Codestral 2508 vs o4 Mini

Summary of our 12-test comparison (scores are from our testing):

• Tests o4 Mini wins: strategic_analysis (o4 Mini 5 vs Codestral 2; o4 Mini is "tied for 1st with 25 other models out of 54 tested" on strategic_analysis), creative_problem_solving (4 vs 2; o4 Mini ranks 9 of 54), classification (4 vs 3; o4 Mini tied for 1st with 29 others), persona_consistency (5 vs 3; o4 Mini tied for 1st with 36 others), multilingual (5 vs 4; o4 Mini tied for 1st with 34 others). These wins indicate o4 Mini is stronger at nuanced tradeoff reasoning, non-obvious idea generation, routing/categorization, maintaining persona, and non-English parity in our tests.
• Ties where both models match: structured_output (5/5; both "tied for 1st with 24 other models" — strong schema/JSON compliance), constrained_rewriting (3/3), tool_calling (5/5; both "tied for 1st with 16 other models" — accurate function selection and sequencing), faithfulness (5/5; both tied for 1st with 32 others), long_context (5/5; both tied for 1st with 36 others), safety_calibration (1/1), agentic_planning (4/4). For practical tasks this means both models are equally reliable on large-context retrieval, structured outputs and calling tools in our benchmarks.
• Tests Codestral does not uniquely win in our suite (no A-only wins). However, Codestral matches o4 Mini on mission-critical engineering signals (tool_calling 5, structured_output 5, faithfulness 5, long_context 5) which supports coding and high-context engineering workflows in our testing.
• External benchmarks (supplementary): o4 Mini scores 97.8% on MATH Level 5 and 81.7% on AIME 2025 (Epoch AI), which supports the model’s strong quantitative/reasoning performance in third-party tests. Overall: o4 Mini takes the lead on reasoning, creativity and multilingual categories; Codestral equals o4 Mini on structured outputs, tool calling, faithfulness and long-context retrieval in our testing, at a fraction of the price.

Per 1,000 tokens (mtok) Codestral 2508 charges $0.30 input / $0.90 output; o4 Mini charges $1.10 input / $4.40 output. Illustrative monthly costs: if you use 1M tokens (1,000 mtok) with a 50/50 input-output split, Codestral ≈ $600/month (500 mtok input = $150 + 500 mtok output = $450) while o4 Mini ≈ $2,750/month (500 mtok input = $550 + 500 mtok output = $2,200). At 10M tokens those totals scale to ~ $6,000 vs $27,500; at 100M tokens to ~ $60,000 vs $275,000. The gap matters most to high-volume apps (SaaS products, large-scale ingestion or batch code generation). Low-volume or accuracy-critical workflows may justify o4 Mini’s higher spend; cost-sensitive, high-throughput coding pipelines should favor Codestral 2508.

Choose Codestral 2508 if: you run high-volume, cost-sensitive coding pipelines (fill-in-the-middle, code correction, test generation per the model description), need low-latency, strong tool-calling, schema compliance and long-context handling, and want the lowest per-token spend ($0.30 input / $0.90 output per 1k). Choose o4 Mini if: you need stronger strategic analysis, creative problem solving, classification/routing, persona consistency and multilingual performance (o4 Mini wins 5 of 12 internal tests and posts 97.8% on MATH Level 5 and 81.7% on AIME 2025 according to Epoch AI), and you can absorb the higher cost ($1.10 input / $4.40 output per 1k).