Cerebras provides high-speed OpenAI-compatible inference on custom inference hardware. The plugin discovers native model metadata and pricing, with a bundled catalog for offline fallback.

Install plugin

apus plugins install @openclaw/cerebras-provider

Installation applies to a running Gateway automatically; otherwise it takes effect on the next startup. See Apply changes and inspect.

Getting started

Create an API key in the [Cerebras Cloud Console](https://cloud.cerebras.ai).

apus onboard --auth-choice cerebras-api-key

apus onboard --non-interactive --accept-risk --skip-health \
  --auth-choice cerebras-api-key \
  --cerebras-api-key "$CEREBRAS_API_KEY"

export CEREBRAS_API_KEY=csk-...

```bash
apus models list --provider cerebras
```

Lists the configured Cerebras models. If `CEREBRAS_API_KEY` is unresolved, `apus models status --json` reports the missing credential under `auth.unusableProfiles`.

Non-interactive setup

apus onboard --non-interactive --accept-risk --skip-health \
  --mode local \
  --auth-choice cerebras-api-key \
  --cerebras-api-key "$CEREBRAS_API_KEY"

--mode defaults to local, so this is the same run as the Direct flag command above. Run it on the Gateway host: remote-client onboarding (--mode remote) only configures the local client connection and does not set up provider credentials on the server.

Discovery and pricing

When Cerebras auth is configured and the inference base URL is the canonical https://api.cerebras.ai/v1, Apus reads GET /public/v1/models. This request uses public headers only: inference API keys and discovery credentials are never sent to the metadata endpoint. A custom base URL skips this public discovery rather than mixing a proxy's catalog with Cerebras metadata. Without a Cerebras credential, the runtime provider stays inactive. Public metadata listing does not establish account entitlement.

Live rows supply the native context and completion limits, reasoning and vision capabilities, and prompt/completion prices. Cerebras returns those prices as USD per-token strings; Apus converts them to USD per million tokens. The public feed does not provide cache tariffs. Zero cache fields in Apus's runtime estimate are not a claim about enterprise caching or billing.

Successful catalogs are cached for 60 seconds. If discovery fails, returns an empty catalog, or has no usable model rows, Apus uses the bundled offline seed. In the default models.mode: "merge", fresh onboarding does not copy generated model rows or prices into your config, allowing prices to refresh. Explicitly authored model rows and costs remain intact. In models.mode: "replace", discovery is disabled and onboarding keeps the offline seed as explicit config instead.

Built-in catalog

The three offline fallback models have a 131,072-token context window and a 40,960-token max output. Prices for models still present in the native public feed were refreshed from its August 31, 2026 response; absent legacy references retain their seed snapshots.

Cerebras's deprecation notice marks zai-glm-4.7 deprecated without naming a replacement. Apus keeps the shipped reference rather than deleting it or rewriting existing selections; retention does not guarantee upstream availability.

Fresh onboarding follows Cerebras's current Gemma 4 recommendation. Cerebras describes Gemma 4 31B as its reference medium-size model for equal-or-higher intelligence than GPT OSS, with multimodal agentic support. It is a public-preview model and may change or be discontinued on shorter notice than the production GPT OSS endpoint; existing Apus configurations keep their selected model.

Manual config

Most setups only need the API key. Use explicit models.providers.cerebras config to override model metadata in mode: "merge"; leave models empty to use discovered rows without pinning generated prices:

{
  env: { vars: { CEREBRAS_API_KEY: "csk-..." } },
  agents: {
    defaults: {
      model: { primary: "cerebras/gemma-4-31b" },
    },
  },
  models: {
    mode: "merge",
    providers: {
      cerebras: {
        baseUrl: "https://api.cerebras.ai/v1",
        apiKey: "${CEREBRAS_API_KEY}",
        api: "openai-completions",
        models: [],
      },
    },
  },
}

Related

Choosing providers, model refs, and failover behavior.

Reasoning effort levels for the Cerebras models.

Agent defaults and model configuration.

Auth profiles, switching models, and resolving "no profile" errors.