inferrs can serve local models behind an OpenAI-compatible /v1 API. OpenClaw works with inferrs through the generic openai-completions path.

Property	Value
Provider id	inferrs (custom; configure under models.providers.inferrs)
Plugin	none — inferrs is not a bundled OpenClaw provider plugin
Auth env var	Optional. 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 lives)

Note

inferrs is currently best treated as a custom self-hosted OpenAI-compatible backend, not a dedicated OpenClaw provider plugin. You configure it through models.providers.inferrs rather than an onboarding choice flag. If you need a true bundled plugin with auto-discovery, see SGLang or vLLM.

Getting started

Start inferrs with a model

```bash
inferrs serve google/gemma-4-E2B-it \
  --host 127.0.0.1 \
  --port 8080 \
  --device metal
```

Verify the server is reachable

```bash
curl http://127.0.0.1:8080/health
curl http://127.0.0.1:8080/v1/models
```

Add an OpenClaw provider entry

Add an explicit provider entry and point your default model at it. See the full config example below.

Full config example

This example uses Gemma 4 on a local inferrs server.

{
  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

Inferrs can also be started by OpenClaw only when an inferrs/... model is selected. Add localService to the same provider entry:

{
  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 absolute. Use which inferrs on the Gateway host and put that path in config. For the full field reference, see Local model services.

Advanced configuration

Why requiresStringContent matters

Some `inferrs` Chat Completions routes accept only string
`messages[].content`, not structured content-part arrays.

Warning

If OpenClaw runs fail with an error like:

```text
messages[1].content: invalid type: sequence, expected a string
```

set `compat.requiresStringContent: true` in your model entry.

```json5
compat: {
  requiresStringContent: true
}
```

OpenClaw will flatten pure text content parts into plain strings before sending
the request.

Gemma and tool-schema caveat

Some current `inferrs` + Gemma combinations accept small direct
`/v1/chat/completions` requests but still fail on full OpenClaw agent-runtime
turns.

If that happens, try this first:

```json5
compat: {
  requiresStringContent: true,
  supportsTools: false
}
```

That disables OpenClaw's tool schema surface for the model and can reduce prompt
pressure on stricter local backends.

If tiny direct requests still work but normal OpenClaw agent turns continue to
crash inside `inferrs`, the remaining issue is usually upstream model/server
behavior rather than OpenClaw's transport layer.

Manual smoke test

Once configured, test both layers:

```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, check the troubleshooting section below.

Proxy-style behavior

`inferrs` is treated as a proxy-style OpenAI-compatible `/v1` backend, not a
native OpenAI endpoint.

- Native OpenAI-only request shaping does not apply here
- No `service_tier`, no Responses `store`, no prompt-cache hints, and no
  OpenAI reasoning-compat payload shaping
- Hidden OpenClaw attribution headers (`originator`, `version`, `User-Agent`)
  are not injected on custom `inferrs` base URLs

Troubleshooting

curl /v1/models fails

`inferrs` is not running, not reachable, or not bound to the expected
host/port. Make sure the server is started and listening on the address you
configured.

messages[].content expected a string

Set `compat.requiresStringContent: true` in the model entry. See the
`requiresStringContent` section above for details.

Direct /v1/chat/completions calls pass but openclaw infer model run fails

Try setting `compat.supportsTools: false` to disable the tool schema surface.
See the Gemma tool-schema caveat above.

inferrs still crashes on larger agent turns

If OpenClaw no longer gets schema errors but `inferrs` still crashes on larger
agent turns, treat it as an upstream `inferrs` or model limitation. Reduce
prompt pressure or switch to a different local backend or model.

Tip

For general help, see Troubleshooting and FAQ.

Related

• Local models — Running OpenClaw against local model servers.
• Local model services — Starting local model servers on demand for configured providers.
• Gateway troubleshooting — Debugging local OpenAI-compatible backends that pass probes but fail agent runs.
• Model selection — Overview of all providers, model refs, and failover behavior.