Mathematics · MiniMax

MiniMax-Text on MATH-500: score, rank and what it means

MiniMax-Text scores 79.0 on MATH-500, placing it #235 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
79.0
0–100 scale
Rank
#235
of 600
Percentile
61th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
17.7
points

Score distribution

The chart shows the top 10 models on MATH-500, with MiniMax-Text highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, MiniMax-Text sits at #235 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 17.7 points. The median model in this index scores 76.0, which puts MiniMax-Text above the midpoint.

MiniMax models average 71.1 on this benchmark. MiniMax-Text is 7.9 points above that provider line, so it is a stronger result than the average MiniMax model.

Among multimodal models, the average is 81.3. MiniMax-Text is 2.3 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 79.0 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 $4.44 per million input tokens, MiniMax-Text is above the median input price of $4.00 across the 600 models scored on MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
ERNIE 4.0 Reasoning Baidu 65536 $12.20 77.8
Llama 3 Modal Modal 32768 $3.82 74.9
Command R+ Cohere 32768 $3.96 76.3
Llama 3 Modal Chat Modal 65536 $3.55 73.3
MiniMax-Text MiniMax 32768 $4.44 77.0
Phi-4 Microsoft 200000 $3.96 75.4
Gemini 3 Flash Mini Google DeepMind 200000 $10.71 76.0

Other benchmarks for MiniMax-Text

BenchmarkScoreRankPercentileRelative
MMLU-Pro 78.9 213 65th
GPQA Diamond 75.6 131 78th
SWE-bench Verified 68.2 142 76th
HumanEval 80.5 223 63th
AIME 2025 71.1 234 61th
LiveCodeBench 71.4 162 73th
IFEval 83.2 240 60th
TruthfulQA 78.8 225 63th
HellaSwag 85.8 224 63th
MMMU 74.0 192 68th
Arena Elo 1420.4 147 76th

FAQ

What score does MiniMax-Text get on MATH-500?

MiniMax-Text scores 79.0 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does MiniMax-Text rank on MATH-500?

It ranks #235 of 600 models, in the 61st percentile. The leader is GPT-5.2 Max at 96.7.

Is MiniMax-Text good at MATH-500?

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 MATH-500 score calculated?

MATH-500 is a mathematics 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 cost?

MiniMax-Text costs $4.44 per million input tokens and $18.68 per million output tokens.

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