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IronClaw supports multiple LLM providers out of the box, including NEAR AI , Anthropic, OpenAI, Google Gemini, GitHub Copilot, Ollama, AWS Bedrock, and any OpenAI-compatible endpoint. Providers can be configured via environment variables or the onboarding wizard. IronClaw’s modular architecture allows seamless integration with new providers by implementing the LLMProvider trait.

Configuring a Provider

To config a new provider, simply run the onboarding wizard:

Provider Overview


NEAR AI

Popular models: Qwen/Qwen3.5-122B-A10B, black-forest-labs/FLUX.2-klein-4B, zai-org/GLM-5-FP8

Anthropic (Claude)

Popular models: claude-sonnet-4-20250514, claude-3-5-sonnet-20241022, claude-3-5-haiku-20241022

OpenAI (GPT)

Popular models: gpt-4o, gpt-4o-mini, o3-mini

Google Gemini (OAuth)

Uses Google OAuth with PKCE (S256) for authentication — no API key required. On first run, a browser opens for Google account login. Credentials (including refresh token) are saved to ~/.gemini/oauth_creds.json with 0600 permissions.

Supported features

Cloud Code API vs standard API

Models containing -preview (with hyphen) or gemini-3 in the name, as well as any gemini- model with major version >= 2, route through the Cloud Code API (cloudcode-pa.googleapis.com) which supports SSE streaming and project-scoped access. Other models use the standard Generative Language API (generativelanguage.googleapis.com).

GitHub Copilot

GitHub Copilot exposes chat endpoint at https://api.githubcopilot.com. IronClaw uses that endpoint directly through the built-in github_copilot provider.
ironclaw onboard can acquire this token for you using GitHub device login. If you already signed into Copilot through VS Code or a JetBrains IDE, you can also reuse the oauth_token stored in ~/.config/github-copilot/apps.json. If you prefer, LLM_BACKEND=github-copilot also works as an alias. Popular models vary by subscription, but gpt-4o is a safe default. IronClaw keeps model entry manual for this provider because GitHub Copilot model listing may require extra integration headers on some clients. IronClaw automatically injects the standard VS Code identity headers (User-Agent, Editor-Version, Editor-Plugin-Version, Copilot-Integration-Id) and lets you override them with GITHUB_COPILOT_EXTRA_HEADERS.

Ollama (local)

Install Ollama from ollama.com, pull a model, then:
Pull a model first: ollama pull llama3.2

MiniMax

MiniMax provides high-performance language models with 204,800 token context windows.
Available models: MiniMax-M2.7 (default), MiniMax-M2.7-highspeed, MiniMax-M2.5, MiniMax-M2.5-highspeed To use the China mainland endpoint, set:

AWS Bedrock (requires --features bedrock)

Uses the native AWS Converse API via aws-sdk-bedrockruntime. Supports standard AWS authentication methods: IAM credentials, SSO profiles, and instance roles.
Build prerequisite: The aws-lc-sys crate (transitive dependency via AWS SDK) requires CMake to compile. Install it before building with --features bedrock:
  • macOS: brew install cmake
  • Ubuntu/Debian: sudo apt install cmake
  • Fedora: sudo dnf install cmake

With AWS credentials (IAM, SSO, instance roles)

The AWS SDK credential chain automatically resolves credentials from environment variables (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY), shared credentials file (~/.aws/credentials), SSO profiles, and EC2/ECS instance roles.

Cross-region inference

Set BEDROCK_CROSS_REGION to route requests across AWS regions for capacity:

OpenAI-Compatible Endpoints

All providers below use LLM_BACKEND=openai_compatible. Set LLM_BASE_URL to the provider’s OpenAI-compatible endpoint and LLM_API_KEY to your API key.

OpenRouter

OpenRouter routes to 300+ models from a single API key.
Popular OpenRouter model IDs: Browse all models at openrouter.ai/models.

Together AI

Together AI provides fast inference for open-source models.
Popular Together AI model IDs:

Fireworks AI

Fireworks AI offers fast inference with compound AI system support.

vLLM / LiteLLM (self-hosted)

For self-hosted inference servers:
LiteLLM proxy (forwards to any backend, including Bedrock, Vertex, Azure):

LM Studio (local GUI)

Start LM Studio’s local server, then: