MiniMax, open weights

# MiniMax-M2.7

> MiniMax-M2.7 by MiniMax, released March 2026. Ranked #196 of 354 with a Noometry Index of 37.7. API: $0.30 in / $1.20 out per M tokens. 205K context. Scores, sources and comparisons.
- Canonical page: https://noometry.com/models/minimax-m2-7
- Last updated: 2026-10-10
- Title: MiniMax-M2.7 Benchmarks, Price & Rank (October 2026)

MiniMax-M2.7 by MiniMax ranks 196th of 354 ranked models on the Noometry Index as of October 2026, with a score of 37.7. Its strongest category is long context, where it ranks 99th. API pricing starts at $0.30 per million input tokens and $1.20 per million output tokens, with a 205K-token context window.

Last verified October 10, 2026

## Specifications

- **Noometry rank:** #196 of 354
- **Index score:** 37.7
- **Evidence:** Confirmed 30 results
- **Provider:** [![](/logos/minimax.svg) MiniMax](https://noometry.com/providers/minimax)
- **Released:** March 18, 2026
- **Weights:** Open weights
- **Reasoning:** Yes
- **Context window:** 205K
- **Max output:** 131K
- **Input price:** $0.30 / M
- **Output price:** $1.20 / M
- **Blended price:** $0.52 / M
- **Output speed:** Not measured
- **Value:** #83 of 219
- **Knowledge cutoff:** Unknown
- **Input:** text
- **Hugging Face:** [MiniMaxAI/MiniMax-M2.7](https://huggingface.co/MiniMaxAI/MiniMax-M2.7)

## Category scores

Each category score combines every public result we have in that category.

MiniMax-M2.7 category scores

1.  Coding 41.8
2.  Agentic & Tool Use 25.1
3.  Reasoning 19.7
4.  Math 25.9
5.  Knowledge 37.7
6.  Multilingual 50.3
7.  Instruction Following 74.1
8.  Long Context 43.3
9.  Writing & Preference 58.9
10.  020406080

MiniMax-M2.7 category ranks
| Category | Score | Rank | Results |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 41.8 | #120 | 4 |
| [Agentic & Tool Use](https://noometry.com/best/agentic) | 25.1 | #111 | 3 |
| [Reasoning](https://noometry.com/best/reasoning) | 19.7 | #253 | 4 |
| [Math](https://noometry.com/best/math) | 25.9 | #263 | 2 |
| [Knowledge](https://noometry.com/best/knowledge) | 37.7 | #152 | 2 |
| [Multilingual](https://noometry.com/best/multilingual) | 50.3 | #123 | 1 |
| [Instruction Following](https://noometry.com/best/instruction-following) | 74.1 | #103 | 1 |
| [Long Context](https://noometry.com/best/long-context) | 43.3 | #99 | 1 |
| [Writing & Preference](https://noometry.com/best/writing) | 58.9 | #112 | 3 |

## Strengths and weaknesses

Categories where MiniMax-M2.7 places highest and lowest among the models ranked in each, with its score against that category's median.

### Strongest categories

MiniMax-M2.7: strongest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Long Context](https://noometry.com/best/long-context) | 43.3 | +2.4 | #99 of 296, top 34% |
| [Instruction Following](https://noometry.com/best/instruction-following) | 74.1 | +2.8 | #103 of 305, top 34% |
| [Coding](https://noometry.com/best/coding) | 41.8 | +3.0 | #120 of 340, top 36% |

### Weakest categories

MiniMax-M2.7: weakest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Math](https://noometry.com/best/math) | 25.9 | −10.6 | #263 of 327, top 81% |
| [Reasoning](https://noometry.com/best/reasoning) | 19.7 | −3.9 | #253 of 350, top 73% |
| [Agentic & Tool Use](https://noometry.com/best/agentic) | 25.1 | −5.3 | #111 of 154, top 73% |

## Closest competitors

The models ranked just above and below MiniMax-M2.7. When scores are this close, price and speed are often the better way to choose.

Models ranked closest to MiniMax-M2.7
| Model | Rank | Score | Blended $/M | Speed |  |
| --- | --- | --- | --- | --- | --- |
| [GPT-5-Codex](https://noometry.com/models/gpt-5-codex) | #192 | 37.9 | $3.44 | 95 | [Compare](https://noometry.com/compare/gpt-5-codex-vs-minimax-m2-7) |
| [Hunyuan Standard 2025 02 10](https://noometry.com/models/hunyuan-standard) | #193 | 37.9 | — | — | [Compare](https://noometry.com/compare/hunyuan-standard-vs-minimax-m2-7) |
| [Gemini 2.0 Flash-Lite](https://noometry.com/models/gemini-2-0-flash-lite) | #194 | 37.8 | — | — | [Compare](https://noometry.com/compare/gemini-2-0-flash-lite-vs-minimax-m2-7) |
| [DeepSeek-R1-Distill-Llama-70B](https://noometry.com/models/deepseek-r1-distill-llama-70b) | #195 | 37.8 | — | 18 | [Compare](https://noometry.com/compare/deepseek-r1-distill-llama-70b-vs-minimax-m2-7) |
| [Gemini Advanced 0514](https://noometry.com/models/gemini-advanced) | #197 | 37.7 | — | — | [Compare](https://noometry.com/compare/gemini-advanced-vs-minimax-m2-7) |
| [Grok 2 Mini 2024 08 13](https://noometry.com/models/grok-2-mini) | #198 | 37.7 | — | — | [Compare](https://noometry.com/compare/grok-2-mini-vs-minimax-m2-7) |
| [Mercury](https://noometry.com/models/mercury) | #199 | 37.6 | — | 35 | [Compare](https://noometry.com/compare/mercury-vs-minimax-m2-7) |
| [DeepSeek-V2.5 (Sep 2024)](https://noometry.com/models/deepseek-v2-5) | #200 | 37.6 | — | — | [Compare](https://noometry.com/compare/deepseek-v2-5-vs-minimax-m2-7) |

Sponsored placements are available on pages like this one. [Advertise on Noometry](https://noometry.com/advertise)

## Benchmark results

Every published result we track, with its source. Bold rows are the ones used for ranking; where several exist we prefer independent runs over self-reported numbers.

### Coding

MiniMax-M2.7 Coding benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena WebDev](https://noometry.com/benchmarks/arena-webdev) | 1398 | #73 of 113, top 65% |  | [LMArena](https://lmarena.ai/leaderboard/webdev) | 2026-10-08 |
| [SciCode](https://noometry.com/benchmarks/scicode) | 47% | #54 of 121, top 45% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [WeirdML](https://noometry.com/benchmarks/weirdml) | 37% | #88 of 119, top 74% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Coding](https://noometry.com/benchmarks/arena-coding) | 1454 | #78 of 294, top 27% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [ALE-Bench](https://noometry.com/benchmarks/ale-bench) | 599.25 | #80 of 105, top 77% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Agentic & Tool Use

MiniMax-M2.7 Agentic & Tool Use benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [Terminal-Bench](https://noometry.com/benchmarks/terminal-bench) | 45.1% | #20 of 41, top 49% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ExploitBench](https://noometry.com/benchmarks/exploitbench) | 13.3% | #9 of 9, top 100% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [GBAEval](https://noometry.com/benchmarks/gbaeval) | 0% | #23 of 23, top 100% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Reasoning

MiniMax-M2.7 Reasoning benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [NYT Connections (extended)](https://noometry.com/benchmarks/nyt-connections) | 24.7% | #77 of 91, top 85% |  | [Lech Mazur benchmarks](https://github.com/lechmazur/nyt-connections) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 0.6% | #89 of 134, top 67% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Thematic Generalization](https://noometry.com/benchmarks/thematic-generalization) | 39.3% | #21 of 23, top 92% |  | [Lech Mazur benchmarks](https://github.com/lechmazur/generalization) |  |
| [LMArena Hard Prompts](https://noometry.com/benchmarks/arena-hard-prompts) | 1422 | #101 of 297, top 35% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [Epoch Capabilities Index](https://noometry.com/benchmarks/epoch-capabilities-index) | 145.85 | #77 of 213, top 37% |  | [Epoch AI](https://epoch.ai/eci) | 2026-03-18 |

### Math

MiniMax-M2.7 Math benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [ProofBench](https://noometry.com/benchmarks/proofbench) | 3% | #73 of 77, top 95% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Math](https://noometry.com/benchmarks/arena-math) | 1420 | #100 of 285, top 36% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Knowledge

MiniMax-M2.7 Knowledge benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [Vectara Hallucination Rate](https://noometry.com/benchmarks/vectara-hallucination) (lower is better) | 12.9% | #80 of 96, top 84% |  | [Vectara Hallucination Leaderboard](https://github.com/vectara/hallucination-leaderboard) |  |
| [LMArena Expert](https://noometry.com/benchmarks/arena-expert) | 1444 | #78 of 273, top 29% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Multilingual

MiniMax-M2.7 Multilingual benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Non-English](https://noometry.com/benchmarks/arena-non-english) | 1382 | #123 of 297, top 42% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Chinese](https://noometry.com/benchmarks/arena-chinese) | 1441 | #112 of 285, top 40% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena French](https://noometry.com/benchmarks/arena-french) | 1421 | #99 of 223, top 45% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena German](https://noometry.com/benchmarks/arena-german) | 1398 | #95 of 231, top 42% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Japanese](https://noometry.com/benchmarks/arena-japanese) | 1262 | #136 of 211, top 65% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Korean](https://noometry.com/benchmarks/arena-korean) | 1313 | #122 of 213, top 58% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Russian](https://noometry.com/benchmarks/arena-russian) | 1383 | #127 of 283, top 45% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Spanish](https://noometry.com/benchmarks/arena-spanish) | 1403 | #108 of 226, top 48% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Instruction Following

MiniMax-M2.7 Instruction Following benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Instruction Following](https://noometry.com/benchmarks/arena-instruction-following) | 1405 | #96 of 298, top 33% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Long Context

MiniMax-M2.7 Long Context benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Longer Query](https://noometry.com/benchmarks/arena-longer-query) | 1419 | #94 of 291, top 33% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Writing & Preference

MiniMax-M2.7 Writing & Preference benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Text](https://noometry.com/benchmarks/arena-text) | 1405 | #116 of 297, top 40% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Creative Writing](https://noometry.com/benchmarks/arena-creative-writing) | 1354 | #126 of 295, top 43% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Multi-Turn](https://noometry.com/benchmarks/arena-multi-turn) | 1412 | #106 of 295, top 36% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

## API pricing by provider

MiniMax-M2.7 API prices
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
| --- | --- | --- | --- | --- |
| [deepinfra](https://deepinfra.com/models) | $0.25 | $1 | $0.05 | 2026-10-10 |
| [minimax](https://platform.minimax.io/docs/guides/quickstart) | $0.30 | $1.20 | $0.06 | 2026-10-10 |
| [openrouter](https://openrouter.ai/minimax/minimax-m2.7) | $0.21 | $0.84 | $0.042 | 2026-10-10 |
| [together](https://docs.together.ai/docs/serverless-models) | $0.30 | $1.20 | $0.06 | 2026-10-10 |

[All MiniMax API prices →](https://noometry.com/llm-pricing/minimax) [Estimate your cost →](https://noometry.com/tools/cost-calculator)

## Compare MiniMax-M2.7

-   [MiniMax-M2.7 vs MiniMax-M2.5](https://noometry.com/compare/minimax-m2-5-vs-minimax-m2-7)
-   [MiniMax-M2.7 vs DeepSeek-R1-Distill-Llama-70B](https://noometry.com/compare/deepseek-r1-distill-llama-70b-vs-minimax-m2-7)
-   [MiniMax-M2.7 vs Gemini Advanced 0514](https://noometry.com/compare/gemini-advanced-vs-minimax-m2-7)
-   [MiniMax-M2.7 vs Gemini 2.0 Flash-Lite](https://noometry.com/compare/gemini-2-0-flash-lite-vs-minimax-m2-7)
-   [MiniMax-M2.7 vs Grok 2 Mini 2024 08 13](https://noometry.com/compare/grok-2-mini-vs-minimax-m2-7)
-   [MiniMax-M2.7 vs Hunyuan Standard 2025 02 10](https://noometry.com/compare/hunyuan-standard-vs-minimax-m2-7)
-   [MiniMax-M2.7 vs Mercury](https://noometry.com/compare/mercury-vs-minimax-m2-7)
-   [MiniMax-M2.7 vs GPT-6 Astra](https://noometry.com/compare/gpt-6-astra-vs-minimax-m2-7)
-   [MiniMax-M2.7 vs Claude Fable 5.1](https://noometry.com/compare/claude-fable-5-1-vs-minimax-m2-7)
-   [MiniMax-M2.7 vs Gemini 3.8 Flash](https://noometry.com/compare/gemini-3-8-flash-vs-minimax-m2-7)
-   [MiniMax-M2.7 vs Kimi K3](https://noometry.com/compare/kimi-k3-vs-minimax-m2-7)
-   [MiniMax-M2.7 vs Grok 4.6](https://noometry.com/compare/grok-4-6-vs-minimax-m2-7)
-   [MiniMax-M2.7 vs Qwen3.8 Max](https://noometry.com/compare/minimax-m2-7-vs-qwen3-8-max)
-   [MiniMax-M2.7 vs GLM-5.3](https://noometry.com/compare/glm-5-3-vs-minimax-m2-7)

## Other MiniMax models

-   [MiniMax-M3](https://noometry.com/models/minimax-m3)43.8
-   [MiniMax M1](https://noometry.com/models/minimax-m1)40.3
-   [MiniMax-M2.1](https://noometry.com/models/minimax-m2-1)38.9
-   [MiniMax-M2.5](https://noometry.com/models/minimax-m2-5)38.3
-   [MiniMax-M2](https://noometry.com/models/minimax-m2)37.4
-   [MiniMax-01](https://noometry.com/models/minimax-01)
-   [MiniMax-M2.5-highspeed](https://noometry.com/models/minimax-m2-5-highspeed)
-   [MiniMax-M2.7-highspeed](https://noometry.com/models/minimax-m2-7-highspeed)

## Frequently asked questions

### How good is MiniMax-M2.7?

MiniMax-M2.7 by MiniMax ranks 196th of 354 ranked models on the Noometry Index as of October 2026, with a score of 37.7. Its strongest category is long context, where it ranks 99th. API pricing starts at $0.30 per million input tokens and $1.20 per million output tokens, with a 205K-token context window.

### How much does MiniMax-M2.7 cost?

MiniMax-M2.7 costs $0.30 per million input tokens and $1.20 per million output tokens on MiniMax's own API, with cached input at $0.06.

### What is MiniMax-M2.7's context window?

MiniMax-M2.7 accepts up to 205K tokens of input and can write up to 131K tokens in one response.

### Is MiniMax-M2.7 open source?

Yes. MiniMax-M2.7's weights are downloadable from Hugging Face (MiniMaxAI/MiniMax-M2.7); check the license for commercial terms.

### What are MiniMax-M2.7's strengths and weaknesses?

Relative to other ranked models, MiniMax-M2.7 places best in long context, instruction following, coding and lowest in math, reasoning, agentic & tool use.

### What is MiniMax-M2.7 best at?

Its best category is long context, where it ranks 99th on Noometry.

### Cite this page

Noometry. (2026). MiniMax-M2.7 benchmarks and pricing. Retrieved October 10, 2026, from https://noometry.com/models/minimax-m2-7

Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/models/minimax-m2-7.md).