Instruction following · MiniMax

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

MiniMax-M2 Instruct scores 87.3 on IFEval, placing it #126 of 600 models in the index. The benchmark average is 78.6 and the leader is Claude Opus 4.5 Pro at 96.1.

Score
87.3
0–100 scale
Rank
#126
of 600
Percentile
79th
within the index
Benchmark avg
78.6
all models
Leader
96.1
Claude Opus 4.5 Pro
Gap to leader
8.8
points

Score distribution

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

Claude Opus 4.5 Pro 96.1
Claude Opus 4.5 Reasoning 95.9
GPT-5.2 Pro 95.6
GPT-5.2 Max 95.2
GPT-5.2 Reasoning 95.0
GPT-5.1 Pro 94.8
Gemini 3 Pro Max 94.7
GPT-5.1 Reasoning 94.6
Claude Opus 4.5 Max 94.5
o4 Reasoning 94.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
2 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9
8 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 o4 Reasoning OpenAI 1000000 $19.69 87.5

What this score means

On IFEval, MiniMax-M2 Instruct sits at #126 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 8.8 points. The median model in this index scores 81.2, which puts MiniMax-M2 Instruct above the midpoint.

MiniMax models average 78.1 on this benchmark. MiniMax-M2 Instruct is 9.2 points above that provider line, so it is a stronger result than the average MiniMax model.

Among multimodal models, the average is 85.2. MiniMax-M2 Instruct is 2.1 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 87.3 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 $5.11 per million input tokens, MiniMax-M2 Instruct is above the median input price of $4.00 across the 600 models scored on IFEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 4 Maverick Base Meta AI 128000 $4.68 79.1
Llama 4 Maverick Chat Meta AI 128000 $5.09 79.7
Nova Pro Reasoning Amazon 200000 $13.48 79.4
Sonar Pro Perplexity 128000 $13.01 79.1
MiniMax-M2 Instruct MiniMax 128000 $5.11 79.4
Reka Core Turbo Reka AI 32768 $12.58 78.4
Claude Haiku 4.5 Turbo Anthropic 200000 $14.37 80.0

Other benchmarks for MiniMax-M2 Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 82.1 121 80th
GPQA Diamond 73.7 178 70th
SWE-bench Verified 69.9 113 81th
HumanEval 86.7 95 84th
MATH-500 82.1 165 73th
AIME 2025 77.8 118 80th
LiveCodeBench 71.1 170 72th
TruthfulQA 80.0 178 70th
HellaSwag 88.5 125 79th
MMMU 74.1 189 69th
Arena Elo 1442.2 95 84th

FAQ

What score does MiniMax-M2 Instruct get on IFEval?

MiniMax-M2 Instruct scores 87.3 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.

How does MiniMax-M2 Instruct rank on IFEval?

It ranks #126 of 600 models, in the 79th percentile. The leader is Claude Opus 4.5 Pro at 96.1.

Is MiniMax-M2 Instruct good at IFEval?

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 IFEval score calculated?

IFEval is a instruction following 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 Instruct cost?

MiniMax-M2 Instruct costs $5.11 per million input tokens and $25.04 per million output tokens.

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