fix: adjust GLM-4.6-turbo max output tokens to 40k

Fixes issue where GLM-4.6-turbo was requesting the entire context window
(202752 tokens) for output, leaving no room for input tokens. Now set to
40960 tokens (20% of 200k context) to allow sufficient input space.

Fixes #8821

Author: roomote

packages/types/src/providers/chutes.ts

@@ -88,7 +88,8 @@ export const chutesModels = {
 		supportsPromptCache: false,
 		inputPrice: 0.23,
 		outputPrice: 0.9,
-		description: "DeepSeek‑V3.1‑Terminus is an update to V3.1 that improves language consistency by reducing CN/EN mix‑ups and eliminating random characters, while strengthening agent capabilities with notably better Code Agent and Search Agent performance.",
+		description:
+			"DeepSeek‑V3.1‑Terminus is an update to V3.1 that improves language consistency by reducing CN/EN mix‑ups and eliminating random characters, while strengthening agent capabilities with notably better Code Agent and Search Agent performance.",
 	},
 	"deepseek-ai/DeepSeek-V3.1-turbo": {
 		maxTokens: 32768,
@@ -97,7 +98,8 @@ export const chutesModels = {
 		supportsPromptCache: false,
 		inputPrice: 1.0,
 		outputPrice: 3.0,
-		description: "DeepSeek-V3.1-turbo is an FP8, speculative-decoding turbo variant optimized for ultra-fast single-shot queries (~200 TPS), with outputs close to the originals and solid function calling/reasoning/structured output, priced at $1/M input and $3/M output tokens, using 2× quota per request and not intended for bulk workloads.",
+		description:
+			"DeepSeek-V3.1-turbo is an FP8, speculative-decoding turbo variant optimized for ultra-fast single-shot queries (~200 TPS), with outputs close to the originals and solid function calling/reasoning/structured output, priced at $1/M input and $3/M output tokens, using 2× quota per request and not intended for bulk workloads.",
 	},
 	"deepseek-ai/DeepSeek-V3.2-Exp": {
 		maxTokens: 163840,
@@ -106,7 +108,8 @@ export const chutesModels = {
 		supportsPromptCache: false,
 		inputPrice: 0.25,
 		outputPrice: 0.35,
-		description: "DeepSeek-V3.2-Exp is an experimental LLM that introduces DeepSeek Sparse Attention to improve long‑context training and inference efficiency while maintaining performance comparable to V3.1‑Terminus.",
+		description:
+			"DeepSeek-V3.2-Exp is an experimental LLM that introduces DeepSeek Sparse Attention to improve long‑context training and inference efficiency while maintaining performance comparable to V3.1‑Terminus.",
 	},
 	"unsloth/Llama-3.3-70B-Instruct": {
 		maxTokens: 32768, // From Groq
@@ -328,7 +331,7 @@ export const chutesModels = {
 			"GLM-4.6 introduces major upgrades over GLM-4.5, including a longer 200K-token context window for complex tasks, stronger coding performance in benchmarks and real-world tools (such as Claude Code, Cline, Roo Code, and Kilo Code), improved reasoning with tool use during inference, more capable and efficient agent integration, and refined writing that better matches human style, readability, and natural role-play scenarios.",
 	},
 	"zai-org/GLM-4.6-turbo": {
-		maxTokens: 202752, // From Chutes /v1/models: max_output_length
+		maxTokens: 40960, // 20% of 200K context window to leave room for input
 		contextWindow: 202752,
 		supportsImages: false,
 		supportsPromptCache: false,
@@ -397,8 +400,9 @@ export const chutesModels = {
 		contextWindow: 262144,
 		supportsImages: true,
 		supportsPromptCache: false,
-		inputPrice: 0.1600,
-		outputPrice: 0.6500,
-		description: "Qwen3‑VL‑235B‑A22B‑Thinking is an open‑weight MoE vision‑language model (235B total, ~22B activated) optimized for deliberate multi‑step reasoning with strong text‑image‑video understanding and long‑context capabilities.",
+		inputPrice: 0.16,
+		outputPrice: 0.65,
+		description:
+			"Qwen3‑VL‑235B‑A22B‑Thinking is an open‑weight MoE vision‑language model (235B total, ~22B activated) optimized for deliberate multi‑step reasoning with strong text‑image‑video understanding and long‑context capabilities.",
 	},
 } as const satisfies Record<string, ModelInfo>