[whatmodel.sh](../../README.md) / Magistral Medium 1.2 (2509) # Magistral Medium 1.2 (2509) Mistral · released 2025-09 · proprietary **score 62.0** ±1.7 · comparison only: no current run option verified · from 4 benchmark results across 1 source · † no independently run results verified Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only. ## What it's good at ● marks Magistral Medium 1.2 (2509) among every model on that task or test, worst to best. 
task    vs the others          rank  counts  tests
coding  ▃█······●·▃▃       #3 of 7*     12%      1
math    ▁▁▃▆██●█▃▁▁▁   #165 of 530*     53%      2
coding · #3 of 7 · 12% of its score Trails [Magistral Small 1.2](magistral-small-2509.md), [Mistral Small 4 (119B-A6.5B)](mistral-small-4.md) here, though they rank lower overall. 
test                                result  vs the others in its run  difficulty        counts  why
LiveCodeBench v5 (window unspecif…   75.0%  ▄█▄······▄·● beats 5/5    medium · avg 50%     12%  at its level
math · #165 of 530 · 53% of its score Beats [MiMo-V2.5 (310B-A15B)](mimo-v2-5.md), [MiniMax-M2.7](minimax-m2-7.md), [MiniMax-M2.1](minimax-m2-1.md) here, though they rank higher overall. Trails [Nemotron 3 Nano 30B-A3B](nemotron-3-nano-30b-a3b.md), [Qwen3-VL 8B Thinking](qwen3-vl-8b-thinking.md), [Olmo 3 32B Think](olmo-3-32b-think.md) here, though they rank lower overall. 
test               result  vs the others in its run  difficulty        counts  why
AIME 2025 (maker)   83.5%  █▃·····▃···● beats 5/5    medium · avg 48%     32%  sharp
AIME 2024 (maker)   91.8%  █▃·····▃···● beats 5/5    medium · avg 60%     21%  sharp
other tests (1) 
test                  result  vs the others in its run  difficulty        counts  why
GPQA Diamond (maker)   76.3%  █·█·███····● beats 5/5    medium · avg 52%     34%  sharp
## How the score was worked out Each result implies a score on its own, after adjusting for how hard that test is and who ran it. The model's score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its *counts* column above; here it is added up by who ran the tests. [Method](../method.md) 
source                                    results  share of the score
mistralai/Magistral-Small-2509 model ca…        4   99% ▇▇▇▇▇▇▇▇▇▇▇▇
prior: pull toward the middle                        1% ▇
weighted average                                   = 62.0
Licences: mistralai/Magistral-Small-2509 model card ([Apache-2.0](../../licenses/mistralai--Magistral-Small-2509.txt)) ## How to run it No verified API or local download yet. [interactive version](https://whatmodel.sh/model/magistral-medium-2509) · [JSON](https://whatmodel.sh/api?format=json&all=1)