The Meta API uses the OpenAI-compatible Responses API (POST /v1/responses) for the Muse Wonder and Muse Spark reasoning models. Apus provides Meta as an official external plugin.

Property Value
Provider id meta
Plugin @openclaw/meta-provider
Auth env var MODEL_API_KEY
Onboarding flag --auth-choice meta-api-key
Direct CLI flag --meta-api-key <key>
API Responses API (openai-responses)
Base URL https://api.meta.ai/v1
Default model meta/muse-spark-1.3
Apus reasoning default high (reasoning.effort)

Getting started

Install the plugin

```bash
apus plugins install @openclaw/meta-provider
```

Installation applies to a running Gateway automatically; otherwise it takes effect
on the next startup. See [Apply changes and inspect](/plugins/manage-plugins#apply-changes-and-inspect).

Set the API key

apus onboard --auth-choice meta-api-key

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

export MODEL_API_KEY=<key>

Verify models are available

```bash
apus models list --provider meta
```

Lists the Meta catalog entries. Select `meta/muse-wonder-1.0` for Wonder. If `MODEL_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 meta-api-key \
  --meta-api-key "$MODEL_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.

Built-in catalog

Prices and data-use terms come from Meta's pricing and rate limits documentation. Meta's model catalog positions Muse Wonder for complex coding and long-running agents, and Muse Spark for lower-cost workloads. New setups keep Muse Spark 1.3 as their default; Wonder is an explicit selection.

Model ref Name Apus input Reasoning Context window Input / cached input / output per 1M tokens
meta/muse-wonder-1.0 Muse Wonder text, image yes 1,048,576 $4.00 / $0.20 / $20.00
meta/muse-spark-1.3 Muse Spark 1.3 text, image yes 1,048,576 $1.25 / $0.15 / $4.25
meta/muse-spark-1.3-contributor Muse Spark 1.3 Contributor text, image yes 1,048,576 $0.10 / $0.002 / $0.20
meta/muse-spark-1.2 Muse Spark 1.2 text, image yes 1,048,576 $1.25 / $0.15 / $4.25
meta/muse-spark-1.2-contributor Muse Spark 1.2 Contributor text, image yes 1,048,576 $0.10 / $0.002 / $0.20
meta/muse-spark-1.1 Muse Spark 1.1 text, image yes 1,048,576 $1.25 / $0.15 / $4.25

Muse Wonder is available in Standard mode only on Meta Model API. There is no muse-wonder-1.0-contributor API model. Muse Wonder Full (muse-wonder-full-1.0) is available only through the native Muse Code CLI on Power Usage and Maximum Usage subscriptions, not through this API provider. Setting Wonder's reasoning effort to max does not select Wonder Full. See Meta's availability table.

Meta's pricing documentation and Terms of Service distinguish Standard Services from Contributor/Discounted Services:

  • Standard Services are the default. Meta says prompts and completions submitted to Standard Services are not used to train Meta models.
  • By using Contributor/Discounted Services, you permit Meta to use Content submitted to and generated by those services as described in the Terms. Under the Terms, use of Discounted Services acknowledges that permission. You must not submit sensitive, confidential, or personal information to the Discounted Services.

Meta's Geographic Use Policy governs availability. It limits API access in some jurisdictions and adds end-user deployment restrictions for products built with the Contributor/Discounted model; those additional restrictions do not apply to your own use or products built with Standard Services.

Capabilities:

Meta's model catalog lists text, image, video, audio, and PDF input for these models. Apus's model catalog directly represents text and image input only; the other upstream modalities are not model-manifest input values.

Apus uses a 131,072-token catalog output cap for these models. Meta does not publish an exact maximum-output figure; this cap is not a claim about Meta's maximum. Output tokens include both reasoning and visible text.

Apus explicitly selects high when no thinking level is configured. This is an Apus default, not Meta's omitted-parameter behavior: Meta's reasoning documentation says that when reasoning.effort is omitted, the model reasons at a model-determined level.

Muse Wonder and Muse Spark do not accept reasoning.effort: "none". Apus maps --thinking off to minimal for this provider.

Manual config

{
  env: { vars: { MODEL_API_KEY: "<key>" } },
  agents: {
    defaults: {
      model: { primary: "meta/muse-wonder-1.0" },
      models: {
        "meta/muse-wonder-1.0": { alias: "Muse Wonder" },
      },
    },
  },
}

If the Gateway runs as a daemon (launchd, systemd, Docker), make sure MODEL_API_KEY is available to that process — for example in ~/.apus/.env or through env.shellEnv. A key exported only in an interactive shell will not help a managed service unless the env is imported separately.

Smoke test

export MODEL_API_KEY=<key>
pnpm test:live -- extensions/meta/meta.live.test.ts

The live suite exercises enabled Meta cases against POST /v1/responses. To test only Wonder, add -t muse-wonder-1.0. Its live cases cover text, image input, reasoning effort, and a tool-call round trip with encrypted reasoning replay.

Related

Model providers

Choosing providers, model refs, and failover behavior.

Thinking modes

Reasoning effort levels for Meta models.

Configuration reference

Agent defaults and model configuration.