Reasoning · MiniMax

MiniMax-M2 Base on GPQA Diamond: score, rank and what it means

MiniMax-M2 Base scores 72.6 on GPQA Diamond, placing it #207 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
72.6
0–100 scale
Rank
#207
of 600
Percentile
66th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
14.4
points

Score distribution

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

GPT-5.2 Reasoning 87.0
GPT-5.1 Max 86.4
Claude Opus 4.5 Pro 86.0
GPT-5.1 Reasoning 85.6
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.2 84.9
o4 Turbo 84.8
Claude Opus 4.5 Max 84.6
Grok 4 Turbo 84.5
Claude Sonnet 4.5 Max 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 GPT-5.2 OpenAI 2000000 $19.71 88.0
7 o4 Turbo OpenAI 2000000 $19.34 86.6
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 Grok 4 Turbo xAI 1000000 $19.21 86.7
10 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2

What this score means

On GPQA Diamond, MiniMax-M2 Base sits at #207 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 14.4 points. The median model in this index scores 68.8, which puts MiniMax-M2 Base above the midpoint.

MiniMax models average 65.1 on this benchmark. MiniMax-M2 Base is 7.5 points above that provider line, so it is a stronger result than the average MiniMax model.

Among multimodal models, the average is 73.5. MiniMax-M2 Base is 0.9 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 72.6 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 $4.20 per million input tokens, MiniMax-M2 Base is above the median input price of $4.00 across the 600 models scored on GPQA Diamond. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
QwQ Chat Alibaba Cloud 65536 $4.28 78.2
Llama 3 Hyperbolic Chat Hyperbolic 200000 $3.64 75.1
Llama 3 Replicate Instruct Replicate 128000 $3.71 75.1
Llama 3 Hyperbolic Hyperbolic 65536 $3.86 74.5
MiniMax-M2 Base MiniMax 65536 $4.20 76.4
Reka Core Reasoning Reka AI 32768 $13.11 78.5
Seed-OSS ByteDance 32768 $3.74 75.3

Other benchmarks for MiniMax-M2 Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 80.0 184 69th
SWE-bench Verified 62.8 259 57th
HumanEval 80.0 233 61th
MATH-500 79.5 223 63th
AIME 2025 75.2 152 75th
LiveCodeBench 66.3 269 55th
IFEval 83.0 244 59th
TruthfulQA 79.9 182 70th
HellaSwag 87.8 150 75th
MMMU 73.3 210 65th
Arena Elo 1404.3 197 67th

FAQ

What score does MiniMax-M2 Base get on GPQA Diamond?

MiniMax-M2 Base scores 72.6 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does MiniMax-M2 Base rank on GPQA Diamond?

It ranks #207 of 600 models, in the 66th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is MiniMax-M2 Base good at GPQA Diamond?

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 GPQA Diamond score calculated?

GPQA Diamond is a reasoning 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 Base cost?

MiniMax-M2 Base costs $4.20 per million input tokens and $21.42 per million output tokens.

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