mistral-small-3.2-2506: benchmark scores, price and ranking

mistral-small-3.2-2506 from Mistral AI ranks #526 of 743 LLMs on the LLMs Tiger aggregate benchmark score (46.4), based on 3 benchmark results captured up to 2026-10-13.

Organisation: Mistral AI
Type: Open-weight / local model
Open weights: Yes
Released: 2025-06-20 (source: epoch)
Aggregate rank: #526 of 743 (score 46.4)

Relative to other models, mistral-small-3.2-2506 is strongest on OTIS Mock AIME (#121 of 189) and weakest on Chess Puzzles (#96 of 122).

Across the 3 benchmarks where at least ten models are scored, mistral-small-3.2-2506 is in the top 10% on 0 and in the top half on 0.

mistral-small-3.2-2506 benchmark results

mistral-small-3.2-2506 benchmark scores, ranked against all models measured on each benchmark
Benchmark	Score	Rank	Source	Captured
OTIS Mock AIME	30.3%	#121 of 189	Epoch AI Benchmarking Hub	2026-10-13
GPQA Diamond	49.1%	#189 of 275	Epoch AI Benchmarking Hub	2026-10-13
Chess Puzzles	1.0%	#96 of 122	Epoch AI Benchmarking Hub	2026-10-13

About mistral-small-3.2-2506

mistral-small-3.2-2506 is an open-weight model that can run on your own hardware from Mistral AI. It was released on 2025-06-20, according to Epoch AI. No API price is listed for it yet. We hold 3 benchmark results for it across 2 areas, and none is in the top tenth of its board.

Where mistral-small-3.2-2506 stands

On our aggregate score, mistral-small-3.2-2506 is #526 of 743 ranked models, in the lower half. Its score is 46.4; the scale is centred on 50, so it sits 3.6 points below the typical model. That beats 29% of the ranked field. Among the 44 ranked Mistral AI models it is #18. The next one up is ollama/mistral-small at 46.4. The next one down is mistral-small-2409 at 46.3.

mistral-small-3.2-2506, benchmark by benchmark

mistral-small-3.2-2506 lands below the middle on OTIS Mock AIME: 30.3%, #121 of 189, with 63% of the field scoring higher. Claude Fable 5.1 (max) leads at 100.0%; the closest result above is o1-preview at 31.1%. It covers competition maths (AIME 2024-25 style). The board median is 57.8%, so mistral-small-3.2-2506 is 27.5 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.

mistral-small-3.2-2506 lands below the middle on GPQA Diamond: 49.1%, #189 of 275, with 68% of the field scoring higher. GPT-6 Astra (max) leads at 95.8%; the closest result above is qwen2.5-72b-instruct at 49.1%. It covers expert-level science questions. The board median is 71.7%, so mistral-small-3.2-2506 is 22.7 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.

mistral-small-3.2-2506 lands below the middle on Chess Puzzles: 1.0%, #96 of 122, with 78% of the field scoring higher. GPT-6 Astra (max) leads at 72.0%; the closest result above is mistral-small-3.1-2503 at 1.0%. It covers chess tactics puzzles. The board median is 12.5%, so mistral-small-3.2-2506 is 11.5 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.

Strengths and weaknesses

Reasoning, maths and science: uneven, ahead of 34% of the field on average across 2 benchmarks. Its best board here is OTIS Mock AIME (#121 of 189) and its weakest is GPQA Diamond (#189 of 275).

Release history

The Mistral AI model released before it was Mistral Small 3.2 on 2025-06-20, which scores 44.0. The next one was codestral-2508 on 2025-07-30, at 46.8.

Reading these numbers

The 3 scores on this page come from 1 source: Epoch AI Benchmarking Hub (3). No official leaderboard supplied any of them, so treat them as third-party measurements. With 3 results the aggregate rank can move a lot when one new score arrives.

Models ranked nearby

#523 gemini-1.5-flash-8b-exp-0827 (46.4)
#524 gemini-1.5-flash-8b-exp-0924 (46.4)
#525 ollama/mistral-small (46.4)
#527 Phi-3-mini-128k-instruct (46.3)
#528 DeepSeek Chat V2.5 (46.3)
#529 qwen1.5-110b-chat (46.3)