MiniMax

MiniMax M2.7

minimax/minimax-m2.7
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

M2.7 在真实的软件工程中有优异的表现,包括端到端的完整项目交付,分析日志排查 Bug、代码安全,机器学习等。 在专业办公领域,我们提升了模型在各领域的专业知识和任务交付能力,在 GDPval-AA 的ELO得分是1495,为开源最高。M2.7 对 Office 三件套 Excel/PPT/Word 的复杂编辑能力显著提升,能更好地完成多轮修改和高保真的编辑。 M2.7具备与复杂环境交互的能力,M2.7 在 40 个复杂 skills (> 2000 Token) 的 case 上,仍能保持 97% 的 skills 遵循率。在OpenClaw的使用中,M2.7相比于M2.5也有了显著的提升,在MMClaw的评测中接近最新的Sonnet 4.6。 M2.7具备优秀的身份保持能力和情商,除了生产力使用外,给互动娱乐场景的创新也准备了空间。

Input / output modalities
文本 to 文本
Reference input / output price
Input¥2.1Output¥8.4per 1M tokens
Context window
200K
Added to catalog
Mar 18, 2026

Providers and pricing

ProviderInput /MOutput /MCached /MContextMax outputDetails
MiniMax¥2.1¥8.4¥0.42200K131K

MiniMax

Latency
0.36s
Throughput
52 tokens/s
Context
200K

Pricing

Input
¥2.1/M tokens
Output
¥8.4/M tokens
Cached
¥0.42/M tokens

Additional pricing

Cache write
¥2.63
Cache read
¥0.42

Specifications

Context
200K
Max output
131K
Supported APIs
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

MiniMax M2.7 code examples and API guide

Modelmesh normalizes requests and responses across service providers behind one consistent API.

Modelmesh provides an OpenAI-compatible Completion API for more than 300 models and service providers. Call it directly, through the OpenAI SDK, or with supported third-party SDKs.

Modelmesh-specific request headers in these examples are optional. When supplied, your application can appear on the Modelmesh rankings.

Supported endpointsSelect an endpoint to switch the example below.
/v1/chat/completions
from openai import OpenAI API_KEY = "$SSY_API_KEY" client = OpenAI( base_url="https://router.shengsuanyun.com/api/v1", api_key=API_KEY, ) try: completion = client.chat.completions.create( model="minimax/minimax-m2.7", messages=[{"role": "user", "content": "Which number is larger, 9.11 or 9.8?"}], temperature=0.6, top_p=0.7, stream=True, ) response_text = "" for chunk in completion: if chunk.choices and chunk.choices[0].delta.content is not None: content = chunk.choices[0].delta.content print(content, end="", flush=True) response_text += content except Exception as error: print(f"Request failed: {error}")
                
              

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