Codestral 2508 vs GPT-5.4

Summary of our 12-test comparison (scores are from our testing): GPT-5.4 wins 7 tests, Codestral 2508 wins 1, and 4 are ties. Ties: structured_output (both 5) — both models rank tied for 1st on schema adherence; faithfulness (both 5) — both tied for 1st for sticking to source material; classification (both 3) — mid-tier (rank 31 of 53 for both); long_context (both 5) — both tied for 1st on >30K retrieval. Codestral wins tool_calling (5 vs 4): Codestral is tied for 1st in tool_calling among tested models while GPT-5.4 ranks 18th, so Codestral is clearly stronger at function selection, argument accuracy, and sequencing in our tests. GPT-5.4 wins strategic_analysis (5 vs 2): GPT-5.4 ranks tied for 1st on nuanced tradeoff reasoning while Codestral ranks 44th, indicating GPT-5.4 is far better for multi-step numeric tradeoffs. GPT-5.4 also wins constrained_rewriting (4 vs 3; rank 6 vs 31), creative_problem_solving (4 vs 2; rank 9 vs 47), safety_calibration (5 vs 1; tied for 1st vs rank 32), persona_consistency (5 vs 3; tied for 1st vs rank 45), agentic_planning (5 vs 4; tied for 1st vs rank 16), and multilingual (5 vs 4; tied for 1st vs rank 36). External benchmarks supplement this: GPT-5.4 scores 76.9% on SWE-bench Verified and 95.3% on AIME 2025 (Epoch AI), supporting its strength on coding benchmarks and math. In practice: pick GPT-5.4 for high-stakes reasoning, safety-sensitive applications, agentic workflows, and multilingual/personalized outputs; pick Codestral when you need top-tier tool calling, low-latency code-centric tasks, or orders-of-magnitude lower token costs.

Pricing per mTok (1k tokens) from the payload: Codestral 2508 = $0.30 input / $0.90 output; GPT-5.4 = $2.50 input / $15.00 output. Assuming a 50/50 split of input vs output tokens: 1M tokens = 1,000 mTok -> Codestral ≈ $600; GPT-5.4 ≈ $8,750. At 10M tokens: Codestral ≈ $6,000 vs GPT-5.4 ≈ $87,500. At 100M tokens: Codestral ≈ $60,000 vs GPT-5.4 ≈ $875,000. The payload’s priceRatio (0.06) shows Codestral is about 6% of GPT-5.4’s cost at list rates. Who should care: high-volume customers, startups, and any product where token costs dominate TCO will see meaningful savings with Codestral; teams that need top-tier safety, strategic reasoning, or multimodal/context capabilities may justify GPT-5.4’s much higher spend.

Choose Codestral 2508 if: you need best-in-class tool calling, FIM and code-correction workflows, large 256k context with lower operational cost, or you process high token volumes where cost dominates (savings ≈ 94% vs GPT-5.4 per the payload priceRatio). Choose GPT-5.4 if: you need top safety calibration, strategic analysis, agentic planning, better constrained rewriting and creative problem solving, or multimodal/very-large-context use cases supported by GPT-5.4’s 1M+ token window and strong external scores (SWE-bench 76.9%, AIME 95.3 per Epoch AI).