mistral-medium-2312: benchmark scores, price and ranking
mistral-medium-2312 from Mistral AI ranks #489 of 743 LLMs on the LLMs Tiger aggregate benchmark score (46.7), based on 1 benchmark results captured up to 2026-10-13.
- Organisation
- Mistral AI
- Type
- Frontier model
- Open weights
- No
- Released
- 2023-12-11 (source: epoch)
- Aggregate rank
- #489 of 743 (score 46.7)
Across the 1 benchmark where at least ten models are scored, mistral-medium-2312 is in the top 10% on 0 and in the top half on 0.
mistral-medium-2312 benchmark results
| Benchmark | Score | Rank | Source | Captured |
|---|---|---|---|---|
| DTBench | 53.3% | #119 of 146 | Epoch AI Benchmarking Hub | 2026-10-13 |
About mistral-medium-2312
mistral-medium-2312 is a frontier model from Mistral AI. It was released on 2023-12-11, according to Epoch AI. No API price is listed for it yet. We hold 1 benchmark result for it across 1 area, and none is in the top tenth of its board.
Where mistral-medium-2312 stands
On our aggregate score, mistral-medium-2312 is #489 of 743 ranked models, in the lower half. Its score is 46.7; the scale is centred on 50, so it sits 3.3 points below the typical model. That beats 34% of the ranked field. Among the 44 ranked Mistral AI models it is #14. The next one up is codestral-2508 at 46.8. The next one down is mistral-small-2402 at 46.7.
mistral-medium-2312, benchmark by benchmark
DTBench is a weak spot. mistral-medium-2312 scores 53.3%, #119 of 146, behind 81% of the models measured. The leader, Claude Opus 5.5 (max), reaches 98.9%. It covers dynamic tool-use benchmark. The board median is 68.8%, so mistral-medium-2312 is 15.5 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
Release history
The Mistral AI model released before it was open-mistral-7b on 2023-09-27, which scores 41.0. The next one was Mixtral-8x7B-Instruct-v0.1 on 2023-12-11, at 45.7.
Reading these numbers
The 1 score on this page comes from 1 source: Epoch AI Benchmarking Hub (1). No official leaderboard supplied any of them, so treat them as third-party measurements. With 1 results the aggregate rank can move a lot when one new score arrives.
Models ranked nearby
- #486 codestral-2508 (46.8)
- #487 Mellum2-12B-A2.5B-Instruct (46.8)
- #488 Gemini 2.0 Pro Exp (Feb 2025) (46.7)
- #490 grok-4-1-fast-reasoning (46.7)
- #491 Llama 4 Maverick Instruct (46.7)
- #492 internlm2-chat-20b (46.7)
More from Mistral AI
- Mistral Large 2 (2407) (#231, 49.9)
- codestral-2405 (#352, 48.4)
- pixtral-large-2411 (#360, 48.3)
- Codestral-22B-v0.1-Q4_K_M (#392, 48.0)
- codestral:22b-v0.1-q8_0 (#393, 48.0)
- Mistral Large 4 (high) (#411, 47.7)
Compare it on the live leaderboard → · How the aggregate score works