MiniMax model product
MiniMax M2.7
7 features model self-improvement driving productivity innovation.
Updated Aug 12, 2026. Default version: MiniMax M2.7
LLMBoard score58.4MiniMax M2.7
Coverage20%8 benchmark families
Context window204.8KTokens
Official input price$0.30MiniMax (minimax.io) API
MiniMax M2.7 Specifications
Technical details for the model's default version.
- Version
- MiniMax M2.7
- Released
- Mar 18, 2026
- Knowledge cutoff
- Unknown
- Parameters
- N/A
- Context window
- 204.8K
- Max output
- 131.1K
- Inputs
- text
- Outputs
- text
- Open weights
- Yes
- License
- MIT
MiniMax M2.7 Capability Profile
This profile uses the model's current scored version. Arena ratings and prices are shown separately.
MiniMax M2.7 Benchmark Results
Benchmark scores for MiniMax M2.7.
| MLE-Bench Lite | 66.6% | 01 | 1 | 100.0% | C | |
| MM-ClawBench | 62.7% | 01 | 1 | 100.0% | C | |
| Multi-SWE-Bench | 52.7% | 01 | 6 | 100.0% | C | |
| VIBE-Pro | 55.6% | 01 | 2 | 100.0% | C | |
| Artificial Analysis | 50.0% | 05 | 5 | 0.0% | C | |
| SWE-bench Multilingual | 76.5% | 07 | 34 | 81.8% | C | |
| NL2Repo | 39.8% | 11 | 14 | 23.1% | C | |
| Toolathlon | 46.3% | 21 | 31 | 33.3% | C | |
| Finance Agent v2 | 27.9% | 26 | 26 | 0.0% | B | |
| Terminal-Bench 2.0 | 57.0% | 26 | 49 | 47.9% | C | |
| SWE-Bench Pro | 56.2% | 28 | 45 | 38.6% | C |
MiniMax M2.7 Arena Results
Preference and agent-evaluation results for the default version.
| agent tool hallucination | overall | 24 | 0.0 | N/A | 537.1K | |
| agent bash recovery steps | overall | 41 | -0.2 | N/A | 20.6K | |
| agent | overall | 43 | -0.1 | N/A | 590.4K | |
| agent praise complaint | overall | 44 | -0.2 | N/A | 4K | |
| agent task outcome explicit | overall | 44 | -0.1 | N/A | 12.7K | |
| agent steerability | overall | 45 | -0.1 | N/A | 16K | |
| webdev | overall | 61 | 1398.0 | 13,296 | N/A | |
| text factuality | overall | 107 | 1421.9 | 57,740 | N/A | |
| text style control | overall | 116 | 1416.1 | 57,838 | N/A | |
| text | overall | 126 | 1405.0 | 57,838 | N/A |
MiniMax M2.7 Runtime Performance
Provider-specific output speed and catalog latency for MiniMax M2.7. Runtime does not affect the capability score.
| Fireworks | 560.077 tok/s | 0.437 s | 196.6K | 196.6K | |
| Novita | 206.764 tok/s | 1.34 s | 204.8K | 131.1K |
Output Speed is generated output tokens received per second. Catalog latency is reported separately from observed provider TTFT.
MiniMax M2.7 Pricing
Official vendor API pricing appears first, followed by individual provider offers.
- Official API
- $0.30 input, $1.2 output per 1M
- Official provider
- MiniMax (minimax.io)
- Lowest third-party
- From $0.08 input, $0.32 output per 1M via LLM Gateway
- Tracked offerings
- 50
| Nvidia | minimaxai/minimax-m2.7 | global | N/A | N/A | 204.8K | |
| UnoRouter | minimax-m2.7:free | global | N/A | N/A | 204.8K | |
| MiniMax Token Plan (minimax.io) | MiniMax-M2.7 | global | N/A | N/A | 204.8K | |
| MiniMax Token Plan (minimax.io) | MiniMax-M2.7-highspeed | global | N/A | N/A | 204.8K | |
| MiniMax Token Plan (minimaxi.com) | MiniMax-M2.7 | global | N/A | N/A | 204.8K | |
| MiniMax Token Plan (minimaxi.com) | MiniMax-M2.7-highspeed | global | N/A | N/A | 204.8K | |
| LLM Gateway | minimax-m2.7 | global | $0.08 | $0.32 | 204.8K | |
| EmpirioLabs AI | minimax-m2-7 | global | $0.15 | $0.60 | 200K | |
| Deep Infra | MiniMaxAI/MiniMax-M2.7 | global | $0.25 | $1 | 196.6K | |
| Pioneer | MiniMaxAI/MiniMax-M2.7 | global | $0.279 | $1.2 | 204.8K | |
| Fireworks AI | accounts/fireworks/models/minimax-m2p7 | global | $0.30 | $1.2 | 196.6K | |
| OpenCode Go | minimax-m2.7 | global | $0.30 | $1.2 | 204.8K | |
| FastRouter | minimax/minimax-m2.7 | global | $0.30 | $1.2 | 204.8K | |
| OpenCode Zen | minimax-m2.7 | global | $0.30 | $1.2 | 204.8K | |
| 302.AI | MiniMax-M2.7 | global | $0.30 | $1.2 | 204.8K | |
| FrogBot | minimax-m2-7 | global | $0.30 | $1.2 | 192K | |
| Abacus | MiniMaxAI/MiniMax-M2.7 | global | $0.30 | $1.2 | 204.8K | |
| EmpirioLabs AI | minimax-m2-7-highspeed | global | $0.30 | $1.2 | 200K | |
| Together AI | MiniMaxAI/MiniMax-M2.7 | global | $0.30 | $1.2 | 202.8K | |
| Auriko | minimax-m2-7 | global | $0.30 | $1.2 | 204.8K | |
| Vultr | MiniMaxAI/MiniMax-M2.7 | global | $0.30 | $1.2 | 204.8K | |
| AIHubMix | minimax-m2.7 | global | $0.30 | $1.2 | 204.8K | |
| OrcaRouter | minimax/minimax-m2.7 | global | $0.30 | $1.2 | 204.8K | |
| MiniMax (minimax.io) | MiniMax-M2.7 | global | $0.30 | $1.2 | 204.8K | |
| Kilo Gateway | minimax/minimax-m2.7 | global | $0.30 | $1.2 | 204.8K | |
| Merge Gateway | minimax/minimax-m2.7 | global | $0.30 | $1.2 | 204.8K | |
| Vercel AI Gateway | minimax/minimax-m2.7 | global | $0.30 | $1.2 | 204.8K | |
| Alibaba (China) | MiniMax/MiniMax-M2.7 | global | $0.30 | $1.2 | 204.8K | |
| NovitaAI | minimax/minimax-m2.7 | global | $0.30 | $1.2 | 204.8K | |
| OpenRouter | minimax/minimax-m2.7 | global | $0.30 | $1.2 | 204.8K | |
| Hugging Face | MiniMaxAI/MiniMax-M2.7 | global | $0.30 | $1.2 | 204.8K | |
| MiniMax (minimaxi.com) | MiniMax-M2.7 | global | $0.30 | $1.2 | 204.8K | |
| ZenMux | minimax/minimax-m2.7 | global | $0.3055 | $1.22 | 204.8K | |
| NanoGPT | minimax/minimax-m2.7 | global | $0.315 | $1.26 | 204.8K | |
| CrossModel | minimax/minimax-m2.7 | global | $0.33 | $1.32 | 204.8K | |
| Venice AI | minimax-m27 | global | $0.375 | $1.5 | 198K | |
| SCX.ai | MiniMax-M2.7 | global | $0.48 | $1.79 | 192K | |
| Charm Hyper | minimax-m2.7 | global | $0.48 | $1.8 | 262.1K | |
| FastRouter | minimax/minimax-m2.7-highspeed | global | $0.60 | $2.4 | 204.8K | |
| LLM Gateway | minimax-m2.7-highspeed | global | $0.60 | $2.4 | 204.8K | |
| Auriko | minimax-m2-7-highspeed | global | $0.60 | $2.4 | 204.8K | |
| OrcaRouter | minimax/minimax-m2.7-highspeed | global | $0.60 | $2.4 | 204.8K | |
| MiniMax (minimax.io) | MiniMax-M2.7-highspeed | global | $0.60 | $2.4 | 204.8K | |
| Merge Gateway | minimax/minimax-m2.7-highspeed | global | $0.60 | $2.4 | 204.8K | |
| Vercel AI Gateway | minimax/minimax-m2.7-highspeed | global | $0.60 | $2.4 | 204.8K | |
| NovitaAI | minimax/minimax-m2.7-highspeed | global | $0.60 | $2.4 | 204.8K | |
| MiniMax (minimaxi.com) | MiniMax-M2.7-highspeed | global | $0.60 | $2.4 | 204.8K | |
| Cortecs | minimax-m2.7 | global | $0.668 | $2.67 | 196.6K | |
| UnoRouter | minimax-m2.7 | global | $0.819 | $3.28 | 204.8K |
Official prices use only the vendor's configured official Provider and positive standard USD PAYG rates. Third-party offers remain explicitly labeled.
MiniMax M2.7 Versions
Available versions of this model. The score column identifies the version used in the overall ranking.
| MiniMax M2.7 | 58.4 | N/A | 204.8K | 131.1K | Yes | MIT |
What is MiniMax M2.7?
Key information about MiniMax M2.7 and its available data.
7 features model self-improvement driving productivity innovation. It builds complex agent harnesses independently to accomplish highly complex productivity tasks. 7 demonstrates excellent performance in real-world software engineering including end-to-end project delivery, log analysis, code security, and ML tasks.
22%, nearly matching Opus. It excels in professional office domains achieving the highest ELO among open-source models on GDPval-AA (1495), with significant improvement in complex editing for Office Suite. 7 maintains 97% skill adherence on 40 complex skills cases.
Data as of 2026-08-11.
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FAQ
Common questions about MiniMax M2.7.
When was MiniMax M2.7 released?
MiniMax M2.7's default version was released on Mar 18, 2026.
How much does MiniMax M2.7 cost?
MiniMax M2.7's official API price is $0.30 per million input tokens and $1.2 per million output tokens via MiniMax (minimax.io). The lowest tracked third-party offer starts at $0.08 input and $0.32 output via LLM Gateway.
Who created MiniMax M2.7?
MiniMax M2.7 was created by MiniMax.
What is the context window for MiniMax M2.7?
The default version has a 204.8K token context window.
Is MiniMax M2.7 open weight?
Yes. The default version is marked as open weight under MIT.
How many API providers offer MiniMax M2.7?
50 provider offerings are linked to the default version.
What models should I compare MiniMax M2.7 with?
Nearby ranked alternatives include GPT-5.2-Codex, ERNIE 5.0, Muse Glimmer 30B.