[whatmodel.sh](../../README.md) / MiniMax-M1 (40k) # MiniMax-M1 (40k) MiniMax · released 2025-06 · 456B params (45.9B active) · apache-2.0 **score 61.0** ±1.3 · comparison only: no current run option verified · from 12 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 MiniMax-M1 (40k) among every model on that task or test, worst to best.}

task         vs the others      rank  counts  tests
agent tasks  ●··········█   #2 of 2*     11%      3
coding       ●··········█   #2 of 2*     15%      2
math         ●··········█    #2 of 2     30%      3

agent tasks · #2 of 2 · 11% of its score

test                                result  vs the others in its run   difficulty      counts  why
SWE-bench Verified (maker)           55.6%  ▁▁▁▁▁▁▂●█▆▁▁ beats 45/138  hard · avg 23%     11%  sharp · at its level · small run
τ-bench Airline (GPT-4.1 user) (m…   60.0%  ●··········█ beats 0/1                          —  not counted yet: no other model in the …
τ-bench Retail (GPT-4.1 user) (ma…   67.8%  █··········● beats 1/1                          —  not counted yet: no other model in the …

coding · #2 of 2 · 15% of its score

test                                result  vs the others in its run   difficulty        counts  why
SWE-bench Verified (maker)           55.6%  ▁▁▁▁▁▁▂●█▆▁▁ beats 45/138  hard · avg 23%       11%  sharp · at its level · small run
LiveCodeBench 2024-08–2025-05 (ve…   62.3%  ▃···●··▅··▃▃ beats 1/7     medium · avg 43%    4.6%  at its level · small run

math · #2 of 2 · 30% of its score

test               result  vs the others in its run   difficulty           counts  why
AIME 2025 (maker)   74.6%  ▁·▁▁▁▂▅▆●▇▅▁ beats 74/133  medium · avg 41%        12%  sharp · at its level · small run
AIME 2024 (maker)   83.3%  ▁▁▁▂▁▃▁▅█●█▃ beats 60/85   medium · avg 56%        11%  sharp · small run
MATH-500 (maker)    96.0%  ▁▃▂▃▄▇▅▇●▄▂▁ beats 59/85   very easy · avg 89%    6.3%  maxed out · small run

other tests (7)

test                          result  vs the others in its run    difficulty            counts  why
GPQA Diamond (maker)           69.2%  ▁▁▁▁▂▄▅▅●██▄ beats 152/322  hard · avg 41%           15%  sharp · at its level · small run
LongBench v2 (maker)           61.0%  ▂·▁·▂▃▁▄▄▃●▄ beats 27/33    hard · avg 39%          7.6%  at its level · small run
Humanity's Last Exam (maker)    7.2%  ▁▁▁●▆▆▇██▆▁▃ beats 9/111    very hard · avg 3.1%    7.4%  small run
ZebraLogic (maker)             80.1%  █·▁▁▁●·▄▄▁▄▁ beats 11/24    medium · avg 59%        7.0%  small run
MMLU-Pro (maker)               80.6%  ▁▁·▁▁▁▃▂▄▅●▁ beats 128/188  medium · avg 59%        6.9%  small run
SimpleQA (maker)               17.9%  ▄▄▄▆█▆●██·▂█ beats 18/32    very hard · avg 7.5%    6.4%  small run
MultiChallenge (maker)         44.7%  ▁·▁·▁▃●▅▃▂█▅ beats 8/30     hard · avg 27%          4.2%  at its level · small run

## 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
MiniMaxAI/MiniMax-M1-80k model card (su…       12   99% ▇▇▇▇▇▇▇▇▇▇▇▇
prior: pull toward the middle                        1% ▇
weighted average                                   = 61.0

_{Licences: MiniMaxAI/MiniMax-M1-80k model card ([apache-2.0](../../licenses/MiniMaxAI--MiniMax-M1-80k.txt))}

Not counted (2)

source                  test                            score  why
MiniMaxAI/MiniMax-M1-…  τ-bench Airline (GPT-4.1 user)  60.0%  too few models have it yet
MiniMaxAI/MiniMax-M1-…  τ-bench Retail (GPT-4.1 user)   67.8%  too few models have it yet

## How to run it No verified API or local download yet. [interactive version](https://whatmodel.sh/model/minimax-m1-40k) · [JSON](https://whatmodel.sh/api?format=json&all=1)