Model profile
MiniMax M2.7
Evidence coverage
35 of 323 tracked benchmarks are published. 14 are verified and 21 provisional. 7 of 8 categories are measured.
- Published / tracked
- 35 / 323
- Verified
- 14
- Provisional
- 21
- Categories with evidence
- 7 / 8
Evidence by category
- Agentic11 benchmarksMixed evidence
- Coding11 benchmarksMixed evidence
- Reasoning2 benchmarksReported
- Knowledge8 benchmarksReported
- Math1 benchmarkReported
- Multilingual0 benchmarksNot measured
- Multimodal1 benchmarkReported
- Inst. Following1 benchmarkReported
MiniMax M2.7 ranks #36 out of 200 models on the public leaderboard with an overall score of 64.11/100. It also ranks #29 out of 99 on the verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.
MiniMax M2.7 is a open weight model with a 200K token context window. It processes queries without explicit chain-of-thought reasoning, offering faster response times and lower token usage.
BenchLM links it directly to MiniMax M2.5 as the earlier related model in that lineage. This profile currently has 35 of 323 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.
Its strongest category is Coding (#78), while its weakest is Agentic (#109). This performance profile makes it particularly well-suited for software development and code generation tasks.
Peer position
Exact provisional scores and ranks for the closest listed peers. A score can appear before a model clears the evidence threshold for a rank, so equal scores can have different rank states.
Range 63.5–64.75
- Gemini 3.5 FlashGoogleCompare#3364.75Gemini 3.5 Flash is #33 with a score of 64.75.
- Claude Opus 4.5AnthropicCompare#3464.22Claude Opus 4.5 is #34 with a score of 64.22.
- Claude Opus 4.6 (Adaptive)AnthropicCompare#3564.18Claude Opus 4.6 (Adaptive) is #35 with a score of 64.18.
- MiniMax M2.7Current modelMiniMax#3664.11MiniMax M2.7 is #36 with a score of 64.11.
- GLM-5.2Z.AICompare#3763.96GLM-5.2 is #37 with a score of 63.96.
- GPT-5.5 ProOpenAICompare#3863.69GPT-5.5 Pro is #38 with a score of 63.69.
- GLM-5V-TurboZ.AICompare#3963.5GLM-5V-Turbo is #39 with a score of 63.5.
Category percentile
More
Relative position among models eligible for each sourced category. A higher percentile means a stronger position within that category's ranked cohort; 100 is highest.
- Coding36%Eligible cohort rank #78 of 122Category score 47.6
- Agentic8%Eligible cohort rank #109 of 119Category score 34.8
Category evidence
Scores and ranks appear only where this model has published benchmark evidence. Categories without displayable source records remain not measured.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #109 of 119Percentile 8thWeight 22%11 benchmarksMixed sources | 34.8 | #109 of 119 | 8th | 22% | 11 benchmarks | Mixed sources |
| CodingRank #78 of 122Percentile 36thWeight 20%11 benchmarksMixed sources | 47.6 | #78 of 122 | 36th | 20% | 11 benchmarks | Mixed sources |
| ReasoningWeight 17%2 benchmarksReported | Score pending | Not ranked | Not available | 17% | 2 benchmarks | Reported |
| KnowledgeRank Not rankedWeight 12%8 benchmarksReported | 28.0 | Not ranked | Not available | 12% | 8 benchmarks | Reported |
| MathRank Not rankedWeight 5%1 benchmarkReported | 81.3 | Not ranked | Not available | 5% | 1 benchmark | Reported |
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | Not ranked | Not available | 7% | 0 benchmarks | Not measured |
| MultimodalWeight 12%1 benchmarkReported | Score pending | Not ranked | Not available | 12% | 1 benchmark | Reported |
| Inst. FollowingRank Not rankedWeight 5%1 benchmarkReported | 75.7 | Not ranked | Not available | 5% | 1 benchmark | Reported |
Chatbot Arena performance
Scroll horizontally to inspect confidence intervals and vote counts.
| View | Elo | Confidence interval | Votes |
|---|---|---|---|
| Text Overall | 1418 | ±4.2 | 49,135 |
| Coding | 1480 | ±6.3 | 14,249 |
| Math | 1424 | ±12.1 | 2,601 |
| Instruction Following | 1410 | ±6.0 | 15,705 |
| Creative Writing | 1365 | ±8.0 | 7,485 |
| Multi-turn | 1428 | ±7.5 | 8,762 |
| Hard Prompts | 1444 | ±5.0 | 31,808 |
| Hard Prompts (English) | 1460 | ±6.2 | 15,078 |
| Longer Query | 1435 | ±5.9 | 19,813 |
Benchmark Details
Rows below have a displayable published verification record. Each source link and provenance note remains in the page HTML while its category is closed. Source-unverified manual rows and generated rows stay hidden.
Agentic11 benchmarks
τ²-Bench Tool-Agent-User Evaluation
Artificial Analysis Agentic Index
GDPval-AA normalized
Gert Labs Composite Game Benchmark
Coding11 benchmarks
SWE-bench Verified (mini-swe-agent-v2)
Vibe Code Bench v1.1
Artificial Analysis Coding Index
Artificial Analysis SciCode
Reasoning2 benchmarks
Artificial Analysis Long Context Reasoning
Critical Physics Tasks
Knowledge8 benchmarks
GPQA Diamond
MMLU-Pro first-party comparison snapshot
Artificial Analysis GPQA Diamond
Artificial Analysis Humanity's Last Exam
Artificial Analysis Omniscience Index
Artificial Analysis Omniscience Accuracy
Artificial Analysis Omniscience Hallucination Rate
Math1 benchmark
AIME25 first-party comparison snapshot
Multimodal1 benchmark
Design Arena Website Elo
Inst. Following1 benchmark
Artificial Analysis IFBench
Frequently Asked Questions
How does MiniMax M2.7 perform overall in AI benchmarks?
MiniMax M2.7 has 35 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.
Is MiniMax M2.7 good for knowledge and understanding?
MiniMax M2.7 has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.
Is MiniMax M2.7 good for coding and programming?
MiniMax M2.7 ranks #78 out of 122 models in coding and programming benchmarks with an average score of 47.6. There are stronger options in this category.
Is MiniMax M2.7 good for mathematics?
MiniMax M2.7 has visible benchmark coverage in mathematics, but BenchLM does not currently assign it a global category rank there.
Is MiniMax M2.7 good for reasoning and logic?
MiniMax M2.7 has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.
Is MiniMax M2.7 good for agentic tool use and computer tasks?
MiniMax M2.7 ranks #109 out of 119 models in agentic tool use and computer tasks benchmarks with an average score of 34.8. There are stronger options in this category.
Is MiniMax M2.7 good for multimodal and grounded tasks?
MiniMax M2.7 has visible benchmark coverage in multimodal and grounded tasks, but BenchLM does not currently assign it a global category rank there.
Is MiniMax M2.7 good for instruction following?
MiniMax M2.7 has visible benchmark coverage in instruction following, but BenchLM does not currently assign it a global category rank there.
Is MiniMax M2.7 open source?
Yes, MiniMax M2.7 is an open weight model created by MiniMax, meaning it can be downloaded and run locally or fine-tuned for specific use cases.
Does MiniMax M2.7 have full benchmark coverage on BenchLM?
Not yet. MiniMax M2.7 currently has 35 published benchmark scores out of the 323 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.
What is the context window size of MiniMax M2.7?
MiniMax M2.7 has a published context window of 200K, which determines how much text it can process in a single interaction.
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