Featherless AI serves open models through an OpenAI-compatible API. Apus installs Featherless as an official external provider plugin and keeps the built-in catalog small while accepting exact model ids from Featherless at runtime.

Property Value
Provider id featherless
Package @openclaw/featherless-provider
Auth env var FEATHERLESS_API_KEY
Onboarding flag --auth-choice featherless-api-key
Direct CLI flag --featherless-api-key <key>
API OpenAI-compatible (openai-completions)
Base URL https://api.featherless.ai/v1
Default model featherless/Qwen/Qwen3-32B

Setup

Install the plugin:

apus plugins install @openclaw/featherless-provider

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

Run onboarding:

apus onboard --auth-choice featherless-api-key

For non-interactive setup:

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

Or expose the key to the Gateway process:

export FEATHERLESS_API_KEY="<your-featherless-api-key>" # pragma: allowlist secret

Verify the provider:

apus models list --provider featherless

Default model

The plugin uses Qwen/Qwen3-32B as the setup default because Featherless documents native tool calling for the Qwen 3 family. Apus configures its 32,768-token context window, a conservative 4,096-token output limit, and Qwen chat-template thinking controls.

The catalog cost fields use Featherless's published request-pricing rates of $0.102 per million input tokens and $0.493 per million output tokens. Fixed subscription plans remain flat-rate; the cache cost fields stay zero because Featherless does not publish separate cache-read or cache-write rates for this model.

Other Featherless models

Use the exact Featherless model id after the featherless/ provider prefix:

{
  agents: {
    defaults: {
      model: {
        primary: "featherless/moonshotai/Kimi-K2-Instruct",
      },
    },
  },
}

Apus deliberately does not copy Featherless's full public model index into the picker. The index is large and does not expose enough structured capability metadata to classify every text, vision, embedding, and reasoning model safely. Unknown ids therefore resolve with conservative text-only, non-reasoning defaults: a 4,096-token context window and 1,024-token output limit.

Add an explicit provider model entry when a model needs different metadata:

{
  models: {
    mode: "merge",
    providers: {
      featherless: {
        baseUrl: "https://api.featherless.ai/v1",
        apiKey: "${FEATHERLESS_API_KEY}",
        api: "openai-completions",
        models: [
          {
            id: "google/gemma-3-27b-it",
            name: "Gemma 3 27B",
            input: ["text", "image"],
            reasoning: false,
            contextWindow: 32768,
            maxTokens: 4096,
          },
        ],
      },
    },
  },
}

Check Featherless's model catalog for current model availability and capability tags before adding custom metadata.

Troubleshooting

Related