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Provider flags let you switch between different AI providers and models on the fly. Use your Claude subscription, cloud platforms, or local models without changing configuration files.

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Available Providers

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Local Providers (Free)

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--ollama
flag
Ollama - Run models locally or on Ollama’s cloud
ai --ollama
ai --ollama task.md
ai --ollama --model qwen3-coder
ai --ollama --model minimax-m2.5:cloud  # Cloud model, no GPU needed
Short form: --olSetup:
brew install ollama              # macOS
ollama pull qwen3-coder          # Pull a model
ollama serve                     # Start server
Requirements:
  • Ollama installed and running at http://localhost:11434
  • 24GB+ VRAM for local coding models (cloud models work on any hardware)
See Local Providers for details.
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--lmstudio
flag
LM Studio - Local models with MLX support (fast on Apple Silicon)
ai --lmstudio
ai --lm task.md
ai --lm --model mlx-community/Qwen2.5-Coder-32B-Instruct-4bit
Short form: --lmSetup:
  1. Download LM Studio from lmstudio.ai
  2. Load a model in the UI
  3. Start server: lms server start --port 1234
Requirements:
  • LM Studio running at http://localhost:1234
  • 24GB+ unified memory for coding models
See Local Providers for details.

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Cloud Providers

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--aws
flag
AWS Bedrock - Claude models on Amazon Web Services
ai --aws
ai --aws --opus task.md
ai --aws --haiku --resume
Setup in ~/.ai-runner/secrets.sh:
export AWS_PROFILE="your-profile-name"
export AWS_REGION="us-west-2"
Authentication:
  • AWS credentials file (~/.aws/credentials)
  • Or IAM role (for EC2/ECS)
See Cloud Providers for details.
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--vertex
flag
Google Vertex AI - Claude models on Google Cloud Platform
ai --vertex
ai --vertex task.md
ai --vertex --sonnet --resume
Setup in ~/.ai-runner/secrets.sh:
export ANTHROPIC_VERTEX_PROJECT_ID="your-gcp-project-id"
export CLOUD_ML_REGION="global"
Authentication:
  • Application default credentials (gcloud auth application-default login)
  • Or service account key file
See Cloud Providers for details.
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--apikey
flag
Anthropic API - Direct access to Anthropic’s API
ai --apikey
ai --apikey --opus task.md
Setup in ~/.ai-runner/secrets.sh:
export ANTHROPIC_API_KEY="sk-ant-..."
Authentication:See Cloud Providers for details.
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--azure
flag
Microsoft Azure - Claude models on Azure Foundry
ai --azure
ai --azure task.md
Setup in ~/.ai-runner/secrets.sh:
export ANTHROPIC_FOUNDRY_API_KEY="your-azure-api-key"
export ANTHROPIC_FOUNDRY_RESOURCE="your-resource-name"
Authentication:
  • Azure Foundry API key
See Cloud Providers for details.
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--vercel
flag
Vercel AI Gateway - Access 100+ models (OpenAI, xAI, Google, Meta, and more)
ai --vercel
ai --vercel --model openai/gpt-5.2-codex
ai --vercel --model anthropic/claude-opus-4-6
ai --vercel --model google/gemini-exp-2506
Setup in ~/.ai-runner/secrets.sh:
export VERCEL_AI_GATEWAY_TOKEN="vck_..."
Authentication:Supported models:
  • OpenAI (GPT-4, GPT-5, etc.)
  • xAI (Grok models)
  • Google (Gemini models)
  • Meta (Llama models)
  • Anthropic (Claude models)
  • And many more
See Cloud Providers for details.
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--pro
flag
Claude Pro/Max - Your regular Claude subscription
ai --pro
ai --pro --resume
Authentication:
  • Claude subscription (log in with claude)
Note: This is the default if you’re logged in and don’t specify another provider.

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Provider Precedence

When no provider is specified, AI Runner auto-detects in this order:
  1. Saved default from --set-default
  2. Claude subscription (if logged in)
  3. Error (no provider available)
CLI flags always override saved defaults.

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Examples

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Basic Usage

# Use default provider (Claude subscription)
ai task.md

# Override to use AWS Bedrock
ai --aws task.md

# Use local Ollama (free)
ai --ollama task.md

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Combining Providers and Models

# AWS with Opus
ai --aws --opus task.md

# Ollama with specific model
ai --ollama --model qwen3-coder task.md

# Vercel with OpenAI
ai --vercel --model openai/gpt-5.2-codex task.md

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Interactive Sessions

# Start session with AWS
ai --aws

# Start with Ollama and bypass permissions
ai --ollama --bypass

# Start with Vertex and agent teams
ai --vertex --team

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Resume Conversations

# Hit rate limit on Pro
ai --pro
# "Rate limit exceeded"

# Switch to AWS and continue
ai --aws --resume

# Or switch to free Ollama
ai --ollama --resume

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Shebang Scripts

#!/usr/bin/env -S ai --aws --opus
Analyze this codebase with AWS Bedrock.

#!/usr/bin/env -S ai --ollama --haiku
Quick analysis with local Ollama.

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Set Default Provider

# Save AWS as default
ai --aws --set-default

# Now 'ai' uses AWS by default
ai task.md

# Override still works
ai --ollama task.md

# Clear default
ai --clear-default

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Provider Status

Check which providers are configured: 
ai-status
See ai-status reference for details.

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Multiple Providers Workflow

Switch between providers based on your needs: 
# Quick tests: use free Ollama
ai --ollama --haiku quick-test.md

# Complex tasks: use AWS with Opus
ai --aws --opus complex-task.md

# Cost-sensitive: use Haiku on any provider
ai --apikey --haiku analyze.md

# Rate-limited: fall back to different provider
ai --aws --resume  # Continue after hitting Pro rate limit

Model Flags

Select model tiers and specific model IDs

Provider Guides

Detailed setup for each provider