Compare Gemma 4 31B It 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.
Gemma 4 31B It
GLM 5.2Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function calling, and multilingual support across 140+ languages. Strong on coding, reasoning, and document understanding tasks. Apache 2.0 license.
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.
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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.
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Gemma 4 31B It: $0.4/M output tokens; GLM 5.2: $2.524/M. Use the cost calculator above to estimate your own workload.
Gemma 4 31B It: 0.2s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.
Gemma 4 31B It accepts 262,100 and GLM 5.2 accepts 1,000,000 input tokens. Maximum output per request is 131,100 tokens on Gemma 4 31B It and 128,000 tokens on GLM 5.2.
Gemma 4 31B It at 209.1 tok/s and GLM 5.2 at 35.9 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.
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