GPT-5.1 vs Mistral Small 3.1 24B

Summary of head-to-head results in our 12-test suite: GPT-5.1 wins 10 tests, Mistral wins none, and the two tie on 2. Ties: structured output (both score 4; rank 26 of 54) and long context (both score 5; tied for 1st). GPT-5.1 wins strategic analysis (5 vs 3) and is tied for 1st on that metric in our rankings; this matters when you need nuanced trade-off reasoning. Constrained_rewriting (4 vs 3) shows GPT-5.1 handles strict character/format limits better (A rank 6 vs B rank 31). Creative_problem_solving (4 vs 2; A rank 9 vs B rank 47) indicates GPT-5.1 yields more novel, feasible ideas. Tool_calling is a major differentiator: GPT-5.1 scores 4 (rank 18 of 54) while Mistral scores 1 (rank 53 of 54) and has a documented quirk 'no_tool calling' — so GPT-5.1 is far better for function selection and argument sequencing. Faithfulness (5 vs 4; A tied for 1st, B rank 34) and classification (4 vs 3; A tied for 1st, B rank 31) show GPT-5.1 produces more accurate, less hallucinatory answers and routing. Safety_calibration (2 vs 1; A rank 12 vs B rank 32) and persona consistency (5 vs 2; A tied for 1st vs B rank 51) favor GPT-5.1 when refusal behavior and character persistence matter. Agentic_planning (4 vs 3) again supports GPT-5.1 for goal decomposition. Multilingual is 5 vs 4 in favor of GPT-5.1 (A tied for 1st, B rank 36). External benchmarks (supplementary): GPT-5.1 scores 68% on SWE-bench Verified (Epoch AI) and 88.6% on AIME 2025 (Epoch AI), ranking 7th on both respective lists; Mistral has no external scores in the payload. Practical meaning: GPT-5.1 is the stronger generalist for coding/math/reasoning-heavy, multi-turn agent and safety-sensitive applications; Mistral is a lower-cost alternative that still offers top-tier long-context performance but lacks reliable tool calling and trails on many reasoning and safety axes.

Prices from the payload: GPT-5.1 input $1.25/mTok and output $10/mTok; Mistral Small 3.1 24B input $0.35/mTok and output $0.56/mTok. Assuming a 50/50 input/output token split, monthly costs are: for 1M tokens — GPT-5.1 $5,625 vs Mistral $455; for 10M tokens — GPT-5.1 $56,250 vs Mistral $4,550; for 100M tokens — GPT-5.1 $562,500 vs Mistral $45,500. The payload also reports a price ratio of ~17.86x. Who should care: startups, high-volume APIs, and edge deployments will see materially different op-ex; enterprises with mission-critical reasoning, tool-enabled agents, or very large context needs may accept GPT-5.1’s higher cost; cost-sensitive products and high-throughput inference pipelines should prefer Mistral for price efficiency.

Choose GPT-5.1 if you need best-in-class reasoning, faithfulness, tool-enabled agents, multilingual production quality, or the largest 400k-token context (examples: developer-facing coding assistants relying on tool calls, regulated customer support, complex financial/legal analysis, or multimodal apps ingesting files). Choose Mistral Small 3.1 24B if you must minimize inference cost at scale, need competitive long-context image->text pipelines, or run high-throughput text workloads without tool calling — example use cases: bulk document ingestion, cheap summarization, low-cost chatbots and prototyping.