Compare gemini-3.1-flash-lite-nothink from Google and GLM 5.2 from Z.AI on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.
gemini-3.1-flash-lite-nothink
GLM 5.2gemini-3.1-flash-lite is currently Google's latest and most cost-effective model, optimized for large-scale agent-based tasks, translation, and simple data processing.
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.
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.
gemini-3.1-flash-lite-nothink: $1.50/M output tokens; GLM 5.2: $3.94/M. Use the cost calculator above to estimate your own workload.
gemini-3.1-flash-lite-nothink: 0.6s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.
gemini-3.1-flash-lite-nothink accepts 1,000,000 and GLM 5.2 accepts 1,000,000 input tokens. Maximum output per request is 64,000 tokens on gemini-3.1-flash-lite-nothink and 128,000 tokens on GLM 5.2.
gemini-3.1-flash-lite-nothink at 97.4 tok/s and GLM 5.2 at 34.6 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.
gemini-3.1-flash-lite-nothink accepts text, image, audio and video input and supports thinking, tool calling, function calling, structured outputs, web search, deep search and long context; GLM 5.2 accepts text input and supports thinking, tool calling, function calling and structured outputs.
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