Commonsense · MiniMax

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

MiniMax-M2 8B scores 76.2 on HellaSwag, placing it #425 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
76.2
0–100 scale
Rank
#425
of 600
Percentile
29th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
19.9
points

Score distribution

The chart shows the top 10 models on HellaSwag, with MiniMax-M2 8B highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.1
GPT-5.2 Turbo 95.5
GPT-5.2 Pro 95.3
Claude Opus 4.5 Pro 95.2
Claude Sonnet 4.5 Reasoning 95.2
Grok 4 Reasoning 95.2
GPT-5.2 Vision 94.6
Gemini 3 Pro Turbo 94.6
GPT-5.1 Reasoning 94.4
o4 Pro 94.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
8 Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
9 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
10 o4 Pro OpenAI 1000000 $19.37 87.3

What this score means

On HellaSwag, MiniMax-M2 8B sits at #425 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 19.9 points. The median model in this index scores 83.6, which puts MiniMax-M2 8B below the midpoint.

MiniMax models average 81.3 on this benchmark. MiniMax-M2 8B is 5.1 points below that provider line, so it is a weaker result than the average MiniMax model.

Among small open-weight models, the average is 70.2. MiniMax-M2 8B is 6.0 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 76.2 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 HellaSwag. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Zephyr Chat Hugging Face 4096 $1.49 61.3
Mistral Large 3 8B Mistral AI 16384 $1.62 61.6
Zephyr Hugging Face 8192 $1.61 62.8
Kimi K1.5 8B Moonshot AI 8192 $1.54 62.2
MiniMax-M2 8B MiniMax 32768 $1.65 61.7
Hunyuan-Turbo Nano Tencent 32768 $4.65 62.7
SmolLM3 Chat Hugging Face 16384 $1.61 62.1

Other benchmarks for MiniMax-M2 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 65.4 446 26th
GPQA Diamond 56.9 442 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
MMMU 59.0 440 27th
Arena Elo 1300.9 419 30th

FAQ

What score does MiniMax-M2 8B get on HellaSwag?

MiniMax-M2 8B scores 76.2 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does MiniMax-M2 8B rank on HellaSwag?

It ranks #425 of 600 models, in the 29th percentile. The leader is GPT-5.2 Max at 96.1.

Is MiniMax-M2 8B good at HellaSwag?

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 HellaSwag score calculated?

HellaSwag is a commonsense 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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