Codestral 2508
Mistral's efficiency model. Context window: 256K tokens.
Scores by test
Methodology →What you need to know
Codestral 2508 is optimized for high-precision execution and long-context retrieval rather than cognitive reasoning. It achieves perfect scores in faithfulness, structured output, and tool calling, making it a reliable engine for programmatic tasks where strict adherence to a schema or a large codebase is required. Its 256K context window is fully leveraged, as evidenced by its top-tier long-context performance.
The model struggles significantly with high-level cognition. With low scores in strategic analysis and creative problem solving, it cannot be relied upon for architectural design or complex logic puzzles. Additionally, a critical failure in safety calibration indicates a lack of robust guardrails, which may be a risk for public-facing deployments.
At a blended cost of $0.750/MTok, the model is priced as a mid-tier utility. While it lacks the general intelligence of top-ranked models—ranking 61st out of 71 overall—the price is justified for developers who need a dependable tool for data extraction and API orchestration rather than a reasoning agent.
Use this model if you need a reliable tool for structured data generation, long-document analysis, or agentic tool calling. Skip this model if your application requires nuanced strategic reasoning, creative synthesis, or strict safety filtering.
Strengths — Top 3
Relative weaknesses — Bottom 3
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