GPT-4.1 vs Mistral Large 3 2512

Test-by-test summary (our 12-test suite comparisons):

• Tool calling: GPT-4.1 5 vs Mistral 4 — GPT-4.1 wins and ranks tied for 1st of 54 (tied with 16 others). This matters for reliable function selection, argument accuracy and sequencing.
• Long-context: GPT-4.1 5 vs Mistral 4 — GPT-4.1 wins and is tied for 1st of 55 (tied with 36 others), improving retrieval and coherence past 30k tokens.
• Persona consistency: GPT-4.1 5 vs Mistral 3 — GPT-4.1 wins and is tied for 1st of 53 (tied with 36 other models), so it better maintains character and resists injection.
• Classification: GPT-4.1 4 vs Mistral 3 — GPT-4.1 wins and is tied for 1st of 53 (tied with 29 others), giving more accurate routing and tagging.
• Strategic analysis: GPT-4.1 5 vs Mistral 4 — GPT-4.1 wins and is tied for 1st of 54 (tied with 25 others), useful for nuanced tradeoff reasoning with numbers.
• Constrained rewriting: GPT-4.1 5 vs Mistral 3 — GPT-4.1 wins and is tied for 1st of 53 (tied with 4 others), important when compressing to hard character limits.
• Structured output: GPT-4.1 4 vs Mistral 5 — Mistral wins and is tied for 1st of 54 (tied with 24 others); choose Mistral when strict JSON/schema compliance is essential.
• Creative problem solving: tie (both 3) — both rank 30 of 54 (17 models share the score); expect similar performance on generating non-obvious feasible ideas.
• Faithfulness: tie (both 5) — both tied for 1st of 55 (tied with 32 others); both stick to source material in our tests.
• Safety calibration: tie (both 1) — both rank 32 of 55; neither excels at calibrated refusals in our suite.
• Agentic planning: tie (both 4) — both rank 16 of 54; comparable goal decomposition and failure recovery.
• Multilingual: tie (both 5) — both tied for 1st of 55 (tied with 34 others); both deliver equivalent non-English quality in our tests. External benchmarks (Epoch AI): GPT-4.1 scores 48.5% on SWE-bench Verified, 83% on MATH Level 5, and 38.3% on AIME 2025 — we report these as supplementary evidence for code and math abilities (attributed to Epoch AI). Mistral Large 3 2512 has no external scores in the payload. Overall, GPT-4.1 wins 6 metrics, Mistral wins 1, and 5 are ties — that distribution defines the verdict above.

Per the payload, GPT-4.1 costs $2.00 per 1k input tokens and $8.00 per 1k output tokens; Mistral Large 3 2512 costs $0.50 per 1k input and $1.50 per 1k output. If you bill monthly for 1M input + 1M output tokens (1,000 mTok each): GPT-4.1 = $2,000 (input) + $8,000 (output) = $10,000; Mistral = $500 + $1,500 = $2,000. At 10M in/out tokens: GPT-4.1 = $100,000 vs Mistral = $20,000. At 100M in/out tokens: GPT-4.1 = $1,000,000 vs Mistral = $200,000. The dominant driver is output cost (GPT-4.1 output $8 vs Mistral $1.5 per 1k tokens; output cost ratio = 8/1.5 = 5.33, matching the payload priceRatio). Enterprises with high-volume generation (chatbots, summarization, large-scale APIs) should care most about this gap; teams prioritizing top-ranked tool calling, long-context, and persona consistency may justify GPT-4.1’s higher spend.

Choose GPT-4.1 if you need best-in-class tool calling, long-context coherence, persona consistency, classification, strategic analysis, or constrained rewriting for production apps and you can absorb higher per-token costs. Choose Mistral Large 3 2512 if strict structured output (JSON/schema compliance) and lower operating cost are your priorities — it delivers the top structured output score while reducing token spend by roughly 4–5× in combined billing scenarios.