Knowledge · MiniMax

MiniMax-Text Instruct on MMLU-Pro: score, rank and what it means

MiniMax-Text Instruct scores 78.7 on MMLU-Pro, placing it #222 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
78.7
0–100 scale
Rank
#222
of 600
Percentile
63th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
12.9
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with MiniMax-Text Instruct highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 91.6
GPT-5.1 Max 91.3
Claude Opus 4.5 Pro 91.2
Claude Opus 4.5 Reasoning 90.7
Gemini 3 Pro Reasoning 90.1
GPT-5.1 Reasoning 90.0
GPT-5.2 89.9
Claude Opus 4.5 Max 89.5
GPT-5.2 Vision 89.5
Gemini 3 Pro Max 89.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
6 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
7 GPT-5.2 OpenAI 2000000 $19.71 88.0
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On MMLU-Pro, MiniMax-Text Instruct sits at #222 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 12.9 points. The median model in this index scores 76.1, which puts MiniMax-Text Instruct above the midpoint.

MiniMax models average 72.7 on this benchmark. MiniMax-Text Instruct is 6.0 points above that provider line, so it is a stronger result than the average MiniMax model.

Among multimodal models, the average is 80.0. MiniMax-Text Instruct is 1.3 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 78.7 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 $4.59 per million input tokens, MiniMax-Text Instruct is above the median input price of $4.00 across the 600 models scored on MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Hunyuan-Turbo Turbo Tencent 65536 $11.60 77.4
Llama 3 Replicate Replicate 200000 $3.75 75.7
Llama 3.1 Meta AI 200000 $4.16 76.3
Reka Flash Reka AI 128000 $9.95 74.1
MiniMax-Text Instruct MiniMax 128000 $4.59 77.7
Nova Lite Reasoning Amazon 32768 $9.92 74.3
Sonar Pro Perplexity 128000 $13.01 79.1

Other benchmarks for MiniMax-Text Instruct

BenchmarkScoreRankPercentileRelative
GPQA Diamond 72.8 202 66th
SWE-bench Verified 69.3 125 79th
HumanEval 81.5 198 67th
MATH-500 80.7 195 68th
AIME 2025 78.5 107 82th
LiveCodeBench 68.1 225 63th
IFEval 87.6 112 81th
TruthfulQA 78.5 238 60th
HellaSwag 85.9 220 63th
MMMU 73.0 222 63th
Arena Elo 1429.1 123 80th

FAQ

What score does MiniMax-Text Instruct get on MMLU-Pro?

MiniMax-Text Instruct scores 78.7 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does MiniMax-Text Instruct rank on MMLU-Pro?

It ranks #222 of 600 models, in the 63rd percentile. The leader is GPT-5.2 Pro at 91.6.

Is MiniMax-Text Instruct good at MMLU-Pro?

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 MMLU-Pro score calculated?

MMLU-Pro is a knowledge 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-Text Instruct cost?

MiniMax-Text Instruct costs $4.59 per million input tokens and $21.17 per million output tokens.

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