MiniMax-M2 1.5B on HumanEval: score, rank and what it means
MiniMax-M2 1.5B scores 58.3 on HumanEval, placing it #520 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.
Score distribution
The chart shows the top 10 models on HumanEval, with MiniMax-M2 1.5B highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 2 | Gemini 3 Pro Pro | Google DeepMind | 200000 | $19.80 | 87.3 |
| 3 | o4 Max | OpenAI | 2000000 | $19.51 | 86.2 |
| 4 | Grok 4 Reasoning | xAI | 2000000 | $19.67 | 87.8 |
| 5 | Claude Opus 4.5 | Anthropic | 400000 | $19.42 | 87.7 |
| 6 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 7 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 8 | Grok 4 Max | xAI | 2000000 | $19.70 | 86.6 |
| 9 | GPT-5.2 Turbo | OpenAI | 1000000 | $20.73 | 87.4 |
| 10 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
What this score means
On HumanEval, MiniMax-M2 1.5B sits at #520 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 38.5 points. The median model in this index scores 77.4, which puts MiniMax-M2 1.5B below the midpoint.
MiniMax models average 73.6 on this benchmark. MiniMax-M2 1.5B is 15.3 points below that provider line, so it is a weaker result than the average MiniMax model.
Among small open-weight models, the average is 56.7. MiniMax-M2 1.5B is 1.6 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 58.3 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 $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 HumanEval. The models immediately around it in the ranking are shown below so you can compare score and price together.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Mixtral 8B | Mistral AI | 8192 | $0.91 | 55.4 |
| Qwen3-Coder 1.5B | Alibaba Cloud | 32768 | $0.76 | 52.8 |
| Llama 3 Hyperbolic 8B | Hyperbolic | 16384 | $0.92 | 56.0 |
| Mixtral Groq 7B | Groq | 4096 | $0.70 | 53.4 |
| MiniMax-M2 1.5B | MiniMax | 16384 | $0.84 | 54.6 |
| Llama 3 Anyscale 7B | Anyscale | 4096 | $0.98 | 56.2 |
| Nemotron 4 7B | NVIDIA | 16384 | $1.05 | 56.9 |
Other benchmarks for MiniMax-M2 1.5B
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 59.6 | 531 | 12th | |
| GPQA Diamond | 49.9 | 525 | 13th | |
| SWE-bench Verified | 42.8 | 492 | 18th | |
| MATH-500 | 53.5 | 530 | 12th | |
| AIME 2025 | 39.6 | 543 | 10th | |
| LiveCodeBench | 41.5 | 530 | 12th | |
| IFEval | 65.9 | 521 | 13th | |
| 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 HumanEval?
MiniMax-M2 1.5B scores 58.3 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.
How does MiniMax-M2 1.5B rank on HumanEval?
It ranks #520 of 600 models, in the 13th percentile. The leader is GPT-5.2 Pro at 96.8.
Is MiniMax-M2 1.5B good at HumanEval?
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 HumanEval score calculated?
HumanEval 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 1.5B cost?
MiniMax-M2 1.5B costs $0.84 per million input tokens and $2.96 per million output tokens.