Compare GLM 5.2 from Z.AI and Qwen 3.8 27B from Qwen on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.
GLM 5.2
Qwen 3.8 27BGLM-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.
Qwen3.8-27b is an Alibaba-released dense vision-language model with open-source weights. Qwen3.8 was developed based on the architecture of Qwen3.5, achieving significant improvements in encoding capability, handling professional tasks, research tasks, and tasks that require long-term completion. Qwen3.8-27B integrates these advantages into a compact, easy-to-deploy dense model — a native vision-language model capable of understanding image and video information and featuring flexible cognitive control capabilities. This model can more reliably accomplish complex, multi-step tasks.
Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.
Promotional prices show the discounted rate; see each model page for promotion windows.
Daily traffic served through AIHubMix — how demand for each model is trending.
Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.
Estimate your monthly bill for the same workload on each model.
Monthly = daily × 30. Discounted rates applied where a promotion is active.
Qwen 3.8 27B: $1.65/M output tokens; GLM 5.2: $2.524/M. Use the cost calculator above to estimate your own workload.
Qwen 3.8 27B: 0.4s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.
GLM 5.2 accepts 1,000,000 and Qwen 3.8 27B accepts 131,072 input tokens.
Qwen 3.8 27B at 688.0 tok/s and GLM 5.2 at 36.1 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.
GLM 5.2 accepts text input and supports thinking, tool calling, function calling and structured outputs; Qwen 3.8 27B accepts text, image and video input.
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