OpenClaw Multi-Model Support: Gemini 3.1, Claude, GPT and More

One AI Assistant, Dozens of Model Providers

One of OpenClaw's most underappreciated capabilities is its model-agnostic architecture. Most people pick one AI provider and hard-code it — so when that provider has an outage, raises prices, or releases a slow model, they're stuck. OpenClaw is designed differently: you configure a list of model providers, and the system can route, fallback, and override at the channel level.

The v2026.2.21 release expanded this further, adding Gemini 3.1 Pro Preview, Volcano Engine (Doubao) and BytePlus providers with coding variants, Claude Sonnet 4.6 and 4.5 via the GitHub Copilot catalog, and fixing Kimi-Coding to use the correct anthropic-messages API type.

Supported Providers as of v2026.2.21

Provider	Notable Models	Best For
Anthropic	Claude Sonnet 4.6, Claude Opus 4.5	Reasoning, long context, coding
OpenAI	GPT-4o, o3-mini, o4	General purpose, function calling
Google	Gemini 3.1 Pro Preview, Gemini 2.0 Flash	Multimodal, long context, speed
Volcano Engine (Doubao)	Doubao Pro, Doubao Coding	Chinese-language tasks, coding
BytePlus	BytePlus Pro, BytePlus Coding	Coding tasks, enterprise
Moonshot (Kimi)	Kimi-Coding, Kimi-Long	Long context (1M+), coding
OpenRouter	Any model on OpenRouter	Model exploration, cost optimisation
Ollama	Llama 3, Mistral, Qwen, Phi	Fully local, air-gapped deployments
GitHub Copilot	Claude Sonnet 4.5/4.6, GPT-4o	Teams with existing Copilot licenses
LM Studio	Any GGUF model	Local development and testing

Basic Provider Configuration

Configure your primary model in openclaw.json or via environment variables. At minimum you need one API key:

# .env — pick at least one
ANTHROPIC_API_KEY=sk-ant-...
OPENAI_API_KEY=sk-...
GEMINI_API_KEY=AIza...
OPENROUTER_API_KEY=sk-or-...

# For Volcano Engine (Doubao) — added v2026.2.21
VOLCENGINE_API_KEY=...

In openclaw.json, set your default model:

{
  "model": "claude-sonnet-4-6",
  "provider": "anthropic"
}

Multi-Model Fallback Chains

The fallback system lets you define an ordered list of models. If the primary model fails (rate limit, outage, timeout), OpenClaw automatically tries the next model in the chain. You see this in /status and in process logs:

{
  "models": {
    "primary": "claude-sonnet-4-6",
    "fallback": [
      "google/gemini-3.1-pro-preview",
      "openai/gpt-4o",
      "openrouter/meta-llama/llama-3-70b-instruct"
    ]
  }
}

The v2026.2.21 release added visibility into the fallback lifecycle — you can now see in /status which model is currently active and whether the system fell back, and why. This is valuable for diagnosing intermittent failures in high-availability deployments.

Per-Channel Model Overrides

New in v2026.2.21: the channels.modelByChannel configuration lets you assign different models to different channels. This is useful when you want a fast, cheap model for high-volume WhatsApp customer interactions but a more powerful model for complex Slack requests:

{
  "channels": {
    "modelByChannel": {
      "whatsapp": "openai/gpt-4o-mini",
      "telegram": "claude-sonnet-4-6",
      "discord": "google/gemini-3.1-pro-preview",
      "slack": "claude-opus-4-5"
    }
  }
}

Per-channel overrides take precedence over the global model setting and are logged in /status so you can verify routing is working as expected.

Thinking Mode Support

Several models support extended thinking (chain-of-thought reasoning before answering). OpenClaw exposes this via the thinkingDefault config key, and v2026.2.21 adds per-model overrides:

{
  "models": {
    "config": {
      "claude-sonnet-4-6": {
        "thinkingDefault": true,
        "thinkingBudget": 8000
      },
      "google/gemini-3.1-pro-preview": {
        "thinkingDefault": false
      }
    }
  }
}

Enable thinking mode for complex reasoning tasks and disable it for fast, simple responses where latency matters more than depth.

Choosing the Right Model for Your Use Case

With a dozen providers available, the choice matters:

• Customer support bots (high volume): GPT-4o-mini or Gemini 2.0 Flash — fast, cheap, accurate enough for FAQ-style responses
• Complex reasoning and coding: Claude Sonnet 4.6 or Claude Opus 4.5 — deep instruction following, long context, strong code generation
• Multimodal (images, video frames, PDFs): Gemini 3.1 Pro Preview — strong native multimodal handling
• Chinese-language deployments: Doubao Pro or BytePlus Pro — optimised for Mandarin, significantly better than Western models on Chinese text
• Air-gapped or privacy-critical: Ollama with Llama 3 or Qwen — fully local, no data leaves your hardware
• Cost optimisation across unpredictable workloads: OpenRouter with fallback — automatic routing to available and affordable models

The Configuration Complexity

Multi-model configuration is one of the areas where OpenClaw's power comes with setup complexity. Getting fallback chains right, provider authentication working across multiple services, per-channel overrides, thinking mode budgets, and cost monitoring configured correctly requires a working understanding of each provider's API structure.

Common issues we see in DIY deployments: wrong model ID strings (provider prefixes like openrouter/ are required for non-default providers), missing API key for the fallback model causing fallback to fail silently, and thinking mode enabled on models that do not support it causing errors.