Safety · MiniMax

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

MiniMax-M2 scores 83.5 on TruthfulQA, placing it #93 of 600 models in the index. The benchmark average is 73.6 and the leader is GPT-5.1 Max at 91.1.

Score
83.5
0–100 scale
Rank
#93
of 600
Percentile
85th
within the index
Benchmark avg
73.6
all models
Leader
91.1
GPT-5.1 Max
Gap to leader
7.6
points

Score distribution

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

GPT-5.1 Max 91.1
Gemini 3 Pro Reasoning 90.3
GPT-5.1 Reasoning 90.0
GPT-5.2 Pro 90.0
GPT-5.2 89.7
Gemini 3 Pro Max 89.6
Grok 4 Reasoning 89.4
Qwen3-Max Max 89.3
GPT-5.1 89.2
GPT-5.1 Turbo 89.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
2 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
3 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
4 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
5 GPT-5.2 OpenAI 2000000 $19.71 88.0
6 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9
7 Grok 4 Reasoning xAI 2000000 $19.67 87.8
8 Qwen3-Max Max Alibaba Cloud 400000 $18.53 85.9
9 GPT-5.1 OpenAI 2000000 $19.01 86.0
10 GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1

What this score means

On TruthfulQA, MiniMax-M2 sits at #93 of 600. The leader, GPT-5.1 Max, scores 91.1, so the gap to the top is 7.6 points. The median model in this index scores 76.3, which puts MiniMax-M2 above the midpoint.

MiniMax models average 72.7 on this benchmark. MiniMax-M2 is 10.8 points above that provider line, so it is a stronger result than the average MiniMax model.

Among multimodal models, the average is 80.1. MiniMax-M2 is 3.4 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 83.5 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 $5.19 per million input tokens, MiniMax-M2 is above the median input price of $4.00 across the 600 models scored on TruthfulQA. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Mistral Large 3 Mistral AI 128000 $5.41 81.7
ERNIE 4.5 Max Baidu 128000 $14.41 80.6
o3 Turbo OpenAI 200000 $16.63 83.4
DeepSeek-V3.2 Base DeepSeek 128000 $5.05 80.2
MiniMax-M2 MiniMax 200000 $5.19 80.6
Nova Pro Turbo Amazon 128000 $13.18 78.4
Command A Reasoning Cohere 400000 $13.74 80.2

Other benchmarks for MiniMax-M2

BenchmarkScoreRankPercentileRelative
MMLU-Pro 81.8 127 79th
GPQA Diamond 75.4 137 77th
SWE-bench Verified 69.9 112 81th
HumanEval 88.0 73 88th
MATH-500 82.3 157 74th
AIME 2025 78.1 115 81th
LiveCodeBench 73.4 121 80th
IFEval 86.1 153 75th
HellaSwag 90.4 76 87th
MMMU 78.0 98 84th
Arena Elo 1423.8 130 78th

FAQ

What score does MiniMax-M2 get on TruthfulQA?

MiniMax-M2 scores 83.5 on TruthfulQA in this index. The benchmark average is 73.6 and the top score is 91.1.

How does MiniMax-M2 rank on TruthfulQA?

It ranks #93 of 600 models, in the 85th percentile. The leader is GPT-5.1 Max at 91.1.

Is MiniMax-M2 good at TruthfulQA?

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 TruthfulQA score calculated?

TruthfulQA is a safety 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 cost?

MiniMax-M2 costs $5.19 per million input tokens and $22.73 per million output tokens.

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