fix(vercel): factor free routes onto base models (#5077)

Co-authored-by: rekram1-node <rekram1-node@users.noreply.github.com>
This commit is contained in:
opencode-agent[bot]
2026-08-19 12:46:58 -05:00
committed by GitHub
parent d328ece240
commit 98de72cc24
4 changed files with 80 additions and 17 deletions
+25
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@@ -0,0 +1,25 @@
# Sources (accessed 2026-08-19):
# - https://z.ai/blog/glm-4.6v
# - https://huggingface.co/zai-org/GLM-4.6V-Flash
name = "GLM-4.6V-Flash"
description = "Lightweight GLM vision model for visual reasoning, documents, and multimodal agents"
family = "glm"
release_date = "2025-12-08"
last_updated = "2025-12-08"
attachment = true
reasoning = true
temperature = true
tool_call = true
open_weights = true
[limit]
context = 128_000
output = 32_768
[modalities]
input = ["text", "image", "video"]
output = ["text"]
[[weights]]
label = "Hugging Face"
url = "https://huggingface.co/zai-org/GLM-4.6V-Flash"
+15 -3
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@@ -70,13 +70,15 @@ export const vercel = {
},
translateModel(model, context) {
const existing = context.existing(model.id);
const baseModel = existing?.base_model ?? resolveCanonicalBaseModel(model.id);
const routeBase = freeRouteBase(model.id);
const baseModel = existing?.base_model ?? resolveVercelBaseModel(model.id);
const inherited = routeBase === undefined ? undefined : context.existing(routeBase);
return {
id: model.id,
model: buildVercelModel(
model,
existing,
baseModel === undefined || baseModel === model.id ? undefined : context.existing(baseModel),
inherited ?? (baseModel === undefined || baseModel === model.id ? undefined : context.existing(baseModel)),
),
};
},
@@ -178,7 +180,7 @@ export function buildVercelModel(
},
};
const baseModel = existing?.base_model ?? resolveCanonicalBaseModel(model.id);
const baseModel = existing?.base_model ?? resolveVercelBaseModel(model.id);
if (baseModel === undefined) return synced;
return factorBaseModel(baseModel, {
@@ -199,6 +201,16 @@ export function buildVercelModel(
}, synced.limit, existing?.base_model_omit);
}
function resolveVercelBaseModel(modelID: string) {
const routeBase = freeRouteBase(modelID);
return resolveCanonicalBaseModel(modelID)
?? (routeBase === undefined ? undefined : resolveCanonicalBaseModel(routeBase));
}
function freeRouteBase(modelID: string) {
return modelID.endsWith("-free") ? modelID.slice(0, -"-free".length) : undefined;
}
function dateFromTimestamp(timestamp: number) {
return new Date(timestamp * 1000).toISOString().slice(0, 10);
}
+38
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@@ -3541,6 +3541,44 @@ test("Vercel factored models inherit temperature from base metadata", () => {
expect(synced).not.toHaveProperty("temperature");
});
test("Vercel free routes factor onto the canonical non-free model", () => {
const [model] = vercel.parseModels({
data: [{
id: "zai/glm-4.6v-flash-free",
name: "GLM-4.6V-Flash (Free)",
created: 1_765_152_000,
released: 1_765_152_000,
context_window: 128_000,
max_tokens: 24_000,
type: "language",
tags: ["reasoning", "tool-use", "vision", "file-input"],
pricing: { input: "0", output: "0" },
}],
});
const translated = vercel.translateModel(model!, {
existing(id) {
return id === "zai/glm-4.6v-flash"
? { reasoning_options: [{ type: "toggle" }] }
: undefined;
},
authored() {
return undefined;
},
});
expect(translated?.model).toMatchObject({
base_model: "zhipuai/glm-4.6v-flash",
name: "GLM-4.6V-Flash (Free)",
reasoning_options: [{ type: "toggle" }],
cost: { input: 0, output: 0 },
limit: { output: 24_000 },
modalities: { input: ["text", "image", "pdf"] },
});
expect(translated?.model).not.toHaveProperty("description");
expect(translated?.model).not.toHaveProperty("family");
});
test("Vercel Claude Opus fast variants factor onto base opus metadata", () => {
const [model] = vercel.parseModels({
data: [{
@@ -1,20 +1,8 @@
name = "GLM-4.6V-Flash"
description = "GLM vision model for visual reasoning, documents, and multimodal agents"
family = "glm"
release_date = "2025-09-30"
last_updated = "2025-09-30"
attachment = true
reasoning = true
base_model = "zhipuai/glm-4.6v-flash"
reasoning_options = [{ type = "toggle" }]
temperature = true
tool_call = true
open_weights = false
knowledge = "2024-10"
[limit]
context = 128000
output = 24000
output = 24_000
[modalities]
input = ["text", "image", "pdf"]
output = ["text"]