Model Switching

Copair supports multiple AI providers and models. You can switch between them at any time during a session — no need to restart.

Supported Providers

Switching Models Mid-Session

Use the /model command to switch models without losing your conversation context:

Copair will display a list of configured providers and models. Select one to switch immediately.

Quick Switch

You can also specify the model directly:

> /model anthropic:claude-sonnet-4.6
> /model openai:gpt-5.4
> /model ollama:llama4

Configuring Providers

Add providers by editing ~/.copair/config.yaml (global) or .copair/config.yaml (project-level).

Single provider

# ~/.copair/config.yaml
version: 1
default_model: claude-sonnet

providers:
  anthropic:
    api_key: ${ANTHROPIC_API_KEY}
    models:
      claude-sonnet:
        id: claude-sonnet-4-20250514

Multiple providers

You can configure multiple providers simultaneously — all appear in the /model menu:

version: 1
default_model: claude-sonnet

providers:
  anthropic:
    api_key: ${ANTHROPIC_API_KEY}
    models:
      claude-sonnet:
        id: claude-sonnet-4-20250514

  openai:
    api_key: ${OPENAI_API_KEY}
    models:
      gpt-5:
        id: gpt-5

  google:
    api_key: ${GOOGLE_API_KEY}
    models:
      gemini-flash:
        id: gemini-3-flash

OpenAI-Compatible Endpoints

For self-hosted or alternative providers that use the OpenAI API format, set type: openai-compatible:

providers:
  ollama:
    type: openai-compatible
    base_url: http://localhost:11434/v1
    models:
      llama4:
        id: llama4
        supports_tool_calling: false

This works with Ollama, vLLM, LM Studio, llama.cpp, and any OpenAI-compatible server.

When to Switch Models

• Complex reasoning — Use Claude Opus 4.6 or GPT-5.4 for architecture decisions and multi-step refactoring
• Quick edits — Use a faster model like Gemini 3 Flash or Claude Haiku 4.5 for small changes
• Local/offline — Switch to Ollama with Llama 4 or Qwen 2.5 when you don't have internet access
• Cost optimization — Use local models for exploration, cloud models for final implementation