GPT-5.1 vs Mistral Small 3.2 24B

Win/tie summary in our 12-test suite: GPT-5.1 wins 8 tests (strategic analysis 5 vs 2, creative problem solving 4 vs 2, faithfulness 5 vs 4, classification 4 vs 3, long context 5 vs 4, safety calibration 2 vs 1, persona consistency 5 vs 3, multilingual 5 vs 4). No tests were won solely by Mistral; four tests tied (structured output 4/4, constrained rewriting 4/4, tool calling 4/4, agentic planning 4/4). What this means in practice: - Faithfulness (A:5, B:4): GPT-5.1 is tied for 1st in our rankings (tied with 32 others out of 55), indicating stronger adherence to source material and fewer hallucinations in our testing than Mistral (rank 34/55). - Long context (A:5, B:4): GPT-5.1 is tied for 1st (36 others) and will be better for retrieval or summarization at 30K+ tokens; Mistral ranks 38/55, so expect weaker long-context handling. - Coding/math: GPT-5.1 posts 68% on SWE-bench Verified and 88.6% on AIME 2025 (Epoch AI) — we report those external scores as supplementary evidence (Epoch AI). Mistral has no external SWE or AIME scores in the payload. GPT-5.1’s swebench rank is 7/12 and AIME rank is 7/23 in our collected rankings. - Strategic analysis & creative problem solving (A leads by large margins): GPT-5.1 (5 and 4) gives more nuanced tradeoffs and non‑obvious feasible ideas than Mistral (2 and 2), which matters for product strategy, proposals, or multi-step reasoning. - Tool calling and constrained formats are tied (4/4): both models perform similarly on function selection/argument accuracy and strict format adherence in our tests. - Safety calibration (A:2 vs B:1): both score low by absolute standards, but GPT-5.1 performed better in our safety refusals and allowances (A ranks 12/55 vs B 32/55). Overall, GPT-5.1 delivers higher raw capability across core reasoning, long context, and math/coding benchmarks; Mistral matches in structured tasks and offers a much lower cost for scale.

Prices (per 1,000 tokens): GPT-5.1 input $1.25, output $10.00; Mistral Small 3.2 input $0.075, output $0.20. Price ratio is ~50×. Using a 50/50 input/output token split as an example: - 1M tokens (1,000 mTok; 500 input / 500 output): GPT-5.1 = $625 + $5,000 = $5,625/month; Mistral = $37.50 + $100 = $137.50/month. - 10M tokens: GPT-5.1 = $56,250/month; Mistral = $1,375/month. - 100M tokens: GPT-5.1 = $562,500/month; Mistral = $13,750/month. Who should care: startups or products under ~1M tokens/month may tolerate GPT-5.1 for premium capabilities; any service with tens of millions of tokens/month should evaluate Mistral for dramatic cost savings unless GPT-5.1’s higher accuracy or long-context abilities are business-critical.

Choose GPT-5.1 if you need top-tier faithfulness, long-context retrieval (30K+ tokens), multilingual output, stronger math/coding performance (68% SWE-bench Verified; 88.6% AIME 2025 per Epoch AI), or superior strategic/creative reasoning — and your budget can absorb ~$5.6K+/month at 1M tokens (50/50 split). Choose Mistral Small 3.2 24B if you must minimize runtime cost for high-volume usage, rely on structured outputs, constrained rewriting, or tool calling (ties vs GPT-5.1), and can accept lower scores on long-context and creative/strategic tasks — it costs roughly $137.50/month at 1M tokens (50/50 split).