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MiniMax: MiniMax: MiniMax M2.7 (free)

MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent...

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InputT
OutputT
Input priceFree
Output priceFree
Context196.608K
Max output176.947K
Providers0
Inference availability

Providers

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Specification

Capabilities

Recorded from the source catalog and provider listings.

? Reasoning Unknown
? Tool calling Unknown
? Structured output Unknown
? Attachments Unknown
× Vision input No
? Open weights Unknown
Creator
MiniMax
Model family
Not documented
Knowledge cutoff
Not documented
License
Not documented
Release date
Not documented
Model ID
minimax/minimax-m2.7:free
Published evaluations

Benchmarks

Every result stays attached to its source, version, metric and harness. Scores from different versions are never merged, and the profile below plots each benchmark against its own population rather than on a shared scale.

Benchmark registry
Benchmark profile
Coding IndexCoding Index Agentic IndexAgentic Index IntelligenceIntelligence Index Design Arena: w…Design Arena: website Design Arena: c…Design Arena: codecategories Design Arena: g…Design Arena: gamedev Design Arena: d…Design Arena: dataviz Design Arena: u…Design Arena: uicomponent This model — Coding Index: 52.6 index (58.0th percentile) This model — Agentic Index: 25.9 index (61.9th percentile) This model — Intelligence Index: 38.9 index (76.3th percentile) This model — Design Arena: website: 1260 elo (67.4th percentile) This model — Design Arena: codecategories: 1252 elo (64.4th percentile) This model — Design Arena: gamedev: 1234 elo (62.3th percentile) This model — Design Arena: dataviz: 1251 elo (69.1th percentile) This model — Design Arena: uicomponent: 1232 elo (56.8th percentile)

Each axis is this model's percentile among the 8 benchmarks it has published results for, measured against every other model with a score on that same benchmark. Percentiles are used because benchmarks do not share a scale — a 60 on one is not a 60 on another. Hover any point for the raw score.

Coding Index index Source ↗
Coding Index #86 of 205
Agentic Index index Source ↗
Agentic Index #74 of 193
Intelligence Index index Source ↗
Intelligence Index #46 of 192
Design Arena: website elo Source ↗
Design Arena: website #57 of 175
Design Arena: codecategories elo Source ↗
Design Arena: codecategories #60 of 167
Design Arena: gamedev elo Source ↗
Design Arena: gamedev #62 of 166
Design Arena: dataviz elo Source ↗
Design Arena: dataviz #51 of 165
Design Arena: uicomponent elo Source ↗
Design Arena: uicomponent #70 of 161
Design Arena: 3d elo Source ↗
Design Arena: 3d #67 of 157
Design Arena: svg elo Source ↗
Design Arena: svg #73 of 116
Design Arena: asciiart elo Source ↗
Design Arena: asciiart #63 of 99

Each strip shows every published score for that benchmark, with this model marked. The lighter shape behind the ticks is the density of results, and the dashed line is the median.

Cost against capability

Price and performance

Listed input price plotted against Coding Index, the benchmark with the widest published coverage that this model appears in.

0 43 86 $0.01 $0.1 $1 $10 Anthropic: Claude Fable 5.1 (batch) — $5/M, score 81.6 Z.ai: GLM 5.3 Flash (batch) — $0.075/M, score 71.5 Nemotron 3.5 Lightning 30B A3B — $0.05/M, score 26.8 Kimi K3 — $3/M, score 76.2 Google: Gemini 3.6 Flash (batch) — $0.375/M, score 69.2 Muse Spark 1.2 — $1.25/M, score 72.2 Thinking Machines: Inkling (batch) — $1/M, score 52.1 MiniMax: MiniMax M3 (batch) — $0.3/M, score 58.6 Gemini 3.5 Flash — $1.5/M, score 70.1 Kimi K2.6 — $0.95/M, score 61.8 Anthropic: Claude Opus 4.7 (batch) — $2.5/M, score 73.6 OpenAI: GPT-5.4 (batch) — $1.25/M, score 71.1 GPT-5.1 — $1.25/M, score 49.4 Anthropic: Claude Sonnet 4.5 — $3/M, score 52.1 DeepSeek: DeepSeek V3.1 Terminus — $0.27/M, score 43.5 GPT OSS 120B — $0.03/M, score 30.4 GPT-4o mini — $0.15/M, score 11.4 OpenAI: GPT-4 Turbo (batch) — $5/M, score 21.5 OpenAI: GPT-3.5 Turbo (batch) — $0.25/M, score 10.7 OpenAI: o3 Mini High (batch) — $0.55/M, score 16.3 SpaceXAI: Grok 4.5 — $2/M, score 72.4 Anthropic: Claude Sonnet 5 (batch) — $1/M, score 71.5 Anthropic: Claude Opus 4.8 — $5/M, score 74.3 Qwen: Qwen3.8 Max (0902) — $2/M, score 71.8 Gemma 3 4B IT — $0.04/M, score 2.7 Nemotron 3 Super 120B A12B — $0.2/M, score 37.7 Claude Fable 5 — $10/M, score 76.5 Gemma 3 27B IT — $0.08/M, score 10.1 DeepSeek V4 Flash 0731 — $0.05/M, score 69.1 DeepSeek-R1 — $0.7/M, score 24.6 OpenAI: o1 (batch) — $7.5/M, score 39.7 GPT-4 Turbo — $10/M, score 21.5 GPT-3.5-turbo — $0.5/M, score 10.7 GPT-4 — $30/M, score 13.1 Kimi K2.7 Code — $0.95/M, score 60.8 LongCat-2.0 — $0.3/M, score 45.3 Nemotron 3 Ultra 550B A55B — $0.5/M, score 49.3 Claude Sonnet 5 — $2/M, score 71.5 Google: Gemini 3.5 Flash (batch) — $0.75/M, score 70.1 OpenAI: GPT-5.4 Nano (batch) — $0.1/M, score 56.1 Mistral: Ministral 3 8B 2512 — $0.15/M, score 9.7 Qwen: Qwen3.5-9B (batch) — $0.17/M, score 28.7 OpenAI: GPT-5.1 (batch) — $0.625/M, score 49.4 DeepSeek V4 Pro — $0.435/M, score 59.4 GPT-5.4 — $2.5/M, score 71.1 Gemini 3.6 Flash — $0.75/M, score 69.2 Nemotron 3 Nano 30B A3B — $0.05/M, score 14.4 OpenAI: GPT-4.1 Nano (batch) — $0.05/M, score 11.1 Gemma 4 26B A4B IT — $0.042/M, score 39.3 Anthropic: Claude Opus 4.8 (batch) — $2.5/M, score 74.3 Z.ai: GLM 5.1 — $0.966/M, score 55.8 Anthropic: Claude Opus 4.7 — $5/M, score 73.6 Qwen: Qwen3.6 Plus — $0.325/M, score 54.5 MiniMax: MiniMax M3 — $0.3/M, score 58.6 DeepSeek: DeepSeek V4 Pro 0813 (batch) — $0.66/M, score 68.8 Thinking Machines: Inkling Small (batch) — $0.5/M, score 52.9 GPT-4.1 nano — $0.1/M, score 11.1 Gemma 4 31B IT — $0.09/M, score 43.4 Google: Gemini 3.1 Pro Preview (batch) — $1/M, score 68.8 Claude Opus 5 — $5/M, score 78.0 Anthropic: Claude Fable 5.1 — $10/M, score 81.6 Google: Gemma 4 31B (batch) — $0.39/M, score 43.4 Qwen: Qwen3.8 2.4T A95B (batch) — $2/M, score 71.9 Mistral: Devstral 2 2512 — $0.4/M, score 31.3 MoonshotAI: Kimi K2.7 Code (batch) — $0.95/M, score 60.8 Inkling — $1.87/M, score 52.1 GPT-4.1 mini — $0.4/M, score 20.2 OpenAI: gpt-oss-20b (batch) — $0.05/M, score 20.7 MiMo-V2.5 — $0.14/M, score 56.8 Google: Gemini 3.5 Flash Lite (batch) — $0.15/M, score 49.3 Kimi K2 Thinking — $0.4/M, score 21.0 Mistral: Mistral Medium 3.5 (batch) — $0.75/M, score 46.9 Qwen: Qwen3.8 Max (0803) — $2/M, score 68.9 Mistral: Mistral Medium 3.1 (batch) — $0.2/M, score 20.5 OpenAI: GPT-5.6 Terra (batch) — $1/M, score 76.7 Qwen: Qwen3.8 27B — $0.42/M, score 68.1 Google: Gemini 3.8 Flash (batch) — $0.375/M, score 76.3 MiniMax: MiniMax M2.7 — $0.3/M, score 52.6 GPT OSS 20B — $0.02/M, score 20.7 inclusionAI: Ling 3.0 Flash VL — $0.06/M, score 57.0 Z.ai: GLM 5.3 (batch) — $0.7/M, score 74.8 DeepSeek: DeepSeek V4 Flash 0731 (batch) — $0.11/M, score 69.1 MoonshotAI: Kimi K3 (batch) — $3/M, score 76.2 GPT-5.4 nano — $0.2/M, score 56.1 GPT-5.6 Sol — $4/M, score 77.4 Anthropic: Claude Fable 5 (batch) — $5/M, score 76.5 IBM: Granite 4.2 8B — $0.06/M, score 22.4 SpaceXAI: Grok 4.3 (batch) — $1/M, score 42.2 Gemini 3.7 Flash — $0.75/M, score 76.1 SpaceXAI: Grok 4.6 — $2/M, score 76.8 Google: Gemini 3.7 Flash (batch) — $0.375/M, score 76.1 Gemini 3.5 Flash Lite — $0.3/M, score 49.3 Qwen: Qwen3.7 Plus — $0.32/M, score 55.9 GPT-5.5 — $5/M, score 74.9 Gemini 3.1 Pro Preview — $2/M, score 68.8 OpenAI: GPT-4o-mini (batch) — $0.075/M, score 11.4 Mistral: Mistral Large 3 2512 (batch) — $0.25/M, score 20.1 OpenAI: GPT-6 Astra (batch) — $5/M, score 76.9 GPT-5 — $1.25/M, score 37.8 GPT-5 Mini — $0.25/M, score 15.6 OpenAI: GPT-5 Mini (batch) — $0.125/M, score 15.6 Anthropic: Claude Sonnet 4.6 — $3/M, score 63.0 Google: Gemini 2.5 Pro (batch) — $0.625/M, score 33.3 Gemini 2.5 Pro — $1.25/M, score 33.3 Mistral: Mistral Large 3 2512 — $0.5/M, score 20.1 Gemma 3 12B IT — $0.05/M, score 5.8 Anthropic: Claude Haiku 4.5 (batch) — $0.5/M, score 43.9 DeepSeek V4 Pro 0813 — $0.442/M, score 68.8 OpenAI: gpt-oss-120b (batch) — $0.15/M, score 30.4 Mistral: Mistral Small 4 (batch) — $0.075/M, score 26.6 Z.ai: GLM 5.2 (batch) — $0.7/M, score 68.8 Z.ai: GLM 5.3 — $1.4/M, score 74.8 SpaceXAI: Grok 4.3 — $1.25/M, score 42.2 GPT-5.6 Terra — $2/M, score 76.7 Anthropic: Claude Sonnet 4.6 (batch) — $1.5/M, score 63.0 NVIDIA: Nemotron 3 Ultra (batch) — $0.6/M, score 49.3 Anthropic: Claude Sonnet 4.5 (batch) — $1.5/M, score 52.1 Gemini 3.8 Flash — $0.75/M, score 76.3 Solar Pro 4 — $0.3/M, score 52.7 Mistral: Mistral Medium 3.1 — $0.4/M, score 20.5 OpenAI: GPT-5.5 (batch) — $2.5/M, score 74.9 GPT-4o (2024-05-13) — $5/M, score 24.2 DeepSeek V4 Flash — $0.15/M, score 52.0 inclusionAI: Ling 3.0 Flash — $0.021/M, score 50.6 GPT-6 Astra — $10/M, score 76.9 Z.ai: GLM 5.3 Flash — $0.15/M, score 71.5 OpenAI: GPT-5.6 Luna (batch) — $0.1/M, score 71.4 OpenAI: GPT-5.4 Mini (batch) — $0.375/M, score 56.1 GPT-5.6 Luna — $0.2/M, score 71.4 Inkling Small — $0.45/M, score 52.9 Muse Spark 1.1 — $1.25/M, score 71.3 o1 — $15/M, score 39.7 OpenAI: GPT-5.6 Sol (batch) — $1/M, score 77.4 Hy3 preview — $0.066/M, score 58.8 Qwen: Qwen3 Next 80B A3B Thinking — $0.15/M, score 17.4 Qwen: Qwen3.8 2.4T A95B — $2/M, score 71.9 Mistral: Ministral 3 8B 2512 (batch) — $0.075/M, score 9.7 Claude Opus 5 (batch) — $2.5/M, score 78.0 Gemini 3.1 Flash Lite Preview — $0.25/M, score 34.7 Kimi K2.5 — $0.3/M, score 46.8 DeepSeek V3.2 — $0.18/M, score 44.2 OpenAI: GPT-4.1 Mini (batch) — $0.2/M, score 20.2 Inception: Mercury 2 — $0.25/M, score 31.1 MiMo-V2.5-Pro — $0.435/M, score 60.2 Z.ai: GLM 4.6 — $0.43/M, score 45.8 OpenAI: GPT-5 (batch) — $0.625/M, score 37.8 Anthropic: Claude Sonnet 4 — $3/M, score 37.6 GPT-5.4 mini — $0.75/M, score 56.1 Trinity Large Thinking — $0.25/M, score 25.8 Qwen: Qwen3 30B A3B Thinking 2507 — $0.2/M, score 12.1 Z.ai: GLM 5.2 — $0.6/M, score 68.8 Qwen: Qwen3.7 Max — $1.475/M, score 66.0 SpaceXAI: Grok Build 0.1 — $1/M, score 51.5 Qwen: Qwen3.6 35B A3B — $0.1/M, score 41.9 Qwen: Qwen3.6 27B — $0.3/M, score 53.7 inclusionAI: Ling-2.6-flash — $0.01/M, score 25.3 Mistral: Mistral Small 4 — $0.15/M, score 26.6 Kwaipilot: KAT-Coder-Pro V2 — $0.3/M, score 59.5 Qwen: Qwen3.5-9B — $0.1/M, score 28.7 Qwen: Qwen3.5-35B-A3B — $0.312/M, score 37.0 Qwen: Qwen3.5-122B-A10B — $0.26/M, score 45.7 Upstage: Solar Pro 3 — $0.15/M, score 16.2 Z.ai: GLM 4.7 — $0.4/M, score 45.3 Amazon: Nova 2 Lite — $0.3/M, score 23.0 Mistral: Ministral 3 3B 2512 — $0.1/M, score 4.8 Google: Gemma 3n 4B — $0.06/M, score 3.2 Meta: Llama 4 Maverick — $0.2/M, score 16.3 OpenAI: o3 Mini High — $1.1/M, score 16.3 Meta: Llama 3.3 70B Instruct — $0.1/M, score 11.9 Meta: Llama 3.1 8B Instruct — $0.05/M, score 5.4 Nex AGI: Nex-N2-Pro — $0.25/M, score 59.1 Mistral: Mistral Medium 3.5 — $1.5/M, score 46.9 inclusionAI: Ring-2.6-1T — $0.075/M, score 42.8 IBM: Granite 4.1 8B — $0.05/M, score 9.5 Qwen: Qwen3.5 397B A17B — $0.55/M, score 48.2 Qwen: Qwen3 Coder Next — $0.12/M, score 36.2 Mistral: Ministral 3 14B 2512 — $0.2/M, score 14.4 Anthropic: Claude Haiku 4.5 — $1/M, score 43.9 Qwen: Qwen3 235B A22B Thinking 2507 — $0.23/M, score 22.1 Qwen: Qwen3 8B — $0.117/M, score 9.0 Qwen: Qwen3 14B — $0.227/M, score 13.8 Qwen: Qwen3 32B — $0.08/M, score 15.3 Meta: Llama 4 Scout — $0.1/M, score 8.2 DeepSeek: DeepSeek V3 0324 — $0.25/M, score 21.2 Cohere: Command A — $2.5/M, score 27.8 Step 3.7 Flash — $0.185/M, score 39.6 Input price per million tokens (log scale) Index

The stepped line is the efficient frontier: at each price, the best score available for that money or less. A model sitting on it is not being beaten by anything cheaper. Price is log-scaled because listed rates span four orders of magnitude. Only models with both a listed price and a score on this benchmark can appear.

Catalog activity

Change log

Field-level changes detected between successful source imports.

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Public API

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API documentation
Endpoint
GET https://model.kyssta.lol/api/v1/models/minimax/minimax-m2.7:free
curl
curl "https://model.kyssta.lol/api/v1/models/minimax/minimax-m2.7:free"
Common questions

Frequently asked questions

Answered directly from the stored record — nothing here is generated beyond the catalog's own fields.

What is MiniMax: MiniMax M2.7 (free)?

MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent. It is published by MiniMax and catalogued here from OpenRouter.

How much does MiniMax: MiniMax M2.7 (free) cost?

This model is documented as free to use at the listed providers.

What is the context length of MiniMax: MiniMax M2.7 (free)?

MiniMax: MiniMax M2.7 (free) accepts up to 196.608K tokens of context and returns up to 176.947K output tokens.

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