Reasoning · MiniMax

MiniMax-M2 8B on GPQA Diamond: score, rank and what it means

MiniMax-M2 8B scores 56.9 on GPQA Diamond, placing it #442 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
56.9
0–100 scale
Rank
#442
of 600
Percentile
26th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
30.1
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with MiniMax-M2 8B 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 8B sits at #442 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 30.1 points. The median model in this index scores 68.8, which puts MiniMax-M2 8B below the midpoint.

MiniMax models average 65.1 on this benchmark. MiniMax-M2 8B is 8.2 points below that provider line, so it is a weaker result than the average MiniMax model.

Among small open-weight models, the average is 49.3. MiniMax-M2 8B is 7.6 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 56.9 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 $1.65 per million input tokens, MiniMax-M2 8B is below 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
Zephyr Base Hugging Face 4096 $1.26 59.5
ERNIE 4.0 Nano Baidu 32768 $4.68 62.1
Kimi K2 7B Moonshot AI 16384 $1.72 62.7
Nova Lite Nano Amazon 8192 $3.29 59.5
MiniMax-M2 8B MiniMax 32768 $1.65 61.7
Llama 3.1 Turbo 8B Together AI 32768 $1.16 58.8
MiniMax-Text 8B MiniMax 4096 $1.22 59.5

Other benchmarks for MiniMax-M2 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 65.4 446 26th
SWE-bench Verified 50.0 423 30th
HumanEval 65.8 433 28th
MATH-500 62.2 441 27th
AIME 2025 53.4 429 29th
LiveCodeBench 50.0 448 25th
IFEval 71.8 431 28th
TruthfulQA 67.5 425 29th
HellaSwag 76.2 425 29th
MMMU 59.0 440 27th
Arena Elo 1300.9 419 30th

FAQ

What score does MiniMax-M2 8B get on GPQA Diamond?

MiniMax-M2 8B scores 56.9 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does MiniMax-M2 8B rank on GPQA Diamond?

It ranks #442 of 600 models, in the 26th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is MiniMax-M2 8B good at GPQA Diamond?

It is below the median for this benchmark, so test it carefully before relying on it for this capability. 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 8B cost?

MiniMax-M2 8B costs $1.65 per million input tokens and $8.35 per million output tokens.

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