Gemma 4 31B
Google's mid-tier model. Context window: 262K tokens.
Scores by test
Methodology →What you need to know
Gemma 4 31B is optimized for high-precision technical tasks, specifically excelling in tool calling, structured output, and strategic analysis. With perfect 5/5 internal scores across agentic planning and faithfulness, it is designed for reliability in complex workflows where hallucination must be minimized and strict adherence to schemas is required.
The model provides a high performance-to-cost ratio, ranking 18th out of 71 models while maintaining a low blended cost of $0.318 per million tokens. This makes it a cost-effective alternative for developers who need frontier-level capabilities in multilingual support and persona consistency without the premium pricing of larger proprietary models.
A significant trade-off is found in safety calibration, which scores a 2/5, indicating a potential lack of restrictive filtering or a higher tendency to bypass safety guardrails compared to other models in its class. While it handles a substantial 262K context window, its long-context performance is rated slightly lower than its core logical capabilities.
Use this model for agentic workflows, automated tool integration, and data-heavy strategic analysis. Skip this model if your application requires strict safety alignment or if your primary use case is highly creative, open-ended problem solving.
Strengths — Top 3
Relative weaknesses — Bottom 3
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