Codestral 2508 vs Mistral Small 3.2 24B

Across our 12-test suite, Codestral 2508 wins 4 tests, Mistral Small 3.2 24B wins 1, and 7 tests tie. Detailed head-to-head (scores shown are from our testing):

• Structured output: Codestral 2508 5 vs Mistral Small 3.2 24B 4. Codestral ties for 1st on structured_output in our rankings (tied for 1st with 24 others out of 54), so expect better JSON/schema compliance and fewer format errors when schema fidelity matters.
• Tool calling: Codestral 2508 5 vs Mistral Small 3.2 24B 4. Codestral is tied for 1st on tool_calling (tied with 16 others out of 54), meaning more accurate function selection and argument sequencing in our tests.
• Faithfulness: Codestral 2508 5 vs Mistral Small 3.2 24B 4. Codestral is tied for 1st in faithfulness (tied with 32 others out of 55), so it sticks to source material more reliably in our benchmarks.
• Long context: Codestral 2508 5 vs Mistral Small 3.2 24B 4. Codestral ties for 1st on long_context (tied with 36 others of 55), indicating stronger retrieval and accuracy at 30K+ token ranges in our tests.
• Constrained rewriting: Codestral 2508 3 vs Mistral Small 3.2 24B 4. Mistral Small ranks 6 of 53 on constrained_rewriting (our tests), so it handles aggressive compression/character limits better.

The remaining tests are ties: strategic_analysis (2/2), creative_problem_solving (2/2), classification (3/3), safety_calibration (1/1), persona_consistency (3/3), agentic_planning (4/4), multilingual (4/4). Where scores tie, both models perform similarly in our suite (e.g., both score 4/5 on multilingual and 4/5 on agentic_planning).

Practical implications: pick Codestral 2508 when your workflow needs strict output format, reliable function calls, long-context retrieval, or fidelity to source code/text. Pick Mistral Small 3.2 24B when you need to compress text into tight limits (constrained rewriting) or when price per token is the priority.

Pricing per 1,000 tokens (mTok): Codestral 2508 charges $0.30 input / $0.90 output; Mistral Small 3.2 24B charges $0.075 input / $0.20 output. Assuming a 50/50 split of input/output tokens, monthly costs for total tokens are: 1M tokens → Codestral $600 vs Mistral Small $137.50; 10M → Codestral $6,000 vs Mistral Small $1,375; 100M → Codestral $60,000 vs Mistral Small $13,750. The ~4.5× price gap (priceRatio 4.5) matters when you scale: teams generating millions of tokens monthly (chat platforms, large-scale code generation, analytics) will save tens of thousands by choosing Mistral Small 3.2 24B. Choose Codestral 2508 only when the quality differences on structured output, tool calling, or long-context fidelity measurably reduce downstream costs (debugging, failed function calls, rework).

Choose Codestral 2508 if you prioritize: precise structured output (5/5), accurate tool calling (5/5), faithfulness (5/5), or long-context retrieval (5/5) in developer/coding workflows and can justify higher monthly spend. Choose Mistral Small 3.2 24B if you prioritize: lower cost ($0.075/$0.20 in/out), better constrained rewriting (4/5), or broad instruction-following and multimodal input (payload shows text+image→text modality) at scale—the cheaper model saves material amounts once you exceed millions of tokens per month.