Coding · MiniMax

MiniMax-M2 8B on SWE-bench Verified: score, rank and what it means

MiniMax-M2 8B scores 50.0 on SWE-bench Verified, placing it #423 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
50.0
0–100 scale
Rank
#423
of 600
Percentile
30th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
31.7
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with MiniMax-M2 8B highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 81.7
Claude Opus 4.5 Pro 81.1
GPT-5.2 Max 80.5
Claude Sonnet 4.5 Max 80.2
GPT-5.2 80.2
GPT-5.1 Pro 80.1
o4 Max 79.8
Claude Sonnet 4.5 Reasoning 79.6
Claude Opus 4.5 Max 79.5
Claude Opus 4.5 Reasoning 79.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
3 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
4 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2
5 GPT-5.2 OpenAI 2000000 $19.71 88.0
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 o4 Max OpenAI 2000000 $19.51 86.2
8 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2

What this score means

On SWE-bench Verified, MiniMax-M2 8B sits at #423 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 31.7 points. The median model in this index scores 61.0, which puts MiniMax-M2 8B below the midpoint.

MiniMax models average 57.0 on this benchmark. MiniMax-M2 8B is 7.0 points below that provider line, so it is a weaker result than the average MiniMax model.

Among small open-weight models, the average is 39.0. MiniMax-M2 8B is 11.0 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 50.0 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 $1.65 per million input tokens, MiniMax-M2 8B is below the median input price of $4.00 across the 600 models scored on SWE-bench Verified. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Zephyr Hugging Face 8192 $1.61 62.8
Molmo Base Allen Institute for AI 4096 $2.02 65.0
Reka Core Nano Reka AI 16384 $5.45 65.1
Llama 4 Maverick 7B Meta AI 4096 $1.52 61.9
MiniMax-M2 8B MiniMax 32768 $1.65 61.7
DeepSeek-V3.2 7B DeepSeek 4096 $1.75 63.2
GLM-4.6 7B Zhipu AI 16384 $1.52 61.8

Other benchmarks for MiniMax-M2 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 65.4 446 26th
GPQA Diamond 56.9 442 26th
HumanEval 65.8 433 28th
MATH-500 62.2 441 27th
AIME 2025 53.4 429 29th
LiveCodeBench 50.0 448 25th
IFEval 71.8 431 28th
TruthfulQA 67.5 425 29th
HellaSwag 76.2 425 29th
MMMU 59.0 440 27th
Arena Elo 1300.9 419 30th

FAQ

What score does MiniMax-M2 8B get on SWE-bench Verified?

MiniMax-M2 8B scores 50.0 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does MiniMax-M2 8B rank on SWE-bench Verified?

It ranks #423 of 600 models, in the 30th percentile. The leader is GPT-5.2 Pro at 81.7.

Is MiniMax-M2 8B good at SWE-bench Verified?

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 SWE-bench Verified score calculated?

SWE-bench Verified is a coding 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 8B cost?

MiniMax-M2 8B costs $1.65 per million input tokens and $8.35 per million output tokens.

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