MiniMax M2.7 API
Released March 18, 2026 | 200K Tokens context | MoE (MiniMax-M2.7) parameters
MiniMax M2.7 API enables production coding assistants, agentic workflows spanning tools and documents, and long-context summarisation workloads. MiniMax-M2.7 is MiniMax's latest OpenAI-compatible reasoning model — a successor to M2.5 with improved coding, agentic, and long-context performance, served via the MiniMax HTTP API with thinking-mode responses by default. Standout strengths include OpenAI-compatible integration, strong benchmark gains over M2.5, and the same cost profile as M2.5 for predictable unit economics.
from openai import OpenAI # Initialize the OpenAI client with Qubrid base URL client = OpenAI( base_url="https://platform.qubrid.com/v1", api_key="QUBRID_API_KEY", ) stream = client.chat.completions.create( model="MiniMaxAI/MiniMax-M2.7", messages=[ { "role": "user", "content": "Explain quantum computing in simple terms" } ], max_tokens=8192, temperature=1, top_p=0.95, stream=True ) for chunk in stream: if chunk.choices and chunk.choices[0].delta.content: print(chunk.choices[0].delta.content, end="", flush=True) print("\n")from openai import OpenAI # Initialize the OpenAI client with Qubrid base URL client = OpenAI( base_url="https://platform.qubrid.com/v1", api_key="QUBRID_API_KEY", ) stream = client.chat.completions.create( model="MiniMaxAI/MiniMax-M2.7", messages=[ { "role": "user", "content": "Explain quantum computing in simple terms" } ], max_tokens=8192, temperature=1, top_p=0.95, stream=True ) for chunk in stream: if chunk.choices and chunk.choices[0].delta.content: print(chunk.choices[0].delta.content, end="", flush=True) print("\n") Enterprise
Platform Integration
Docker Support
Official Docker images for containerized deployments
Kubernetes Ready
Production-grade KBS manifests and Helm charts
SDK Libraries
Official SDKs for Python, Javascript, Go, and Java
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Document Intelligence Platform