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feat: add zai-org/GLM-4.5-turbo model to Chutes provider #8157

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feat: add zai-org/GLM-4.5-turbo model to Chutes provider #8157

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10 changes: 10 additions & 0 deletions packages/types/src/providers/chutes.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -29,6 +29,7 @@ export type ChutesModelId =
| "tngtech/DeepSeek-R1T-Chimera"
| "zai-org/GLM-4.5-Air"
| "zai-org/GLM-4.5-FP8"
| "zai-org/GLM-4.5-turbo"
| "moonshotai/Kimi-K2-Instruct-75k"
| "moonshotai/Kimi-K2-Instruct-0905"
| "Qwen/Qwen3-235B-A22B-Thinking-2507"
Expand Down Expand Up @@ -274,6 +275,15 @@ export const chutesModels = {
description:
"GLM-4.5-FP8 model with 128k token context window, optimized for agent-based applications with MoE architecture.",
},
"zai-org/GLM-4.5-turbo": {
maxTokens: 32768,
contextWindow: 131072,
supportsImages: false,
supportsPromptCache: false,
inputPrice: 1,
outputPrice: 3,
description: "GLM-4.5-turbo model with 128K token context window, optimized for fast inference.",
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The implementation correctly adds the GLM-4.5-turbo model with accurate metadata from the Chutes API. The pricing ( input, output per 1M tokens) and context window (131,072 tokens) match the specification provided by @mugnimaestra.

},
"Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8": {
maxTokens: 32768,
contextWindow: 262144,
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22 changes: 22 additions & 0 deletions src/api/providers/__tests__/chutes.spec.ts
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Expand Up @@ -253,6 +253,28 @@ describe("ChutesHandler", () => {
)
})

it("should return zai-org/GLM-4.5-turbo model with correct configuration", () => {
const testModelId: ChutesModelId = "zai-org/GLM-4.5-turbo"
const handlerWithModel = new ChutesHandler({
apiModelId: testModelId,
chutesApiKey: "test-chutes-api-key",
})
const model = handlerWithModel.getModel()
expect(model.id).toBe(testModelId)
expect(model.info).toEqual(
expect.objectContaining({
maxTokens: 32768,
contextWindow: 131072,
supportsImages: false,
supportsPromptCache: false,
inputPrice: 1,
outputPrice: 3,
description: "GLM-4.5-turbo model with 128K token context window, optimized for fast inference.",
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Good test coverage! The test properly verifies all the model configuration parameters including the default temperature (0.5) for non-DeepSeek models.

temperature: 0.5, // Default temperature for non-DeepSeek models
}),
)
})

it("should return Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8 model with correct configuration", () => {
const testModelId: ChutesModelId = "Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8"
const handlerWithModel = new ChutesHandler({
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