MiniMax M3 Provider for Claude Code

MiniMax-M3 has a 1 million token context window and a 512K max output. That size changes what fits in a single session. You can load a whole monorepo, run long agentic workflows, and let the model accumulate context across hundreds of files before it needs to compact.

Model specs

The template maps MiniMax-M3 to every role (Opus, Sonnet, Haiku, small/fast). There is only one model, so quick shell commands and complex multi-step reasoning both go to it.

Effort level is set to max and thinking is enabled with REASONING_EFFORT: high. The model gets 32,000 thinking tokens by default, which is deep enough for most work without eating much of the context window.

Setup

1. Create an account at minimax.io and generate an API key
2. Run the setup command:

claude-multi add minimax

3. Paste your API key when prompted

The template sets the base URL, model mapping, thinking parameters, and output limits. You should not need to edit anything by hand.

When to pick MiniMax

Pick MiniMax when context length is the constraint. If you work on large codebases, do multi-repository analysis, or run agentic tasks that accumulate a lot of state, the 1M window means fewer compaction cycles.

The 512K output limit also makes a few things practical that other providers cap out on: generating an application scaffold in one pass, or getting a long analysis back without truncation.

For shorter, more interactive sessions, DeepSeek or GLM may cost you less.

Pricing details

MiniMax bills per token through minimax.io with no monthly commitment. Token Plan subscriptions are also available (Plus / Max / Ultra monthly tiers). Both routes share the same api.minimax.io endpoint, and your API key type decides which quota gets consumed.

For benchmark comparisons vs Opus 4.7 and GPT-5.5, see the MiniMax M3 announcement post.

Related providers

• DeepSeek - 1M context, pay-per-token
• GLM - fixed monthly subscription plan
• Kimi - 256K context, built for tool-heavy work