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Featherless AI serves open models through an OpenAI-compatible API. OpenClaw installs Featherless as an official external provider plugin and keeps the built-in catalog small while accepting exact model ids from Featherless at runtime.
PropertyValue
Provider idfeatherless
Package@openclaw/featherless-provider
Auth env varFEATHERLESS_API_KEY
Onboarding flag--auth-choice featherless-api-key
Direct CLI flag--featherless-api-key <key>
APIOpenAI-compatible (openai-completions)
Base URLhttps://api.featherless.ai/v1
Default modelfeatherless/Qwen/Qwen3-32B

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Setup

Install the plugin and restart the Gateway: 
openclaw plugins install @openclaw/featherless-provider
openclaw gateway restart
Run onboarding: 
openclaw onboard --auth-choice featherless-api-key
For non-interactive setup: 
openclaw onboard --non-interactive \
  --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: 
openclaw models list --provider featherless

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Default model

The plugin uses Qwen/Qwen3-32B as the setup default because Featherless documents native tool calling for the Qwen 3 family. OpenClaw configures its 32,768-token context window, a conservative 4,096-token output limit, and Qwen chat-template thinking controls. The catalog cost fields are zero because Featherless supports multiple billing modes and OpenClaw does not embed account-specific plan or request-pricing rates.

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Other Featherless models

Use the exact Featherless model id after the featherless/ provider prefix: 
{
  agents: {
    defaults: {
      model: {
        primary: "featherless/moonshotai/Kimi-K2-Instruct",
      },
    },
  },
}
OpenClaw 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.

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Troubleshooting

  • 401 or 403: confirm FEATHERLESS_API_KEY is visible to the Gateway process, or run onboarding again.
  • Unknown model: use the exact case-sensitive id from Featherless after the featherless/ prefix.
  • Tool calls returned as text: choose a model family Featherless documents for native function calling, such as Qwen 3.
  • Managed Gateway cannot see the key: put it in ~/.openclaw/.env or another environment source loaded by the service, then restart the Gateway.