---
summary: "Run OpenClaw through inferrs (OpenAI-compatible local server)"
read_when:
- You want to run OpenClaw against a local inferrs server
- You are serving Gemma or another model through inferrs
- You need the exact OpenClaw compat flags for inferrs
title: "Inferrs"
---
[inferrs](https://github.com/ericcurtin/inferrs) serves local models behind an OpenAI-compatible `/v1` API. OpenClaw talks to it through the generic `openai-completions` adapter.
| Property | Value |
| ------------------ | -------------------------------------------------------------------- |
| Provider id | `inferrs` (custom; configure under `models.providers.inferrs`) |
| Plugin | none — not a bundled OpenClaw provider plugin |
| Auth env var | none required; any value works if your inferrs server has no auth |
| API | OpenAI-compatible (`openai-completions`) |
| Suggested base URL | `http://127.0.0.1:8080/v1` (or wherever your inferrs server listens) |
`inferrs` is a custom self-hosted OpenAI-compatible backend, not a dedicated OpenClaw provider plugin: you configure it under `models.providers.inferrs` instead of picking an onboarding auth choice. For a bundled plugin with auto-discovery, see [SGLang](/providers/sglang) or [vLLM](/providers/vllm).
## Getting started
```bash
inferrs serve google/gemma-4-E2B-it \
--host 127.0.0.1 \
--port 8080 \
--device metal
```
```bash
curl http://127.0.0.1:8080/health
curl http://127.0.0.1:8080/v1/models
```
Add an explicit provider entry and point your default model at it. See the config example below.
## Full config example
Gemma 4 on a local `inferrs` server:
```json5
{
agents: {
defaults: {
model: { primary: "inferrs/google/gemma-4-E2B-it" },
models: {
"inferrs/google/gemma-4-E2B-it": {
alias: "Gemma 4 (inferrs)",
},
},
},
},
models: {
mode: "merge",
providers: {
inferrs: {
baseUrl: "http://127.0.0.1:8080/v1",
apiKey: "inferrs-local",
api: "openai-completions",
models: [
{
id: "google/gemma-4-E2B-it",
name: "Gemma 4 E2B (inferrs)",
reasoning: false,
input: ["text"],
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
contextWindow: 131072,
maxTokens: 4096,
compat: {
requiresStringContent: true,
},
},
],
},
},
},
}
```
## On-demand startup
OpenClaw can start `inferrs` itself only when an `inferrs/...` model is selected. Add `localService` to the same provider entry:
```json5
{
models: {
providers: {
inferrs: {
baseUrl: "http://127.0.0.1:8080/v1",
apiKey: "inferrs-local",
api: "openai-completions",
timeoutSeconds: 300,
localService: {
command: "/opt/homebrew/bin/inferrs",
args: [
"serve",
"google/gemma-4-E2B-it",
"--host",
"127.0.0.1",
"--port",
"8080",
"--device",
"metal",
],
healthUrl: "http://127.0.0.1:8080/v1/models",
readyTimeoutMs: 180000,
idleStopMs: 0,
},
models: [
{
id: "google/gemma-4-E2B-it",
name: "Gemma 4 E2B (inferrs)",
reasoning: false,
input: ["text"],
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
contextWindow: 131072,
maxTokens: 4096,
compat: {
requiresStringContent: true,
},
},
],
},
},
},
}
```
`command` must be an absolute path. Run `which inferrs` on the Gateway host and use that path. Full field reference: [Local model services](/gateway/local-model-services).
## Advanced configuration
Some `inferrs` Chat Completions routes accept only string `messages[].content`, not structured content-part arrays.
If OpenClaw runs fail with:
```text
messages[1].content: invalid type: sequence, expected a string
```
set `compat.requiresStringContent: true` in the model entry. OpenClaw then flattens pure text content parts into plain strings before sending the request.
Some `inferrs` + Gemma combinations accept small direct `/v1/chat/completions` requests but fail on full OpenClaw agent-runtime turns. Try disabling the tool schema surface first:
```json5
compat: {
requiresStringContent: true,
supportsTools: false
}
```
That reduces prompt pressure on stricter local backends. If tiny direct requests still work but normal OpenClaw agent turns keep crashing inside `inferrs`, treat it as an upstream model/server limitation rather than an OpenClaw transport issue.
Test both layers once configured:
```bash
curl http://127.0.0.1:8080/v1/chat/completions \
-H 'content-type: application/json' \
-d '{"model":"google/gemma-4-E2B-it","messages":[{"role":"user","content":"What is 2 + 2?"}],"stream":false}'
```
```bash
openclaw infer model run \
--model inferrs/google/gemma-4-E2B-it \
--prompt "What is 2 + 2? Reply with one short sentence." \
--json
```
If the first command works but the second fails, see Troubleshooting below.
Because `inferrs` uses the generic `openai-completions` adapter (not `openai-responses`), native-OpenAI-only request shaping never applies: no `service_tier`, no Responses `store`, no prompt-cache hints, and no OpenAI reasoning-compat payload shaping get sent.
## Troubleshooting
`inferrs` is not running, not reachable, or not bound to the host/port you configured. Confirm the server is started and listening on that address.
Set `compat.requiresStringContent: true` in the model entry (see above).
Set `compat.supportsTools: false` to disable the tool schema surface (see the Gemma caveat above).
If schema errors are gone but `inferrs` still crashes on larger agent turns, treat it as an upstream `inferrs` or model limitation. Reduce prompt pressure or switch backend/model.
For general help, see [Troubleshooting](/help/troubleshooting) and [FAQ](/help/faq).
## Related
Running OpenClaw against local model servers.
Starting local model servers on demand for configured providers.
Debugging local OpenAI-compatible backends that pass probes but fail agent runs.
Overview of all providers, model refs, and failover behavior.