> ## Documentation Index
> Fetch the complete documentation index at: https://docs2.openclaw.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# vLLM
vLLM serves open-source (and some custom) models through an **OpenAI-compatible** HTTP API. OpenClaw connects using the `openai-completions` API and can **auto-discover** models when you opt in with `VLLM_API_KEY`.
| Property | Value |
| ---------------- | ------------------------------------------ |
| Provider ID | `vllm` |
| API | `openai-completions` (OpenAI-compatible) |
| Auth | `VLLM_API_KEY` environment variable |
| Default base URL | `http://127.0.0.1:8000/v1` |
| Streaming usage | Supported (`stream_options.include_usage`) |
## Getting started
Your base URL must expose `/v1` endpoints (`/v1/models`, `/v1/chat/completions`). vLLM commonly runs on:
```text theme={"theme":{"light":"min-light","dark":"min-dark"}}
http://127.0.0.1:8000/v1
```
Any non-empty value works if your server does not enforce auth:
```bash theme={"theme":{"light":"min-light","dark":"min-dark"}}
export VLLM_API_KEY="vllm-local"
```
Replace with one of your vLLM model IDs:
```json5 theme={"theme":{"light":"min-light","dark":"min-dark"}}
{
agents: {
defaults: {
model: { primary: "vllm/your-model-id" },
},
},
}
```
```bash theme={"theme":{"light":"min-light","dark":"min-dark"}}
openclaw models list --provider vllm
```
For non-interactive setup (CI, scripting), pass the base URL, key, and model directly:
```bash theme={"theme":{"light":"min-light","dark":"min-dark"}}
openclaw onboard --non-interactive \
--mode local \
--auth-choice vllm \
--custom-base-url "http://127.0.0.1:8000/v1" \
--custom-api-key "vllm-local" \
--custom-model-id "your-model-id"
```
## Model discovery (implicit provider)
When `VLLM_API_KEY` is set (or an auth profile exists) and `models.providers.vllm` is **not** defined, OpenClaw queries `GET http://127.0.0.1:8000/v1/models` and converts the returned IDs into model entries.
If you set `models.providers.vllm` explicitly, OpenClaw uses only your declared models. Add `"vllm/*": {}` to `agents.defaults.models` to make OpenClaw also query that configured provider's `/models` endpoint and include all advertised vLLM models.
## Explicit configuration
Configure explicitly when vLLM runs on a different host or port, you want to pin `contextWindow`/`maxTokens`, your server requires a real API key, or you connect to a trusted loopback, LAN, or Tailscale endpoint:
```json5 theme={"theme":{"light":"min-light","dark":"min-dark"}}
{
models: {
providers: {
vllm: {
baseUrl: "http://127.0.0.1:8000/v1",
apiKey: "${VLLM_API_KEY}",
api: "openai-completions",
timeoutSeconds: 300, // Optional: extend request timeout for slow local models
models: [
{
id: "your-model-id",
name: "Local vLLM Model",
reasoning: false,
input: ["text"],
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
contextWindow: 128000,
maxTokens: 8192,
},
],
},
},
},
}
```
To keep the provider dynamic without listing every model, add a wildcard to the visible model catalog:
```json5 theme={"theme":{"light":"min-light","dark":"min-dark"}}
{
agents: {
defaults: {
models: {
"vllm/*": {},
},
},
},
}
```
## Advanced configuration
vLLM is treated as a proxy-style OpenAI-compatible `/v1` backend, not a native OpenAI endpoint:
| Behavior | Applied? |
| --------------------------------------- | -------------------------------- |
| Native OpenAI request shaping | No |
| `service_tier` | Not sent |
| Responses `store` | Not sent |
| Prompt-cache hints | Not sent |
| OpenAI reasoning-compat payload shaping | Not applied |
| Hidden OpenClaw attribution headers | Not injected on custom base URLs |
For Qwen models, set `compat.thinkingFormat: "qwen-chat-template"` on the model row when the server expects Qwen chat-template kwargs. These models expose a binary `/think` profile (`off`, `on`) because Qwen chat-template thinking is an on/off flag, not an OpenAI-style effort ladder.
```json5 theme={"theme":{"light":"min-light","dark":"min-dark"}}
{
models: {
providers: {
vllm: {
models: [
{
id: "Qwen/Qwen3-8B",
name: "Qwen3 8B",
reasoning: true,
compat: { thinkingFormat: "qwen-chat-template" },
},
],
},
},
},
}
```
OpenClaw maps `/think off` to:
```json theme={"theme":{"light":"min-light","dark":"min-dark"}}
{
"chat_template_kwargs": {
"enable_thinking": false,
"preserve_thinking": true
}
}
```
Non-`off` thinking levels send `enable_thinking: true`. If your endpoint expects DashScope-style top-level flags instead, use `compat.thinkingFormat: "qwen"` to send `enable_thinking` at the request root.
For `vllm/nemotron-3-*` models with thinking off, the bundled plugin sends:
```json theme={"theme":{"light":"min-light","dark":"min-dark"}}
{
"chat_template_kwargs": {
"enable_thinking": false,
"force_nonempty_content": true
}
}
```
To customize these values, set `chat_template_kwargs` under the model params. If you also set `params.extra_body.chat_template_kwargs`, that value wins because `extra_body` is the last request-body override.
```json5 theme={"theme":{"light":"min-light","dark":"min-dark"}}
{
agents: {
defaults: {
models: {
"vllm/nemotron-3-super": {
params: {
chat_template_kwargs: {
enable_thinking: false,
force_nonempty_content: true,
},
},
},
},
},
},
}
```
First confirm vLLM was started with the right tool-call parser and chat template for the model. vLLM documents `hermes` for Qwen2.5 models and `qwen3_xml` for Qwen3-Coder models.
Symptoms: skills/tools never run, the assistant prints raw JSON/XML such as `{"name":"read","arguments":...}`, or vLLM returns an empty `tool_calls` array when OpenClaw sends `tool_choice: "auto"`.
Some Qwen/vLLM combinations return structured tool calls only when the request uses `tool_choice: "required"`. Force it per model with `params.extra_body`:
```json5 theme={"theme":{"light":"min-light","dark":"min-dark"}}
{
agents: {
defaults: {
models: {
"vllm/Qwen-Qwen2.5-Coder-32B-Instruct": {
params: {
extra_body: {
tool_choice: "required",
},
},
},
},
},
},
}
```
Replace the model id with the exact id from `openclaw models list --provider vllm`, or apply the same override from the CLI:
```bash theme={"theme":{"light":"min-light","dark":"min-dark"}}
openclaw config set agents.defaults.models '{"vllm/Qwen-Qwen2.5-Coder-32B-Instruct":{"params":{"extra_body":{"tool_choice":"required"}}}}' --strict-json --merge
```
This is an opt-in workaround: it forces every turn with tools to make a tool call, so use it only for a dedicated model entry where that is acceptable. Do not set it as a global default for all vLLM models, and do not pair it with a proxy that converts arbitrary assistant text into executable tool calls.
If your vLLM server runs on a non-default host or port, set `baseUrl` in the explicit provider config:
```json5 theme={"theme":{"light":"min-light","dark":"min-dark"}}
{
models: {
providers: {
vllm: {
baseUrl: "http://192.168.1.50:9000/v1",
apiKey: "${VLLM_API_KEY}",
api: "openai-completions",
timeoutSeconds: 300,
models: [
{
id: "my-custom-model",
name: "Remote vLLM Model",
reasoning: false,
input: ["text"],
contextWindow: 64000,
maxTokens: 4096,
},
],
},
},
},
}
```
## Troubleshooting
For large local models, remote LAN hosts, or tailnet links, set a provider-scoped request timeout:
```json5 theme={"theme":{"light":"min-light","dark":"min-dark"}}
{
models: {
providers: {
vllm: {
baseUrl: "http://192.168.1.50:8000/v1",
apiKey: "${VLLM_API_KEY}",
api: "openai-completions",
timeoutSeconds: 300,
models: [{ id: "your-model-id", name: "Local vLLM Model" }],
},
},
},
}
```
`timeoutSeconds` applies to vLLM model HTTP requests only: connection setup, response headers, body streaming, and the total guarded-fetch abort. It also raises the LLM idle/stream watchdog ceiling above the implicit \~120s default for this provider. Prefer this over increasing `agents.defaults.timeoutSeconds`, which controls the whole agent run.
Check that the vLLM server is running and accessible:
```bash theme={"theme":{"light":"min-light","dark":"min-dark"}}
curl http://127.0.0.1:8000/v1/models
```
If you see a connection error, verify the host, port, and that vLLM started in OpenAI-compatible server mode. OpenClaw trusts the exact configured `models.providers.vllm.baseUrl` origin for guarded model requests on loopback, LAN, and Tailscale endpoints. Metadata/link-local origins remain blocked without explicit opt-in. Set `models.providers.vllm.request.allowPrivateNetwork: true` only when vLLM requests must reach another private origin, or `false` to opt out of exact-origin trust.
If requests fail with auth errors, set a real `VLLM_API_KEY` that matches your server configuration, or configure the provider explicitly under `models.providers.vllm`.
If your vLLM server does not enforce auth, any non-empty value for `VLLM_API_KEY` works as an opt-in signal for OpenClaw.
Auto-discovery requires `VLLM_API_KEY` to be set. If you have defined `models.providers.vllm`, OpenClaw uses only your declared models unless `agents.defaults.models` includes `"vllm/*": {}`.
If a Qwen model prints JSON/XML tool syntax instead of executing a skill:
* Start vLLM with the correct parser/template for that model.
* Confirm the exact model id with `openclaw models list --provider vllm`.
* Add a dedicated per-model `params.extra_body.tool_choice: "required"` override only if `tool_choice: "auto"` still returns empty or text-only tool calls.
More help: [Troubleshooting](/help/troubleshooting) and [FAQ](/help/faq).
## Related
Choosing providers, model refs, and failover behavior.
Native OpenAI provider and OpenAI-compatible route behavior.
Auth details and credential reuse rules.
Common issues and how to resolve them.