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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.

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Configuring a Provider

To config a new provider, simply run the onboarding wizard: 
ironclaw onboard --provider-only

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Provider Overview

ProviderBackend valueRequires API keyNotes
NEAR AInearaiOAuth (browser)Multi-model
AnthropicanthropicANTHROPIC_API_KEYClaude models
OpenAIopenaiOPENAI_API_KEYGPT models
Google Geminigemini_oauthOAuth (browser)Gemini models; function calling
io.netionetIONET_API_KEYIntelligence API
MistralmistralMISTRAL_API_KEYMistral models
Yandex AI StudioyandexYANDEX_API_KEYYandexGPT models
MiniMaxminimaxMINIMAX_API_KEYMiniMax-M2.7 models
Cloudflare Workers AIcloudflareCLOUDFLARE_API_KEYAccess to Workers AI
GitHub Copilotgithub_copilotGITHUB_COPILOT_TOKENMulti-models
OllamaollamaNoLocal inference
AWS BedrockbedrockAWS credentialsNative Converse API
OpenRouteropenai_compatibleLLM_API_KEY300+ models
Together AIopenai_compatibleLLM_API_KEYFast inference
Fireworks AIopenai_compatibleLLM_API_KEYFast inference
vLLM / LiteLLMopenai_compatibleOptionalSelf-hosted
LM Studioopenai_compatibleNoLocal GUI

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NEAR AI

NEARAI_MODEL=claude-3-5-sonnet-20241022
NEARAI_BASE_URL=https://private.near.ai
Popular models: Qwen/Qwen3.5-122B-A10B, black-forest-labs/FLUX.2-klein-4B, zai-org/GLM-5-FP8

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Anthropic (Claude)

LLM_BACKEND=anthropic
ANTHROPIC_API_KEY=sk-ant-...
Popular models: claude-sonnet-4-20250514, claude-3-5-sonnet-20241022, claude-3-5-haiku-20241022

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OpenAI (GPT)

LLM_BACKEND=openai
OPENAI_API_KEY=sk-...
Popular models: gpt-4o, gpt-4o-mini, o3-mini

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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. 
LLM_BACKEND=gemini_oauth
GEMINI_MODEL=gemini-2.5-flash

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Supported features

FeatureStatusNotes
Function calling✅functionDeclarations / functionCall / functionResponse
generationConfig✅temperature, maxOutputTokens passed from request
thinkingConfig✅thinkingBudget/thinkingLevel for thinking-capable models (does NOT set includeThoughts)
toolConfig✅functionCallingConfig.mode: AUTO/ANY/NONE
SSE streaming✅Cloud Code API with streamGenerateContent?alt=sse
Token refresh✅Automatic via refresh token
ModelIDNotes
Gemini 3.1 Progemini-3.1-pro-previewLatest, strongest reasoning
Gemini 3.1 Pro Custom Toolsgemini-3.1-pro-preview-customtoolsEnhanced tool use
Gemini 3 Progemini-3-pro-previewPreview
Gemini 3 Flashgemini-3-flash-previewFast preview with thinking
Gemini 3.1 Flash Litegemini-3.1-flash-lite-previewPreview, lightweight
Gemini 2.5 Progemini-2.5-proStable, strong reasoning
Gemini 2.5 Flashgemini-2.5-flashFast, good quality
Gemini 2.5 Flash Litegemini-2.5-flash-liteFastest, lightweight

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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).

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GitHub Copilot

GitHub Copilot exposes chat endpoint at https://api.githubcopilot.com. IronClaw uses that endpoint directly through the built-in github_copilot provider. 
LLM_BACKEND=github_copilot
GITHUB_COPILOT_TOKEN=gho_...
GITHUB_COPILOT_MODEL=gpt-4o
# Optional advanced headers if your setup needs them:
# GITHUB_COPILOT_EXTRA_HEADERS=Copilot-Integration-Id:vscode-chat
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.

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Ollama (local)

Install Ollama from ollama.com, pull a model, then: 
LLM_BACKEND=ollama
OLLAMA_MODEL=llama3.2
# OLLAMA_BASE_URL=http://localhost:11434   # default
Pull a model first: ollama pull llama3.2

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MiniMax

MiniMax provides high-performance language models with 204,800 token context windows. 
LLM_BACKEND=minimax
MINIMAX_API_KEY=...
Available models: MiniMax-M2.7 (default), MiniMax-M2.7-highspeed, MiniMax-M2.5, MiniMax-M2.5-highspeed To use the China mainland endpoint, set: 
MINIMAX_BASE_URL=https://api.minimaxi.com/v1

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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

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With AWS credentials (IAM, SSO, instance roles)

LLM_BACKEND=bedrock
BEDROCK_MODEL=anthropic.claude-opus-4-6-v1
BEDROCK_REGION=us-east-1
BEDROCK_CROSS_REGION=us
# AWS_PROFILE=my-sso-profile   # optional, for named profiles
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.

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Cross-region inference

Set BEDROCK_CROSS_REGION to route requests across AWS regions for capacity:
PrefixRouting
usUS regions (us-east-1, us-east-2, us-west-2)
euEuropean regions
apacAsia-Pacific regions
globalAll commercial AWS regions
(unset)Single-region only
ModelID
Claude Opus 4.6anthropic.claude-opus-4-6-v1
Claude Sonnet 4.5anthropic.claude-sonnet-4-5-20250929-v1:0
Claude Haiku 4.5anthropic.claude-haiku-4-5-20251001-v1:0
Amazon Nova Proamazon.nova-pro-v1:0
Llama 4 Maverickmeta.llama4-maverick-17b-instruct-v1:0

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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.

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OpenRouter

OpenRouter routes to 300+ models from a single API key. 
LLM_BACKEND=openai_compatible
LLM_BASE_URL=https://openrouter.ai/api/v1
LLM_API_KEY=sk-or-...
LLM_MODEL=anthropic/claude-sonnet-4
Popular OpenRouter model IDs:
ModelID
Claude Sonnet 4anthropic/claude-sonnet-4
GPT-4oopenai/gpt-4o
Llama 4 Maverickmeta-llama/llama-4-maverick
Gemini 2.0 Flashgoogle/gemini-2.0-flash-001
Mistral Smallmistralai/mistral-small-3.1-24b-instruct
Browse all models at openrouter.ai/models.

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Together AI

Together AI provides fast inference for open-source models. 
LLM_BACKEND=openai_compatible
LLM_BASE_URL=https://api.together.xyz/v1
LLM_API_KEY=...
LLM_MODEL=meta-llama/Llama-3.3-70B-Instruct-Turbo
Popular Together AI model IDs:
ModelID
Llama 3.3 70Bmeta-llama/Llama-3.3-70B-Instruct-Turbo
DeepSeek R1deepseek-ai/DeepSeek-R1
Qwen 2.5 72BQwen/Qwen2.5-72B-Instruct-Turbo

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Fireworks AI

Fireworks AI offers fast inference with compound AI system support. 
LLM_BACKEND=openai_compatible
LLM_BASE_URL=https://api.fireworks.ai/inference/v1
LLM_API_KEY=fw_...
LLM_MODEL=accounts/fireworks/models/llama4-maverick-instruct-basic

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vLLM / LiteLLM (self-hosted)

For self-hosted inference servers: 
LLM_BACKEND=openai_compatible
LLM_BASE_URL=http://localhost:8000/v1
LLM_API_KEY=token-abc123        # set to any string if auth is not configured
LLM_MODEL=meta-llama/Llama-3.1-8B-Instruct
LiteLLM proxy (forwards to any backend, including Bedrock, Vertex, Azure): 
LLM_BACKEND=openai_compatible
LLM_BASE_URL=http://localhost:4000/v1
LLM_API_KEY=sk-...
LLM_MODEL=gpt-4o                 # as configured in litellm config.yaml

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LM Studio (local GUI)

Start LM Studio’s local server, then: 
LLM_BACKEND=openai_compatible
LLM_BASE_URL=http://localhost:1234/v1
LLM_MODEL=llama-3.2-3b-instruct-q4_K_M
# LLM_API_KEY is not required for LM Studio