Bai Qwen3 VL 235B A22B Instruct vs GLM 5.2

Output tokens cost $1.10 per million on Bai Qwen3 VL 235B A22B Instruct and $3.94 per million on GLM 5.2. Input tokens cost $0.27 per million on Bai Qwen3 VL 235B A22B Instruct and $1.13 per million on GLM 5.2. Cached input tokens are billed at $0.27 per million on Bai Qwen3 VL 235B A22B Instruct and $0.28 per million on GLM 5.2. Context lengths are 131,000 tokens on Bai Qwen3 VL 235B A22B Instruct and 1,000,000 tokens on GLM 5.2. Time to first token (TTFT) measured on AIHubMix is 1.1s on Bai Qwen3 VL 235B A22B Instruct and 0.6s on GLM 5.2. Measured output throughput is 41.7 tok/s on Bai Qwen3 VL 235B A22B Instruct and 45.3 tok/s on GLM 5.2. On the LMArena coding leaderboard Bai Qwen3 VL 235B A22B Instruct scores 1466 and GLM 5.2 scores 1505.

Bai Qwen3 VL 235B A22B Instruct✕GLM 5.2✕

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Bai Qwen3 VL 235B A22B Instruct

Qwen · → text

The Qwen3 series open-source models include hybrid models, thinking models, and non-thinking models, with both reasoning capabilities and general abilities reaching industry SOTA levels at the same scale.

Input$0.27 /M

Output$1.10 /M

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GLM 5.2

Z.AI · text → text

GLM-5.2 is Z.ai’s flagship model for the era of long-horizon tasks. With a truly usable 1M-token context window, it can handle project-level engineering context, execute long-running tasks more reliably, follow engineering standards more consistently, and complete the full development workflow from requirements to multi-platform deployment in a single task.

Input$1.13 /M

Output$3.94 /M

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