Codestral 2508 vs GPT-5

Across our 12-test suite, GPT-5 wins 8 tests, Codestral 2508 wins 0, and they tie on 4. Tie wins (both score 5): structured_output (5 vs 5; both tied for 1st in structured_output), tool_calling (5 vs 5; both tied for 1st), faithfulness (5 vs 5; both tied for 1st) and long_context (5 vs 5; both tied for 1st). GPT-5 wins: strategic_analysis 5 vs 2 (GPT-5 is tied for 1st in strategic_analysis), creative_problem_solving 4 vs 2 (GPT-5 ranks 9 of 54), constrained_rewriting 4 vs 3 (GPT-5 rank 6 of 53), classification 4 vs 3 (GPT-5 tied for 1st), safety_calibration 2 vs 1 (GPT-5 ranks 12 of 55 vs Codestral rank 32), persona_consistency 5 vs 3 (GPT-5 tied for 1st; Codestral rank 45), agentic_planning 5 vs 4 (GPT-5 tied for 1st; Codestral rank 16), and multilingual 5 vs 4 (GPT-5 tied for 1st; Codestral rank 36). Rankings show GPT-5 holding top positions across strategic, agentic, persona, classification and multilingual axes, while Codestral ties at the top for format fidelity, tool selection and long-context retrieval. On external third-party benchmarks (Epoch AI) GPT-5 scores: SWE-bench Verified 73.6% (rank 6 of 12), Math Level 5 98.1% (rank 1 of 14), AIME 2025 91.4% (rank 6 of 23) — all cited from Epoch AI. Codestral has no external scores in the payload. In practical terms: pick GPT-5 when you need superior reasoning, classification, creative problem solving or math; pick Codestral when you need the same JSON/format fidelity, tool-calling accuracy, and long-context behavior at a far lower price.

Prices (per 1k tokens / mTok): Codestral 2508 input $0.30, output $0.90; GPT-5 input $1.25, output $10.00. Per 1M tokens: input-only = Codestral $300, GPT-5 $1,250; output-only = Codestral $900, GPT-5 $10,000. For a 50/50 input/output split per 1M tokens the cost is ~Codestral $600 vs GPT-5 $5,625. Multiply by volume: 10M → Codestral ~$6,000 vs GPT-5 ~$56,250; 100M → Codestral ~$60,000 vs GPT-5 ~$562,500. The gap matters for high-volume services, consumer apps, or CI-style code generation: at 10M–100M tokens/month, Codestral reduces bill by roughly an order of magnitude. Teams focused on absolute top-tier reasoning, multilingual accuracy, or math-heavy features should budget for GPT-5; teams optimizing cost-per-request for code completion, test generation, or FIM should prioritize Codestral 2508.

Choose Codestral 2508 if: you need cost-efficient, low-latency code workflows (FIM, code correction, test generation), high-format compliance and long-context retrieval, or you operate at tens of millions of tokens/month and want ~10x lower bills (Codestral output $0.9/mTok vs GPT-5 $10/mTok). Choose GPT-5 if: you require top results on strategic analysis, agentic planning, persona consistency, creative problem solving, classification and math-heavy tasks (GPT-5 wins 8/12 tests and posts 98.1% on Math Level 5 per Epoch AI).