M3

LLM
MiniMax

M3 by MiniMax is a text-based LLM built for coding and agentic tasks, featuring a 1 million token context window and open weights for enterprise customization.

Context tokens

524,288

Output tokens

131,072

Released

Jun 1, 2026

Capabilities

Tool use
Structured output

Supported tools

  • Seclai Content Tools

    Inspect source documents connected to your account. Includes tools for loading full content, reading character ranges, searching within documents, viewing stats, and listing available content sources. When a source_connection_content_version_id is provided in agent run metadata it is used as the default. Otherwise the model can discover content via list_content_sources.

  • Seclai Knowledge Base

    Search your knowledge bases using semantic similarity. Includes search_knowledge_base and list_knowledge_bases. When a knowledge_base_id is provided in the prompt or agent run metadata it is used as the default. Otherwise the model can discover available knowledge bases at runtime.

  • Seclai Memory Banks

    Manage persistent memory across agent runs. Includes tools for listing memory banks, writing entries, searching memory via semantic similarity, and loading entries in chronological order. Supports two memory types: 'conversation' (speaker-attributed turns) and 'general' (freeform text). Use key to organize entries by topic, session, or user.

  • Seclai Web Tools

    Fetch web pages and search the web from within agent prompt calls. Includes seclai_web_fetch for retrieving page content in markdown, HTML, or plain text, and seclai_web_search for finding relevant pages with content snippets.

Pricing

TypeCreditsUnits
Input3.99Credits per 1k tokens
Output15.96Credits per 1k tokens
Cache hit0.798Credits per 1k tokens

Variants

No variants available for this model.

Try This Model

Write a prompt and experiment with M3 in the model experiments page. You can compare it with other models side by side.