clawdbot/docs/providers/minimax.md

summary, read_when

summary	read_when
Use MiniMax M2.1 in Clawdbot (cloud, API, or LM Studio)	You want MiniMax models in Clawdbot You need MiniMax cloud/API setup or LM Studio config

MiniMax

MiniMax is an AI company that builds the M2/M2.1 model family. The current coding-focused release is MiniMax M2.1 (December 23, 2025), built for real-world complex tasks.

Source: MiniMax M2.1 release note

Model overview (M2.1)

MiniMax highlights these improvements in M2.1:

• Stronger multi-language coding (Rust, Java, Go, C++, Kotlin, Objective-C, TS/JS).
• Better web/app development and aesthetic output quality (including native mobile).
• Improved composite instruction handling for office-style workflows, building on interleaved thinking and integrated constraint execution.
• More concise responses with lower token usage and faster iteration loops.
• Stronger tool/agent framework compatibility and context management (Claude Code, Droid/Factory AI, Cline, Kilo Code, Roo Code, BlackBox).
• Higher-quality dialogue and technical writing outputs.

Choose a setup

Option A: MiniMax Cloud (OpenAI-compatible /v1)

Best for: hosted MiniMax with OpenAI-compatible API.

Configure via CLI:

• Run clawdbot configure
• Select Model/auth
• Choose MiniMax M2.1 (minimax.io)

{
  env: { MINIMAX_API_KEY: "sk-..." },
  agents: { defaults: { model: { primary: "minimax/MiniMax-M2.1" } } },
  models: {
    mode: "merge",
    providers: {
      minimax: {
        baseUrl: "https://api.minimax.io/v1",
        apiKey: "${MINIMAX_API_KEY}",
        api: "openai-completions",
        models: [
          {
            id: "MiniMax-M2.1",
            name: "MiniMax M2.1",
            reasoning: false,
            input: ["text"],
            cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
            contextWindow: 200000,
            maxTokens: 8192
          }
        ]
      }
    }
  }
}

Option B: MiniMax API (Anthropic-compatible /anthropic)

Best for: MiniMax's Anthropic-compatible API (platform.minimax.io).

Configure via CLI:

• Run clawdbot configure
• Select Model/auth
• Choose MiniMax API (platform.minimax.io)

{
  env: { MINIMAX_API_KEY: "sk-..." },
  agents: { defaults: { model: { primary: "minimax/MiniMax-M2.1" } } },
  models: {
    mode: "merge",
    providers: {
      minimax: {
        baseUrl: "https://api.minimax.io/anthropic",
        apiKey: "${MINIMAX_API_KEY}",
        api: "anthropic-messages",
        models: [
          {
            id: "MiniMax-M2.1",
            name: "MiniMax M2.1",
            reasoning: false,
            input: ["text"],
            cost: { input: 15, output: 60, cacheRead: 2, cacheWrite: 10 },
            contextWindow: 200000,
            maxTokens: 8192
          },
          {
            id: "MiniMax-M2.1-lightning",
            name: "MiniMax M2.1 Lightning",
            reasoning: false,
            input: ["text"],
            cost: { input: 15, output: 60, cacheRead: 2, cacheWrite: 10 },
            contextWindow: 200000,
            maxTokens: 8192
          },
          {
            id: "MiniMax-M2",
            name: "MiniMax M2",
            reasoning: true,
            input: ["text"],
            cost: { input: 15, output: 60, cacheRead: 2, cacheWrite: 10 },
            contextWindow: 200000,
            maxTokens: 8192
          }
        ]
      }
    }
  }
}

Option C: Local via LM Studio

Best for: local inference with LM Studio. We have seen strong results with MiniMax M2.1 on powerful hardware (e.g. a beefy Mac Studio) using LM Studio's local server.

Configure via CLI:

• Run clawdbot configure
• Select Model/auth
• Choose MiniMax M2.1 (LM Studio)

{
  agents: {
    defaults: {
      model: { primary: "lmstudio/minimax-m2.1-gs32" },
      models: { "lmstudio/minimax-m2.1-gs32": { alias: "Minimax" } }
    }
  },
  models: {
    mode: "merge",
    providers: {
      lmstudio: {
        baseUrl: "http://127.0.0.1:1234/v1",
        apiKey: "lmstudio",
        api: "openai-responses",
        models: [
          {
            id: "minimax-m2.1-gs32",
            name: "MiniMax M2.1 GS32",
            reasoning: false,
            input: ["text"],
            cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
            contextWindow: 196608,
            maxTokens: 8192
          }
        ]
      }
    }
  }
}

Configure via clawdbot configure

Use the interactive config wizard to set MiniMax without editing JSON:

1. Run clawdbot configure.
2. Select Model/auth.
3. Choose MiniMax M2.1 (minimax.io), MiniMax API (platform.minimax.io), or MiniMax M2.1 (LM Studio).
4. Pick your default model when prompted.

Configuration options

• models.providers.minimax.baseUrl: https://api.minimax.io/v1 or https://api.minimax.io/anthropic.
• models.providers.minimax.api: openai-completions (cloud) or anthropic-messages (API).
• models.providers.minimax.apiKey: MiniMax API key (MINIMAX_API_KEY).
• models.providers.minimax.models: define id, name, reasoning, contextWindow, maxTokens, cost.
• agents.defaults.models: alias models you want in the allowlist.
• models.mode: keep merge if you want to add MiniMax alongside built-ins.

Notes

• Model refs are minimax/<model> or lmstudio/<model>.
• MiniMax pricing is not published; the costs above are placeholders. Override in models.json for accurate tracking.
• See /concepts/model-providers for provider rules.
• Use clawdbot models list and clawdbot models set minimax/MiniMax-M2.1 to switch.