Compare GLM 5.2 from Z.AI and Kimi K2.7 Code Highspeed from Moonshot AI 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
Kimi K2.7 Code HighspeedGLM-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.
High-Speed version of Kimi K2.7 Code model, with output speed of approximately 180 Tokens/s and up to 260 Tokens/s in short context scenarios, delivering a more extreme coding experience.
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.
GLM 5.2: $3.94/M output tokens; Kimi K2.7 Code Highspeed: $8.00/M. Use the cost calculator above to estimate your own workload.
GLM 5.2: 1.1s 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 Kimi K2.7 Code Highspeed accepts 262,144 input tokens. Maximum output per request is 128,000 tokens on GLM 5.2 and 32,768 tokens on Kimi K2.7 Code Highspeed.
Kimi K2.7 Code Highspeed at 55.0 tok/s and GLM 5.2 at 33.7 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; Kimi K2.7 Code Highspeed accepts text, image and video input and supports thinking, function calling and structured outputs.
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