Commonsense · MiniMax

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

MiniMax-M2 Chat scores 87.8 on HellaSwag, placing it #151 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
87.8
0–100 scale
Rank
#151
of 600
Percentile
75th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
8.3
points

Score distribution

The chart shows the top 10 models on HellaSwag, with MiniMax-M2 Chat 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 Chat sits at #151 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 8.3 points. The median model in this index scores 83.6, which puts MiniMax-M2 Chat above the midpoint.

MiniMax models average 81.3 on this benchmark. MiniMax-M2 Chat is 6.5 points above that provider line, so it is a stronger result than the average MiniMax model.

Among multimodal models, the average is 86.8. MiniMax-M2 Chat is 1.0 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 87.8 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 $5.02 per million input tokens, MiniMax-M2 Chat is above 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
QwQ Chat Alibaba Cloud 65536 $4.28 78.2
Doubao 1.5 Pro Max ByteDance 400000 $14.93 81.2
GLM-4.5 Instruct Zhipu AI 200000 $4.70 78.8
MiniMax-M2 Base MiniMax 65536 $4.20 76.4
MiniMax-M2 Chat MiniMax 200000 $5.02 80.2
ERNIE 4.5 Max Baidu 128000 $14.41 80.6
Hunyuan-Large Instruct Tencent 65536 $4.39 78.2

Other benchmarks for MiniMax-M2 Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 84.3 75 88th
GPQA Diamond 77.8 91 85th
SWE-bench Verified 66.4 182 70th
HumanEval 84.2 128 79th
MATH-500 86.0 93 85th
AIME 2025 78.3 109 82th
LiveCodeBench 70.4 184 69th
IFEval 88.0 102 83th
TruthfulQA 80.3 172 71th
MMMU 79.2 70 88th
Arena Elo 1443.0 93 85th

FAQ

What score does MiniMax-M2 Chat get on HellaSwag?

MiniMax-M2 Chat scores 87.8 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does MiniMax-M2 Chat rank on HellaSwag?

It ranks #151 of 600 models, in the 75th percentile. The leader is GPT-5.2 Max at 96.1.

Is MiniMax-M2 Chat good at HellaSwag?

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 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 Chat cost?

MiniMax-M2 Chat costs $5.02 per million input tokens and $18.95 per million output tokens.

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