openclaw/docs/providers/ollama.md

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Run OpenClaw with Ollama (local LLM runtime)	You want to run OpenClaw with local models via Ollama You need Ollama setup and configuration guidance	Ollama

Ollama

Ollama is a local LLM runtime that makes it easy to run open-source models on your machine. OpenClaw integrates with Ollama's OpenAI-compatible API and can auto-discover tool-capable models when you opt in with OLLAMA_API_KEY (or an auth profile) and do not define an explicit models.providers.ollama entry.

Quick start

1. Install Ollama: https://ollama.ai

2. Pull a model:

ollama pull gpt-oss:20b
# or
ollama pull llama3.3
# or
ollama pull qwen2.5-coder:32b
# or
ollama pull deepseek-r1:32b

3. Enable Ollama for OpenClaw (any value works; Ollama doesn't require a real key):

# Set environment variable
export OLLAMA_API_KEY="ollama-local"

# Or configure in your config file
openclaw config set models.providers.ollama.apiKey "ollama-local"

4. Use Ollama models:

{
  agents: {
    defaults: {
      model: { primary: "ollama/gpt-oss:20b" },
    },
  },
}

Model discovery (implicit provider)

When you set OLLAMA_API_KEY (or an auth profile) and do not define models.providers.ollama, OpenClaw discovers models from the local Ollama instance at http://127.0.0.1:11434:

• Queries /api/tags and /api/show
• Keeps only models that report tools capability
• Marks reasoning when the model reports thinking
• Reads contextWindow from model_info["<arch>.context_length"] when available
• Sets maxTokens to 10× the context window
• Sets all costs to 0

This avoids manual model entries while keeping the catalog aligned with Ollama's capabilities.

To see what models are available:

ollama list
openclaw models list

To add a new model, simply pull it with Ollama:

ollama pull mistral

The new model will be automatically discovered and available to use.

If you set models.providers.ollama explicitly, auto-discovery is skipped and you must define models manually (see below).

Configuration

Basic setup (implicit discovery)

The simplest way to enable Ollama is via environment variable:

export OLLAMA_API_KEY="ollama-local"

Explicit setup (manual models)

Use explicit config when:

• Ollama runs on another host/port.
• You want to force specific context windows or model lists.
• You want to include models that do not report tool support.

{
  models: {
    providers: {
      ollama: {
        // Use a host that includes /v1 for OpenAI-compatible APIs
        baseUrl: "http://ollama-host:11434/v1",
        apiKey: "ollama-local",
        api: "openai-completions",
        models: [
          {
            id: "gpt-oss:20b",
            name: "GPT-OSS 20B",
            reasoning: false,
            input: ["text"],
            cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
            contextWindow: 8192,
            maxTokens: 8192 * 10
          }
        ]
      }
    }
  }
}

If OLLAMA_API_KEY is set, you can omit apiKey in the provider entry and OpenClaw will fill it for availability checks.

Custom base URL (explicit config)

If Ollama is running on a different host or port (explicit config disables auto-discovery, so define models manually):

{
  models: {
    providers: {
      ollama: {
        apiKey: "ollama-local",
        baseUrl: "http://ollama-host:11434/v1",
      },
    },
  },
}

Model selection

Once configured, all your Ollama models are available:

{
  agents: {
    defaults: {
      model: {
        primary: "ollama/gpt-oss:20b",
        fallbacks: ["ollama/llama3.3", "ollama/qwen2.5-coder:32b"],
      },
    },
  },
}

Advanced

Reasoning models

OpenClaw marks models as reasoning-capable when Ollama reports thinking in /api/show:

ollama pull deepseek-r1:32b

Model Costs

Ollama is free and runs locally, so all model costs are set to $0.

Streaming Configuration

Due to a known issue in the underlying SDK with Ollama's response format, streaming is disabled by default for Ollama models. This prevents corrupted responses when using tool-capable models.

When streaming is disabled, responses are delivered all at once (non-streaming mode), which avoids the issue where interleaved content/reasoning deltas cause garbled output.

Re-enable Streaming (Advanced)

If you want to re-enable streaming for Ollama (may cause issues with tool-capable models):

{
  agents: {
    defaults: {
      models: {
        "ollama/gpt-oss:20b": {
          streaming: true,
        },
      },
    },
  },
}

Disable Streaming for Other Providers

You can also disable streaming for any provider if needed:

{
  agents: {
    defaults: {
      models: {
        "openai/gpt-4": {
          streaming: false,
        },
      },
    },
  },
}

Context windows

For auto-discovered models, OpenClaw uses the context window reported by Ollama when available, otherwise it defaults to 8192. You can override contextWindow and maxTokens in explicit provider config.

Troubleshooting

Ollama not detected

Make sure Ollama is running and that you set OLLAMA_API_KEY (or an auth profile), and that you did not define an explicit models.providers.ollama entry:

ollama serve

And that the API is accessible:

curl http://localhost:11434/api/tags

No models available

OpenClaw only auto-discovers models that report tool support. If your model isn't listed, either:

• Pull a tool-capable model, or
• Define the model explicitly in models.providers.ollama.

To add models:

ollama list  # See what's installed
ollama pull gpt-oss:20b  # Pull a tool-capable model
ollama pull llama3.3     # Or another model

Connection refused

Check that Ollama is running on the correct port:

# Check if Ollama is running
ps aux | grep ollama

# Or restart Ollama
ollama serve

Corrupted responses or tool names in output

If you see garbled responses containing tool names (like sessions_send, memory_get) or fragmented text when using Ollama models, this is due to an upstream SDK issue with streaming responses. This is fixed by default in the latest OpenClaw version by disabling streaming for Ollama models.

If you manually enabled streaming and experience this issue:

1. Remove the streaming: true configuration from your Ollama model entries, or
2. Explicitly set streaming: false for Ollama models (see Streaming Configuration)

See Also

• Model Providers - Overview of all providers
• Model Selection - How to choose models
• Configuration - Full config reference