7.9 KiB
summary, read_when, title
| summary | read_when | title | ||
|---|---|---|---|---|
| Run OpenClaw with Ollama (local LLM runtime) |
|
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 native API (/api/chat), supports streaming and tool calling, and can auto-discover local Ollama 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
-
Install Ollama: https://ollama.com/download
-
Pull a local model if you want local inference:
ollama pull glm-4.7-flash
# or
ollama pull gpt-oss:20b
# or
ollama pull llama3.3
- If you want Ollama Cloud models too, sign in:
ollama signin
- Run onboarding and choose
Ollama:
openclaw onboard
Local: local models onlyCloud + Local: local models plus Ollama Cloud models- Cloud models such as
kimi-k2.5:cloud,minimax-m2.5:cloud, andglm-5:clouddo not require a localollama pull
OpenClaw currently suggests:
- local default:
glm-4.7-flash - cloud defaults:
kimi-k2.5:cloud,minimax-m2.5:cloud,glm-5:cloud
- If you prefer manual setup, enable Ollama for OpenClaw directly (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"
- Inspect or switch models:
openclaw models list
openclaw models set ollama/glm-4.7-flash
- Or set the default in config:
{
agents: {
defaults: {
model: { primary: "ollama/glm-4.7-flash" },
},
},
}
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 - Uses best-effort
/api/showlookups to readcontextWindowwhen available - Marks
reasoningwith a model-name heuristic (r1,reasoning,think) - Sets
maxTokensto the default Ollama max-token cap used by OpenClaw - Sets all costs to
0
This avoids manual model entries while keeping the catalog aligned with the local Ollama instance.
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 fully manual model definitions.
{
models: {
providers: {
ollama: {
baseUrl: "http://ollama-host:11434",
apiKey: "ollama-local",
api: "ollama",
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", // No /v1 - use native Ollama API URL
api: "ollama", // Set explicitly to guarantee native tool-calling behavior
},
},
},
}
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 treats models with names such as deepseek-r1, reasoning, or think as reasoning-capable by default:
ollama pull deepseek-r1:32b
Model Costs
Ollama is free and runs locally, so all model costs are set to $0.
Streaming Configuration
OpenClaw's Ollama integration uses the native Ollama API (/api/chat) by default, which fully supports streaming and tool calling simultaneously. No special configuration is needed.
Legacy OpenAI-Compatible Mode
**Tool calling is not reliable in OpenAI-compatible mode.** Use this mode only if you need OpenAI format for a proxy and do not depend on native tool calling behavior.If you need to use the OpenAI-compatible endpoint instead (e.g., behind a proxy that only supports OpenAI format), set api: "openai-completions" explicitly:
{
models: {
providers: {
ollama: {
baseUrl: "http://ollama-host:11434/v1",
api: "openai-completions",
injectNumCtxForOpenAICompat: true, // default: true
apiKey: "ollama-local",
models: [...]
}
}
}
}
This mode may not support streaming + tool calling simultaneously. You may need to disable streaming with params: { streaming: false } in model config.
When api: "openai-completions" is used with Ollama, OpenClaw injects options.num_ctx by default so Ollama does not silently fall back to a 4096 context window. If your proxy/upstream rejects unknown options fields, disable this behavior:
{
models: {
providers: {
ollama: {
baseUrl: "http://ollama-host:11434/v1",
api: "openai-completions",
injectNumCtxForOpenAICompat: false,
apiKey: "ollama-local",
models: [...]
}
}
}
}
Context windows
For auto-discovered models, OpenClaw uses the context window reported by Ollama when available, otherwise it falls back to the default Ollama context window used by OpenClaw. 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
If your model is not listed, either:
- Pull the model locally, or
- Define the model explicitly in
models.providers.ollama.
To add models:
ollama list # See what's installed
ollama pull glm-4.7-flash
ollama pull gpt-oss:20b
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
See Also
- Model Providers - Overview of all providers
- Model Selection - How to choose models
- Configuration - Full config reference