GPT-4o vs Mistral Large 3 2512

Overview — our 12-test suite results: Mistral Large 3 2512 wins 4 tests, GPT-4o wins 2, and 6 are ties. Detailed walk-through: 1) Structured output (JSON/schema compliance): Mistral 5 vs GPT-4o 4 — Mistral is top-tier here (tied for 1st of 54 models with 24 others), so prefer it when exact format adherence matters. 2) Strategic analysis (numeric tradeoffs): Mistral 4 vs GPT-4o 2 — Mistral’s 4 indicates noticeably better nuanced tradeoff reasoning in our tests (rank 27 of 54 vs GPT-4o rank 44). 3) Faithfulness (avoiding hallucination): Mistral 5 vs GPT-4o 4 — Mistral ties for 1st of 55 models (32 others share the top score), so it’s safer for source-accurate tasks. 4) Multilingual: Mistral 5 vs GPT-4o 4 — Mistral ties for 1st of 55 models (34 others share), making it stronger for non-English production. 5) Classification: GPT-4o 4 vs Mistral 3 — GPT-4o ties for 1st with many models on classification in our dataset (tied for 1st with 29 others out of 53), so routing/labeling tasks often favor GPT-4o. 6) Persona consistency: GPT-4o 5 vs Mistral 3 — GPT-4o ties for 1st (with 36 others), so it better preserves roles/characters in chat. Ties: constrained rewriting 3/3, creative problem solving 3/3, tool calling 4/4 (both rank 18 of 54), long context 4/4 (both rank 38 of 55), safety calibration 1/1, and agentic planning 4/4. Context windows (payload): GPT-4o = 128,000 tokens; Mistral Large 3 2512 = 262,144 tokens — both support very long contexts, and both scored identically on our long context test. External benchmarks (supplementary): GPT-4o shows 31% on SWE-bench Verified, 53.3% on MATH Level 5, and 6.4% on AIME 2025 (scores per Epoch AI); Mistral Large 3 2512 has no external percentages in this payload. In short: Mistral leads on structured output, strategic analysis, faithfulness, and multilingual work; GPT-4o leads on classification and persona consistency; many other capabilities are tied.

Raw pricing (per 1k tokens): GPT-4o input $2.50, output $10.00; Mistral Large 3 2512 input $0.50, output $1.50. Output-only cost at common volumes: 1M output tokens = GPT-4o $10,000 vs Mistral $1,500; 10M = $100,000 vs $15,000; 100M = $1,000,000 vs $150,000. If you assume a 1:1 input:output token ratio, combined costs per 1M output tokens become $12,500 (GPT-4o) vs $2,000 (Mistral), and scale to $125,000 vs $20,000 at 10M. The 6.67× priceRatio in the payload means high-volume products, LLM-hosting providers, and cost-sensitive teams should prefer Mistral for throughput; teams prioritizing GPT-4o’s classification/persona behavior and multimodal/file support should budget for materially higher spend.

Choose Mistral Large 3 2512 if you need: - Accurate JSON/schema outputs and strict format adherence (structured output 5; tied for 1st). - Strong multilingual and faithfulness performance (multilingual 5; faithfulness 5) at low cost (output $1.50/1k). - High-volume deployments where cost per token matters. Choose GPT-4o if you need: - Better classification and persona consistency (classification 4; persona consistency 5 in our tests). - File-to-text modality in addition to text+image (payload shows GPT-4o supports text+image+file->text). - A willingness to pay ~6.7× more per output token for those behavioral strengths.