"
+variant = "medium"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 34.4
+metric = "pass@1"
+harness = "Cursor CLI"
+variant = "medium"
+dataset = "hard-aa"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "Terminal-Bench"
+score = 70.6
+metric = "pass@1"
+harness = "Cursor CLI"
+variant = "medium"
+version = "2.1"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "Artificial Analysis Coding Agent Index"
+score = 59.9
+metric = "average pass@1"
+harness = "Claude Code"
+variant = "medium"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "SWE-Atlas Codebase QnA"
+score = 71.7
+metric = "pass@1"
+harness = "Claude Code"
+variant = "medium"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 36.4
+metric = "pass@1"
+harness = "Claude Code"
+variant = "medium"
+dataset = "hard-aa"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "Terminal-Bench"
+score = 71.4
+metric = "pass@1"
+harness = "Claude Code"
+variant = "medium"
+version = "2.1"
+source = "https://artificialanalysis.ai/agents/coding-agents"

models/anthropic/claude-opus-4-8.toml

@@ -0,0 +1,33 @@
+name = "Claude Opus 4.8"
+family = "claude-opus"
+release_date = "2026-05-28"
+last_updated = "2026-05-28"
+attachment = true
+reasoning = true
+temperature = false
+tool_call = true
+open_weights = false
+
+[limit]
+context = 1_000_000
+output = 128_000
+
+[modalities]
+input = ["text", "image", "pdf"]
+output = ["text"]
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 69.2
+metric = "resolve rate"
+source = "https://www.anthropic.com/news/claude-opus-4-8"
+date = "2026-05-28"
+
+[[benchmarks]]
+name = "Terminal-Bench"
+score = 74.6
+metric = "success rate"
+harness = "Terminus-2"
+version = "2.1"
+source = "https://www.anthropic.com/news/claude-opus-4-8"
+date = "2026-05-28"

models/anthropic/claude-sonnet-4-0.toml

@@ -0,0 +1,32 @@
+name = "Claude Sonnet 4 (latest)"
+family = "claude-sonnet"
+release_date = "2025-05-22"
+last_updated = "2025-05-22"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2025-03-31"
+open_weights = false
+
+[limit]
+context = 200_000
+output = 64_000
+
+[modalities]
+input = ["text", "image", "pdf"]
+output = ["text"]
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 61.3
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-05-24"
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 42.7
+metric = "resolve rate"
+dataset = "public"
+source = "https://labs.scale.com/leaderboard/swe_bench_pro_public"

models/anthropic/claude-sonnet-4-20250514.toml

@@ -1,20 +1,14 @@
-name = "Claude Sonnet 4 (US)"
+name = "Claude Sonnet 4"
 family = "claude-sonnet"
 release_date = "2025-05-22"
 last_updated = "2025-05-22"
 attachment = true
 reasoning = true
 temperature = true
-knowledge = "2024-04"
 tool_call = true
+knowledge = "2025-03-31"
 open_weights = false
 
-[cost]
-input = 3.00
-output = 15.00
-cache_read = 0.30
-cache_write = 3.75
-
 [limit]
 context = 200_000
 output = 64_000
@@ -22,3 +16,10 @@ output = 64_000
 [modalities]
 input = ["text", "image", "pdf"]
 output = ["text"]
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 61.3
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-05-24"

models/anthropic/claude-sonnet-4-5-20250929.toml

@@ -9,12 +9,6 @@ tool_call = true
 knowledge = "2025-07-31"
 open_weights = false
 
-[cost]
-input = 3.30
-output = 16.50
-cache_read = 0.30
-cache_write = 3.75
-
 [limit]
 context = 200_000
 output = 64_000

models/anthropic/claude-sonnet-4-5.toml

@@ -0,0 +1,25 @@
+name = "Claude Sonnet 4.5 (latest)"
+family = "claude-sonnet"
+release_date = "2025-09-29"
+last_updated = "2025-09-29"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2025-07-31"
+open_weights = false
+
+[limit]
+context = 200_000
+output = 64_000
+
+[modalities]
+input = ["text", "image", "pdf"]
+output = ["text"]
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 43.6
+metric = "resolve rate"
+dataset = "public"
+source = "https://labs.scale.com/leaderboard/swe_bench_pro_public"

models/anthropic/claude-sonnet-4-6.toml

@@ -0,0 +1,73 @@
+name = "Claude Sonnet 4.6"
+family = "claude-sonnet"
+release_date = "2026-02-17"
+last_updated = "2026-03-13"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2025-08-31"
+open_weights = false
+
+[limit]
+context = 1_000_000
+output = 64_000
+
+[modalities]
+input = ["text", "image", "pdf"]
+output = ["text"]
+
+[[benchmarks]]
+name = "SWE-Atlas Codebase QnA"
+score = 31.2
+metric = "score"
+harness = "Claude Code"
+source = "https://labs.scale.com/leaderboard/sweatlas-qna"
+
+[[benchmarks]]
+name = "SWE-Atlas Refactoring"
+score = 32.21
+metric = "score"
+harness = "Claude Code"
+source = "https://labs.scale.com/leaderboard/sweatlas-refactoring"
+
+[[benchmarks]]
+name = "SWE-Atlas Test Writing"
+score = 31.76
+metric = "score"
+harness = "Claude Code"
+source = "https://labs.scale.com/leaderboard/sweatlas-tw"
+
+[[benchmarks]]
+name = "Artificial Analysis Coding Agent Index"
+score = 49.4
+metric = "average pass@1"
+harness = "Claude Code"
+variant = "medium"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "SWE-Atlas Codebase QnA"
+score = 70.3
+metric = "pass@1"
+harness = "Claude Code"
+variant = "medium"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 14.9
+metric = "pass@1"
+harness = "Claude Code"
+variant = "medium"
+dataset = "hard-aa"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "Terminal-Bench"
+score = 63.1
+metric = "pass@1"
+harness = "Claude Code"
+variant = "medium"
+version = "2.1"
+source = "https://artificialanalysis.ai/agents/coding-agents"

models/cohere/command-a-03-2025.toml

@@ -0,0 +1,29 @@
+name = "Command A"
+family = "command-a"
+release_date = "2025-03-13"
+last_updated = "2025-03-13"
+attachment = false
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2024-06-01"
+open_weights = true
+
+[limit]
+context = 256_000
+output = 8_000
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/CohereLabs/c4ai-command-a-03-2025"
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 12.0
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-03-14"

models/cohere/command-r-08-2024.toml

@@ -0,0 +1,22 @@
+name = "Command R"
+family = "command-r"
+release_date = "2024-08-30"
+last_updated = "2024-08-30"
+attachment = false
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2024-06-01"
+open_weights = true
+
+[limit]
+context = 128_000
+output = 4_000
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/CohereLabs/c4ai-command-r-08-2024"

models/cohere/command-r-plus-08-2024.toml

@@ -0,0 +1,22 @@
+name = "Command R+"
+family = "command-r"
+release_date = "2024-08-30"
+last_updated = "2024-08-30"
+attachment = false
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2024-06-01"
+open_weights = true
+
+[limit]
+context = 128_000
+output = 4_000
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/CohereLabs/c4ai-command-r-plus-08-2024"

models/cohere/command-r7b-12-2024.toml

@@ -0,0 +1,22 @@
+name = "Command R7B"
+family = "command-r"
+release_date = "2024-02-27"
+last_updated = "2024-02-27"
+attachment = false
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2024-06-01"
+open_weights = true
+
+[limit]
+context = 128_000
+output = 4_000
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/CohereLabs/c4ai-command-r7b-12-2024"

models/deepseek/deepseek-chat.toml

@@ -0,0 +1,29 @@
+name = "DeepSeek Chat"
+family = "deepseek"
+release_date = "2025-12-01"
+last_updated = "2026-02-28"
+attachment = true
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2025-09"
+open_weights = true
+
+[limit]
+context = 1_000_000
+output = 384_000
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/deepseek-ai/DeepSeek-V3.2"
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 70.2
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-10-03"

models/deepseek/deepseek-r1.toml

@@ -0,0 +1,50 @@
+name = "DeepSeek-R1"
+family = "deepseek-thinking"
+release_date = "2025-01-20"
+last_updated = "2025-05-29"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2024-07"
+open_weights = true
+
+[limit]
+context = 128_000
+output = 32_768
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/deepseek-ai/DeepSeek-R1"
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 56.9
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-01-20"
+
+[[benchmarks]]
+name = "Artificial Analysis Coding Index"
+score = 15.9
+metric = "index"
+source = "https://openrouter.ai/deepseek/deepseek-r1/benchmarks"
+date = "2026-03-11"
+
+[[benchmarks]]
+name = "SciCode"
+score = 35.7
+metric = "percent correct"
+source = "https://openrouter.ai/deepseek/deepseek-r1/benchmarks"
+date = "2026-03-11"
+
+[[benchmarks]]
+name = "Terminal-Bench Hard"
+score = 6.1
+metric = "success rate"
+source = "https://openrouter.ai/deepseek/deepseek-r1/benchmarks"
+date = "2026-03-11"

models/deepseek/deepseek-reasoner.toml

@@ -0,0 +1,29 @@
+name = "DeepSeek Reasoner"
+family = "deepseek-thinking"
+release_date = "2025-12-01"
+last_updated = "2026-02-28"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+knowledge = "2025-09"
+open_weights = true
+
+[limit]
+context = 1_000_000
+output = 384_000
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/deepseek-ai/DeepSeek-V3.2"
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 74.2
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-10-03"

models/deepseek/deepseek-v4-flash.toml

@@ -0,0 +1,29 @@
+name = "DeepSeek V4 Flash"
+family = "deepseek-flash"
+release_date = "2026-04-24"
+last_updated = "2026-04-24"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = true
+knowledge = "2025-05"
+open_weights = true
+
+[limit]
+context = 1_000_000
+output = 384_000
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash"
+
+[[benchmarks]]
+name = "SWE-Bench Verified"
+score = 79
+metric = "resolved"
+source = "https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash"

models/deepseek/deepseek-v4-pro.toml

@@ -0,0 +1,63 @@
+name = "DeepSeek V4 Pro"
+family = "deepseek-thinking"
+release_date = "2026-04-24"
+last_updated = "2026-04-24"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = true
+knowledge = "2025-05"
+open_weights = true
+
+[limit]
+context = 1_000_000
+output = 384_000
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro"
+
+[[benchmarks]]
+name = "SWE-Bench Verified"
+score = 80.6
+metric = "resolved"
+source = "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro"
+
+[[benchmarks]]
+name = "Artificial Analysis Coding Agent Index"
+score = 50.1
+metric = "average pass@1"
+harness = "Claude Code"
+variant = "high"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "SWE-Atlas Codebase QnA"
+score = 67.8
+metric = "pass@1"
+harness = "Claude Code"
+variant = "high"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 18
+metric = "pass@1"
+harness = "Claude Code"
+variant = "high"
+dataset = "hard-aa"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "Terminal-Bench"
+score = 64.7
+metric = "pass@1"
+harness = "Claude Code"
+variant = "high"
+version = "2.1"
+source = "https://artificialanalysis.ai/agents/coding-agents"

models/google/gemini-2.0-flash-lite.toml

@@ -0,0 +1,19 @@
+name = "Gemini 2.0 Flash-Lite"
+family = "gemini-flash-lite"
+release_date = "2024-12-11"
+last_updated = "2024-12-11"
+attachment = true
+reasoning = false
+temperature = true
+tool_call = true
+structured_output = true
+knowledge = "2024-06"
+open_weights = false
+
+[limit]
+context = 1_048_576
+output = 8_192
+
+[modalities]
+input = ["text", "image", "audio", "video", "pdf"]
+output = ["text"]

models/google/gemini-2.0-flash.toml

@@ -5,16 +5,11 @@ last_updated = "2024-12-11"
 attachment = true
 reasoning = false
 temperature = true
-knowledge = "2024-06"
 tool_call = true
 structured_output = true
+knowledge = "2024-06"
 open_weights = false
 
-[cost]
-input = 0.10
-output = 0.40
-cache_read = 0.025
-
 [limit]
 context = 1_048_576
 output = 8_192

models/google/gemini-2.5-flash-image.toml

@@ -1,23 +1,18 @@
-name = "Gemini 2.5 Flash Image (Preview)"
+name = "Nano Banana"
 family = "gemini-flash"
 release_date = "2025-08-26"
 last_updated = "2025-08-26"
 attachment = true
 reasoning = true
 temperature = true
-knowledge = "2025-06"
 tool_call = false
+knowledge = "2025-06"
 open_weights = false
 
-[cost]
-input = 0.30
-output = 30
-cache_read = 0.075
-
 [limit]
 context = 32_768
 output = 32_768
 
 [modalities]
 input = ["text", "image"]
-output = ["text", "image"]
+output = ["text", "image"]

models/google/gemini-2.5-flash-lite.toml

@@ -0,0 +1,40 @@
+name = "Gemini 2.5 Flash-Lite"
+family = "gemini-flash-lite"
+release_date = "2025-06-17"
+last_updated = "2025-06-17"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = true
+knowledge = "2025-01"
+open_weights = false
+
+[limit]
+context = 1_048_576
+output = 65_536
+
+[modalities]
+input = ["text", "image", "audio", "video", "pdf"]
+output = ["text"]
+
+[[benchmarks]]
+name = "Artificial Analysis Coding Index"
+score = 9.5
+metric = "index"
+source = "https://openrouter.ai/google/gemini-2.5-flash-lite/benchmarks"
+date = "2026-03-11"
+
+[[benchmarks]]
+name = "SciCode"
+score = 19.3
+metric = "percent correct"
+source = "https://openrouter.ai/google/gemini-2.5-flash-lite/benchmarks"
+date = "2026-03-11"
+
+[[benchmarks]]
+name = "Terminal-Bench Hard"
+score = 4.5
+metric = "success rate"
+source = "https://openrouter.ai/google/gemini-2.5-flash-lite/benchmarks"
+date = "2026-03-11"

models/google/gemini-2.5-flash.toml

@@ -0,0 +1,47 @@
+name = "Gemini 2.5 Flash"
+family = "gemini-flash"
+release_date = "2025-03-20"
+last_updated = "2025-06-05"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = true
+knowledge = "2025-01"
+open_weights = false
+
+[limit]
+context = 1_048_576
+output = 65_536
+
+[modalities]
+input = ["text", "image", "audio", "video", "pdf"]
+output = ["text"]
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 55.1
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-05-25"
+
+[[benchmarks]]
+name = "Artificial Analysis Coding Index"
+score = 22.2
+metric = "index"
+source = "https://openrouter.ai/google/gemini-2.5-flash/benchmarks"
+date = "2026-06-02"
+
+[[benchmarks]]
+name = "SciCode"
+score = 39.4
+metric = "percent correct"
+source = "https://openrouter.ai/google/gemini-2.5-flash/benchmarks"
+date = "2026-06-02"
+
+[[benchmarks]]
+name = "Terminal-Bench Hard"
+score = 13.6
+metric = "success rate"
+source = "https://openrouter.ai/google/gemini-2.5-flash/benchmarks"
+date = "2026-06-02"

models/google/gemini-2.5-pro.toml

@@ -0,0 +1,47 @@
+name = "Gemini 2.5 Pro"
+family = "gemini-pro"
+release_date = "2025-03-20"
+last_updated = "2025-06-05"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = true
+knowledge = "2025-01"
+open_weights = false
+
+[limit]
+context = 1_048_576
+output = 65_536
+
+[modalities]
+input = ["text", "image", "audio", "video", "pdf"]
+output = ["text"]
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 83.1
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-06-06"
+
+[[benchmarks]]
+name = "Artificial Analysis Coding Index"
+score = 32
+metric = "index"
+source = "https://openrouter.ai/google/gemini-2.5-pro/benchmarks"
+date = "2026-06-02"
+
+[[benchmarks]]
+name = "SciCode"
+score = 42.8
+metric = "percent correct"
+source = "https://openrouter.ai/google/gemini-2.5-pro/benchmarks"
+date = "2026-06-02"
+
+[[benchmarks]]
+name = "Terminal-Bench Hard"
+score = 26.5
+metric = "success rate"
+source = "https://openrouter.ai/google/gemini-2.5-pro/benchmarks"
+date = "2026-06-02"

models/google/gemini-3-flash-preview.toml

@@ -0,0 +1,47 @@
+name = "Gemini 3 Flash Preview"
+family = "gemini-flash"
+release_date = "2025-12-17"
+last_updated = "2025-12-17"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = true
+knowledge = "2025-01"
+open_weights = false
+
+[limit]
+context = 1_048_576
+output = 65_536
+
+[modalities]
+input = ["text", "image", "video", "audio", "pdf"]
+output = ["text"]
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 34.63
+metric = "resolve rate"
+dataset = "public"
+source = "https://labs.scale.com/leaderboard/swe_bench_pro_public"
+
+[[benchmarks]]
+name = "SWE-Atlas Codebase QnA"
+score = 8.2
+metric = "score"
+harness = "Mini-SWE-Agent"
+source = "https://labs.scale.com/leaderboard/sweatlas-qna"
+
+[[benchmarks]]
+name = "SWE-Atlas Refactoring"
+score = 10
+metric = "score"
+harness = "Mini-SWE-Agent"
+source = "https://labs.scale.com/leaderboard/sweatlas-refactoring"
+
+[[benchmarks]]
+name = "SWE-Atlas Test Writing"
+score = 30.3
+metric = "score"
+harness = "Mini-SWE-Agent"
+source = "https://labs.scale.com/leaderboard/sweatlas-tw"

models/google/gemini-3-pro-preview.toml

@@ -10,15 +10,17 @@ structured_output = true
 knowledge = "2025-01"
 open_weights = false
 
-[cost]
-input = 2
-output = 12
-cache_read = 0.2
-
 [limit]
-context = 1_000_000
-output = 64_000
+context = 1_048_576
+output = 65_536
 
 [modalities]
 input = ["text", "image", "video", "audio", "pdf"]
 output = ["text"]
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 43.3
+metric = "resolve rate"
+dataset = "public"
+source = "https://labs.scale.com/leaderboard/swe_bench_pro_public"

models/google/gemini-3.1-flash-image-preview.toml

@@ -0,0 +1,18 @@
+name = "Nano Banana 2"
+family = "gemini-flash"
+release_date = "2026-02-26"
+last_updated = "2026-02-26"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = false
+knowledge = "2025-01"
+open_weights = false
+
+[limit]
+context = 65_536
+output = 65_536
+
+[modalities]
+input = ["text", "image", "pdf"]
+output = ["text", "image"]

models/google/gemini-3.1-flash-lite-preview.toml

@@ -1,23 +1,19 @@
-name = "Gemini 2.5 Flash Lite Preview 09-25"
+name = "Gemini 3.1 Flash Lite Preview"
 family = "gemini-flash-lite"
-release_date = "2025-09-25"
-last_updated = "2025-09-25"
+release_date = "2026-03-03"
+last_updated = "2026-03-03"
 attachment = true
 reasoning = true
 temperature = true
-knowledge = "2025-01"
 tool_call = true
+structured_output = true
+knowledge = "2025-01"
 open_weights = false
 
-[cost]
-input = 0.10
-output = 0.40
-cache_read = 0.025
-
 [limit]
 context = 1_048_576
 output = 65_536
 
 [modalities]
-input = ["text", "image", "audio", "video", "pdf"]
+input = ["text", "image", "video", "audio", "pdf"]
 output = ["text"]

models/google/gemini-3.1-flash-lite.toml

@@ -0,0 +1,19 @@
+name = "Gemini 3.1 Flash Lite"
+family = "gemini-flash-lite"
+release_date = "2026-05-07"
+last_updated = "2026-05-07"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = true
+knowledge = "2025-01"
+open_weights = false
+
+[limit]
+context = 1_048_576
+output = 65_536
+
+[modalities]
+input = ["text", "image", "video", "audio", "pdf"]
+output = ["text"]

models/google/gemini-3.1-pro-preview-customtools.toml

@@ -0,0 +1,19 @@
+name = "Gemini 3.1 Pro Preview Custom Tools"
+family = "gemini-pro"
+release_date = "2026-02-19"
+last_updated = "2026-02-19"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = true
+knowledge = "2025-01"
+open_weights = false
+
+[limit]
+context = 1_048_576
+output = 65_536
+
+[modalities]
+input = ["text", "image", "video", "audio", "pdf"]
+output = ["text"]

models/google/gemini-3.1-pro-preview.toml

@@ -0,0 +1,97 @@
+name = "Gemini 3.1 Pro Preview"
+family = "gemini-pro"
+release_date = "2026-02-19"
+last_updated = "2026-02-19"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = true
+knowledge = "2025-01"
+open_weights = false
+
+[limit]
+context = 1_048_576
+output = 65_536
+
+[modalities]
+input = ["text", "image", "video", "audio", "pdf"]
+output = ["text"]
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 54.2
+metric = "resolve rate"
+source = "https://www.anthropic.com/news/claude-opus-4-8"
+date = "2026-05-28"
+
+[[benchmarks]]
+name = "Terminal-Bench"
+score = 70.3
+metric = "success rate"
+harness = "Terminus-2"
+version = "2.1"
+source = "https://www.anthropic.com/news/claude-opus-4-8"
+date = "2026-05-28"
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 46.1
+metric = "resolve rate"
+dataset = "public"
+source = "https://labs.scale.com/leaderboard/swe_bench_pro_public"
+
+[[benchmarks]]
+name = "SWE-Atlas Codebase QnA"
+score = 13.5
+metric = "score"
+harness = "Mini-SWE-Agent"
+source = "https://labs.scale.com/leaderboard/sweatlas-qna"
+
+[[benchmarks]]
+name = "SWE-Atlas Refactoring"
+score = 33.81
+metric = "score"
+harness = "Gemini CLI"
+source = "https://labs.scale.com/leaderboard/sweatlas-refactoring"
+
+[[benchmarks]]
+name = "SWE-Atlas Test Writing"
+score = 29.84
+metric = "score"
+harness = "Mini-SWE-Agent"
+source = "https://labs.scale.com/leaderboard/sweatlas-tw"
+
+[[benchmarks]]
+name = "Artificial Analysis Coding Agent Index"
+score = 43
+metric = "average pass@1"
+harness = "Gemini CLI"
+variant = "high"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "SWE-Atlas Codebase QnA"
+score = 45.6
+metric = "pass@1"
+harness = "Gemini CLI"
+variant = "high"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 15.1
+metric = "pass@1"
+harness = "Gemini CLI"
+variant = "high"
+dataset = "hard-aa"
+source = "https://artificialanalysis.ai/agents/coding-agents"
+
+[[benchmarks]]
+name = "Terminal-Bench"
+score = 68.3
+metric = "pass@1"
+harness = "Gemini CLI"
+variant = "high"
+version = "2.1"
+source = "https://artificialanalysis.ai/agents/coding-agents"

models/google/gemini-3.5-flash.toml

@@ -1,25 +1,19 @@
-name = "Gemini 2.5 Flash Preview 09-25"
+name = "Gemini 3.5 Flash"
 family = "gemini-flash"
-release_date = "2025-09-25"
-last_updated = "2025-09-25"
+release_date = "2026-05-19"
+last_updated = "2026-05-19"
 attachment = true
 reasoning = true
 temperature = true
-knowledge = "2025-01"
 tool_call = true
 structured_output = true
+knowledge = "2025-01"
 open_weights = false
 
-[cost]
-input = 0.30
-output = 2.50
-cache_read = 0.075
-input_audio = 1.00
-
 [limit]
 context = 1_048_576
 output = 65_536
 
 [modalities]
-input = ["text", "image", "audio", "video", "pdf"]
+input = ["text", "image", "video", "audio", "pdf"]
 output = ["text"]

models/google/gemini-embedding-001.toml

@@ -0,0 +1,18 @@
+name = "Gemini Embedding 001"
+family = "gemini"
+release_date = "2025-05-20"
+last_updated = "2025-05-20"
+attachment = false
+reasoning = false
+temperature = false
+tool_call = false
+knowledge = "2025-05"
+open_weights = false
+
+[limit]
+context = 2_048
+output = 1
+
+[modalities]
+input = ["text"]
+output = ["text"]

models/google/gemini-flash-latest.toml

@@ -1,20 +1,15 @@
-name = "Gemini 2.5 Flash Preview 09-25"
+name = "Gemini Flash Latest"
 family = "gemini-flash"
 release_date = "2025-09-25"
 last_updated = "2025-09-25"
 attachment = true
 reasoning = true
 temperature = true
-knowledge = "2025-01"
 tool_call = true
 structured_output = true
+knowledge = "2025-01"
 open_weights = false
 
-[cost]
-input = 0.30
-output = 2.50
-cache_read = 0.031
-
 [limit]
 context = 1_048_576
 output = 65_536

models/google/gemini-flash-lite-latest.toml

@@ -1,20 +1,15 @@
-name = "Gemini 2.5 Flash Lite Preview 09-25"
+name = "Gemini Flash-Lite Latest"
 family = "gemini-flash-lite"
 release_date = "2025-09-25"
 last_updated = "2025-09-25"
 attachment = true
 reasoning = true
 temperature = true
-knowledge = "2025-01"
 tool_call = true
 structured_output = true
+knowledge = "2025-01"
 open_weights = false
 
-[cost]
-input = 0.10
-output = 0.40
-cache_read = 0.025
-
 [limit]
 context = 1_048_576
 output = 65_536

models/google/gemma-4-26b-a4b-it.toml

@@ -0,0 +1,22 @@
+name = "Gemma 4 26B A4B IT"
+family = "gemma"
+release_date = "2026-04-02"
+last_updated = "2026-04-02"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = true
+open_weights = true
+
+[limit]
+context = 262_144
+output = 32_768
+
+[modalities]
+input = ["text", "image"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/google/gemma-4-26B-A4B-it"

models/google/gemma-4-31b-it.toml

@@ -0,0 +1,22 @@
+name = "Gemma 4 31B IT"
+family = "gemma"
+release_date = "2026-04-02"
+last_updated = "2026-04-02"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+structured_output = true
+open_weights = true
+
+[limit]
+context = 262_144
+output = 32_768
+
+[modalities]
+input = ["text", "image"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/google/gemma-4-31B-it"

models/meta/llama-3.3-70b-instruct.toml

@@ -0,0 +1,43 @@
+name = "Llama-3.3-70B-Instruct"
+family = "llama"
+release_date = "2024-12-06"
+last_updated = "2024-12-06"
+attachment = true
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2023-12"
+open_weights = true
+
+[limit]
+context = 128_000
+output = 4_096
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct"
+
+[[benchmarks]]
+name = "Artificial Analysis Coding Index"
+score = 10.7
+metric = "index"
+source = "https://openrouter.ai/meta-llama/llama-3.3-70b-instruct/benchmarks"
+date = "2026-03-11"
+
+[[benchmarks]]
+name = "SciCode"
+score = 26
+metric = "percent correct"
+source = "https://openrouter.ai/meta-llama/llama-3.3-70b-instruct/benchmarks"
+date = "2026-03-11"
+
+[[benchmarks]]
+name = "Terminal-Bench Hard"
+score = 3
+metric = "success rate"
+source = "https://openrouter.ai/meta-llama/llama-3.3-70b-instruct/benchmarks"
+date = "2026-03-11"

models/meta/llama-4-maverick-17b-instruct.toml

@@ -0,0 +1,36 @@
+name = "Llama 4 Maverick 17B Instruct"
+family = "llama"
+release_date = "2025-04-05"
+last_updated = "2025-04-05"
+attachment = true
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2024-08"
+open_weights = true
+
+[limit]
+context = 1_000_000
+output = 16_384
+
+[modalities]
+input = ["text", "image"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/meta-llama/Llama-4-Maverick-17B-128E-Instruct"
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 15.6
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-04-06"
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 5.24
+metric = "resolve rate"
+dataset = "public"
+source = "https://labs.scale.com/leaderboard/swe_bench_pro_public"

models/meta/llama-4-scout-17b-instruct.toml

@@ -0,0 +1,22 @@
+name = "Llama 4 Scout 17B Instruct"
+family = "llama"
+release_date = "2025-04-05"
+last_updated = "2025-04-05"
+attachment = true
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2024-08"
+open_weights = true
+
+[limit]
+context = 3_500_000
+output = 16_384
+
+[modalities]
+input = ["text", "image"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct"

models/minimax/MiniMax-M2.1.toml

@@ -0,0 +1,34 @@
+name = "MiniMax-M2.1"
+family = "minimax"
+release_date = "2025-12-23"
+last_updated = "2025-12-23"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+open_weights = true
+
+[limit]
+context = 204_800
+output = 131_072
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/MiniMaxAI/MiniMax-M2.1"
+
+[[benchmarks]]
+name = "SWE-Bench Verified"
+score = 74
+metric = "resolved"
+source = "https://huggingface.co/MiniMaxAI/MiniMax-M2.1"
+
+[[benchmarks]]
+name = "SWE-Bench Pro"
+score = 36.81
+metric = "resolve rate"
+dataset = "public"
+source = "https://labs.scale.com/leaderboard/swe_bench_pro_public"

models/minimax/MiniMax-M2.5-highspeed.toml

@@ -0,0 +1,21 @@
+name = "MiniMax-M2.5-highspeed"
+family = "minimax"
+release_date = "2026-02-13"
+last_updated = "2026-02-13"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+open_weights = true
+
+[limit]
+context = 204_800
+output = 131_072
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/MiniMaxAI/MiniMax-M2.5"

models/minimax/MiniMax-M2.5.toml

@@ -0,0 +1,48 @@
+name = "MiniMax-M2.5"
+family = "minimax"
+release_date = "2026-02-12"
+last_updated = "2026-02-12"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+open_weights = true
+
+[limit]
+context = 204_800
+output = 131_072
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/MiniMaxAI/MiniMax-M2.5"
+
+[[benchmarks]]
+name = "SWE-Bench Verified"
+score = 75.8
+metric = "resolved"
+source = "https://www.swebench.com/"
+
+[[benchmarks]]
+name = "SWE-Atlas Codebase QnA"
+score = 10.3
+metric = "score"
+harness = "Mini-SWE-Agent"
+source = "https://labs.scale.com/leaderboard/sweatlas-qna"
+
+[[benchmarks]]
+name = "SWE-Atlas Refactoring"
+score = 19.52
+metric = "score"
+harness = "Mini-SWE-Agent"
+source = "https://labs.scale.com/leaderboard/sweatlas-refactoring"
+
+[[benchmarks]]
+name = "SWE-Atlas Test Writing"
+score = 18.6
+metric = "score"
+harness = "Mini-SWE-Agent"
+source = "https://labs.scale.com/leaderboard/sweatlas-tw"

models/minimax/MiniMax-M2.7-highspeed.toml

@@ -0,0 +1,21 @@
+name = "MiniMax-M2.7-highspeed"
+family = "minimax"
+release_date = "2026-03-18"
+last_updated = "2026-03-18"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+open_weights = true
+
+[limit]
+context = 204_800
+output = 131_072
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/MiniMaxAI/MiniMax-M2.7"

models/minimax/MiniMax-M2.7.toml

@@ -1,20 +1,13 @@
-name = "MiniMax M2.1"
+name = "MiniMax-M2.7"
 family = "minimax"
+release_date = "2026-03-18"
+last_updated = "2026-03-18"
 attachment = false
 reasoning = true
-tool_call = true
 temperature = true
-release_date = "2025-12-23"
-last_updated = "2025-12-23"
+tool_call = true
 open_weights = true
 
-[interleaved]
-field = "reasoning_details"
-
-[cost]
-input = 0.29
-output = 1.15
-
 [limit]
 context = 204_800
 output = 131_072
@@ -23,3 +16,6 @@ output = 131_072
 input = ["text"]
 output = ["text"]
 
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/MiniMaxAI/MiniMax-M2.7"

models/minimax/MiniMax-M2.toml

@@ -0,0 +1,27 @@
+name = "MiniMax-M2"
+family = "minimax"
+release_date = "2025-10-27"
+last_updated = "2025-10-27"
+attachment = false
+reasoning = true
+temperature = true
+tool_call = true
+open_weights = true
+
+[limit]
+context = 196_608
+output = 128_000
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/MiniMaxAI/MiniMax-M2"
+
+[[benchmarks]]
+name = "SWE-Bench Verified"
+score = 69.4
+metric = "resolved"
+source = "https://huggingface.co/MiniMaxAI/MiniMax-M2"

models/minimax/MiniMax-M3.toml

@@ -0,0 +1,17 @@
+name = "MiniMax-M3"
+family = "minimax"
+release_date = "2026-06-01"
+last_updated = "2026-06-01"
+attachment = true
+reasoning = true
+temperature = true
+tool_call = true
+open_weights = false
+
+[limit]
+context = 512_000
+output = 128_000
+
+[modalities]
+input = ["text", "image", "video"]
+output = ["text"]

models/mistral/codestral-latest.toml

@@ -0,0 +1,29 @@
+name = "Codestral (latest)"
+family = "codestral"
+release_date = "2024-05-29"
+last_updated = "2025-01-04"
+attachment = false
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2024-10"
+open_weights = true
+
+[limit]
+context = 256_000
+output = 4_096
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/mistralai/Codestral-22B-v0.1"
+
+[[benchmarks]]
+name = "Aider Polyglot"
+score = 11.1
+metric = "percent correct"
+source = "https://aider.chat/docs/leaderboards/"
+date = "2025-01-13"

models/mistral/devstral-2512.toml

@@ -0,0 +1,43 @@
+name = "Devstral 2"
+family = "devstral"
+release_date = "2025-12-09"
+last_updated = "2025-12-09"
+attachment = false
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2025-12"
+open_weights = true
+
+[limit]
+context = 262_144
+output = 262_144
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/mistralai/Devstral-2-123B-Instruct-2512"
+
+[[benchmarks]]
+name = "Artificial Analysis Coding Index"
+score = 23.7
+metric = "index"
+source = "https://openrouter.ai/mistralai/devstral-2512/benchmarks"
+date = "2026-05-31"
+
+[[benchmarks]]
+name = "SciCode"
+score = 33.1
+metric = "percent correct"
+source = "https://openrouter.ai/mistralai/devstral-2512/benchmarks"
+date = "2026-05-31"
+
+[[benchmarks]]
+name = "Terminal-Bench Hard"
+score = 18.9
+metric = "success rate"
+source = "https://openrouter.ai/mistralai/devstral-2512/benchmarks"
+date = "2026-05-31"

models/mistral/devstral-medium-2507.toml

@@ -5,19 +5,21 @@ last_updated = "2025-07-10"
 attachment = false
 reasoning = false
 temperature = true
-knowledge = "2025-05"
 tool_call = true
-structured_output = true
-open_weights = true
-
-[cost]
-input = 0.40
-output = 2.00
+knowledge = "2025-05"
+open_weights = false
 
 [limit]
-context = 131_072 
-output = 131_072
+context = 128_000
+output = 128_000
 
 [modalities]
 input = ["text"]
-output = ["text"]
+output = ["text"]
+
+[[benchmarks]]
+name = "SWE-Bench Verified"
+score = 61.6
+metric = "resolved"
+source = "https://mistral.ai/news/devstral-2507"
+date = "2025-07-10"

models/mistral/devstral-medium-latest.toml

@@ -0,0 +1,22 @@
+name = "Devstral 2 (latest)"
+family = "devstral"
+release_date = "2025-12-02"
+last_updated = "2025-12-02"
+attachment = false
+reasoning = false
+temperature = true
+tool_call = true
+knowledge = "2025-12"
+open_weights = true
+
+[limit]
+context = 262_144
+output = 262_144
+
+[modalities]
+input = ["text"]
+output = ["text"]
+
+[[weights]]
+label = "Hugging Face"
+url = "https://huggingface.co/mistralai/Devstral-2-123B-Instruct-2512"