Instruction following · MiniMax

MiniMax-M2 1.5B on IFEval: score, rank and what it means

MiniMax-M2 1.5B scores 65.9 on IFEval, placing it #521 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
65.9
0–100 scale
Rank
#521
of 600
Percentile
13th
within the index
Benchmark avg
78.6
all models
Leader
96.1
Claude Opus 4.5 Pro
Gap to leader
30.2
points

Score distribution

The chart shows the top 10 models on IFEval, with MiniMax-M2 1.5B 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 1.5B sits at #521 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 30.2 points. The median model in this index scores 81.2, which puts MiniMax-M2 1.5B below the midpoint.

MiniMax models average 78.1 on this benchmark. MiniMax-M2 1.5B is 12.2 points below that provider line, so it is a weaker result than the average MiniMax model.

Among small open-weight models, the average is 64.9. MiniMax-M2 1.5B 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 65.9 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 $0.84 per million input tokens, MiniMax-M2 1.5B is below 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
Mixtral Turbo 7B Together AI 8192 $0.68 53.2
Kimi K1.5 1.5B Moonshot AI 4096 $0.75 53.2
Llama 3 Hyperbolic 8B Hyperbolic 16384 $0.92 56.0
Llama 3.1 Turbo 7B Together AI 8192 $0.98 56.4
MiniMax-M2 1.5B MiniMax 16384 $0.84 54.6
Mistral Small 3 7B Mistral AI 4096 $0.89 55.2
Phi-4 8B Microsoft 32768 $0.96 54.9

Other benchmarks for MiniMax-M2 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 59.6 531 12th
GPQA Diamond 49.9 525 13th
SWE-bench Verified 42.8 492 18th
HumanEval 58.3 520 13th
MATH-500 53.5 530 12th
AIME 2025 39.6 543 10th
LiveCodeBench 41.5 530 12th
TruthfulQA 63.0 492 18th
HellaSwag 72.0 500 17th
MMMU 54.6 501 17th
Arena Elo 1238.4 516 14th

FAQ

What score does MiniMax-M2 1.5B get on IFEval?

MiniMax-M2 1.5B scores 65.9 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.

How does MiniMax-M2 1.5B rank on IFEval?

It ranks #521 of 600 models, in the 13th percentile. The leader is Claude Opus 4.5 Pro at 96.1.

Is MiniMax-M2 1.5B good at IFEval?

It is below the median for this benchmark, so test it carefully before relying on it for this capability. 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 1.5B cost?

MiniMax-M2 1.5B costs $0.84 per million input tokens and $2.96 per million output tokens.

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