Coding · MiniMax

MiniMax-M2 Instruct on HumanEval: score, rank and what it means

MiniMax-M2 Instruct scores 86.7 on HumanEval, placing it #95 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
86.7
0–100 scale
Rank
#95
of 600
Percentile
84th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
10.1
points

Score distribution

The chart shows the top 10 models on HumanEval, with MiniMax-M2 Instruct highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 96.8
Gemini 3 Pro Pro 95.0
o4 Max 94.6
Grok 4 Reasoning 93.8
Claude Opus 4.5 93.7
GPT-5.2 Max 93.6
Claude Opus 4.5 Pro 93.4
Grok 4 Max 93.4
GPT-5.2 Turbo 93.2
GPT-5.1 Reasoning 92.9

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Gemini 3 Pro Pro Google DeepMind 200000 $19.80 87.3
3 o4 Max OpenAI 2000000 $19.51 86.2
4 Grok 4 Reasoning xAI 2000000 $19.67 87.8
5 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
6 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
7 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
8 Grok 4 Max xAI 2000000 $19.70 86.6
9 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
10 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3

What this score means

On HumanEval, MiniMax-M2 Instruct sits at #95 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 10.1 points. The median model in this index scores 77.4, which puts MiniMax-M2 Instruct above the midpoint.

MiniMax models average 73.6 on this benchmark. MiniMax-M2 Instruct is 13.1 points above that provider line, so it is a stronger result than the average MiniMax model.

Among multimodal models, the average is 82.2. MiniMax-M2 Instruct is 4.5 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 86.7 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.

Price context

At $5.11 per million input tokens, MiniMax-M2 Instruct is above the median input price of $4.00 across the 600 models scored on HumanEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Gemini 3 Flash Reasoning Google DeepMind 128000 $17.05 83.7
GPT-4.1 Vision OpenAI 1000000 $14.88 82.0
Grok 3 Turbo xAI 128000 $15.97 83.1
Gemini 2.5 Pro Reasoning Google DeepMind 128000 $16.81 83.8
MiniMax-M2 Instruct MiniMax 128000 $5.11 79.4
Llama 4 Scout Meta AI 200000 $4.90 79.3
DeepSeek-R1 DeepSeek 128000 $5.83 82.8

Other benchmarks for MiniMax-M2 Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 82.1 121 80th
GPQA Diamond 73.7 178 70th
SWE-bench Verified 69.9 113 81th
MATH-500 82.1 165 73th
AIME 2025 77.8 118 80th
LiveCodeBench 71.1 170 72th
IFEval 87.3 126 79th
TruthfulQA 80.0 178 70th
HellaSwag 88.5 125 79th
MMMU 74.1 189 69th
Arena Elo 1442.2 95 84th

FAQ

What score does MiniMax-M2 Instruct get on HumanEval?

MiniMax-M2 Instruct scores 86.7 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does MiniMax-M2 Instruct rank on HumanEval?

It ranks #95 of 600 models, in the 84th percentile. The leader is GPT-5.2 Pro at 96.8.

Is MiniMax-M2 Instruct good at HumanEval?

Yes, relative to the index: it is above the median and inside the top half of scores. The result should be read alongside its price and context window.

How is the HumanEval score calculated?

HumanEval is a coding benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.

What does MiniMax-M2 Instruct cost?

MiniMax-M2 Instruct costs $5.11 per million input tokens and $25.04 per million output tokens.

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