Meta Model API

The Meta Model API (public preview) serves Meta Superintelligence Labs' Muse Spark models through an OpenAI-compatible API. The Meta provider extends the OpenAI provider and supports its compatible options.

note

This provider is for the Meta Model API at api.meta.ai (Muse models), which supersedes Meta's Llama API (api.llama.com) as Meta's hosted inference service — the Llama API Public Preview was retired on July 6, 2026.

Setup

Create an API key from the API keys tab on the Meta Model API dashboard.
Set the MODEL_API_KEY environment variable — Meta's official variable, the same one its SDKs and quickstart use — or specify apiKey (or a custom apiKeyEnvar) in your config.

providers:
  - id: meta:muse-spark-1.1

meta:<model> defaults to the Responses API — Meta's full-feature surface and the one its docs recommend. Use meta:chat:<model> for the OpenAI-compatible chat completions endpoint, or meta:messages:<model> for the Anthropic-compatible Messages API. If you omit the model, the provider defaults to muse-spark-1.1.

Available Models

Check the models page for the live list. As of writing:

muse-spark-1.1 — multimodal reasoning model: 1,048,576-token context window, 131,072 max output tokens, text/image/video/PDF input, tool calling, structured output, and search grounding (Responses and Messages APIs).

Configuration

providers:
  - id: meta:muse-spark-1.1
    config:
      reasoning_effort: high
      max_completion_tokens: 8192
      temperature: 1.0

Configuration Options

The provider accepts compatible OpenAI provider options. Notable behavior:

reasoning_effort — minimal, low, medium, high, or xhigh. When omitted, the model picks its own reasoning depth. Muse Spark does not support none; the provider rejects it with a clear error. Reasoning tokens bill at the output rate and count toward the output cap.
max_completion_tokens — caps generation on the chat endpoint (Meta accepts max_tokens only as a deprecated alias; if you set it, the provider forwards it as the canonical max_completion_tokens). On the Responses API the cap is max_output_tokens, and the provider maps max_completion_tokens/max_tokens onto it. When unset, no cap is sent so reasoning can use the full output budget.
temperature — supported (0–2, API default 1.0). Promptfoo sends its deterministic default of 0 unless you override it.
response_format — structured output with guaranteed JSON schema matching.
tools / tool_choice — parallel tool calling with streamed arguments.
prompt_cache_retention — in_memory or 24h for prompt caching; cached prompt tokens bill at the cached-input rate.
seed — best-effort determinism.

Muse Spark does not support logprobs, n > 1, stop, or audio input/output. The provider fails fast for unsupported options instead of surfacing an HTTP 400 per request. OpenAI-compatible stream is also rejected because promptfoo expects a complete JSON response on the chat and Responses surfaces. OpenAI-scoped environment defaults (OPENAI_TEMPERATURE, OPENAI_TOP_P, OPENAI_MAX_COMPLETION_TOKENS, penalty variables) are not applied to Meta requests.

Cost Tracking

Promptfoo computes cost from the published pricing ($1.25 input / $0.15 cached input / $4.25 output per 1M tokens for muse-spark-1.1), including the cached-input rate for prompt-cache hits. Override with cost, inputCost, outputCost, or cacheReadCost (all in USD per token) if pricing changes or you have custom rates.

Responses API

meta:<model> (the default) and meta:responses:<model> target Meta's /v1/responses endpoint — the only Meta endpoint that carries reasoning across turns, with built-in web-search grounding:

providers:
  - id: meta:responses:muse-spark-1.1
    config:
      reasoning_effort: medium
      tools:
        - type: web_search

With web_search, the model grounds answers in real-time web results with inline citations. Web search bills separately ($2.50 per 1,000 queries) and is not included in promptfoo's computed token cost.

Messages API

meta:messages:<model> targets Meta's Anthropic-compatible Messages endpoint (https://api.meta.ai/v1/messages) — the surface Anthropic-format coding agents such as Claude Code use. Use it to evaluate Muse Spark over the same wire format those agents send:

providers:
  - id: meta:messages:muse-spark-1.1
    config:
      max_tokens: 8192

The provider extends the Anthropic provider, so its options (max_tokens, tools, image and document content blocks, etc.) apply. It defaults max_tokens to Muse Spark's 131,072-token output budget and enables streaming so the Anthropic SDK can safely handle long generations; streamed output is aggregated before grading. Authentication uses your Meta key as a bearer token (Authorization: Bearer), matching Meta's docs — Anthropic-scoped settings like ANTHROPIC_API_KEY, ANTHROPIC_BASE_URL, ANTHROPIC_MAX_TOKENS, ANTHROPIC_TEMPERATURE, custom headers, and Claude Code OAuth credentials are deliberately ignored on this surface.

Muse Spark's reasoning arrives on this surface as encrypted redacted_thinking blocks, so the provider defaults showThinking to false to keep the ciphertext out of graded output.

Using with coding-agent providers

Meta positions Muse Spark as a backend for coding agents, and promptfoo's agentic providers can evaluate those setups end to end. In both recipes, set apiKey explicitly: the agent subprocesses inherit your shell environment, and an explicit key guarantees your Meta key is used instead of an ambient OPENAI_API_KEY or ANTHROPIC_API_KEY that belongs to another service.

Codex CLI

The openai:codex-sdk provider drives Muse Spark over the Responses API:

providers:
  - id: openai:codex-sdk
    config:
      base_url: https://api.meta.ai/v1
      model: muse-spark-1.1
      apiKey: '{{env.MODEL_API_KEY}}'

The explicit apiKey is required — the provider does not read MODEL_API_KEY on its own, and without it an ambient OPENAI_API_KEY would be sent to the Meta endpoint instead.

Claude Code

The anthropic:claude-agent-sdk provider forwards config.env to the agent subprocess. Pass the environment Meta's guide prescribes, with apiKey set to your Meta key:

providers:
  - id: anthropic:claude-agent-sdk
    # Provider-level `env` outranks the eval's top-level `env`, pinning the
    # routing values a suite-wide ANTHROPIC_BASE_URL (e.g. an Anthropic
    # gateway) would otherwise override — which would send the Meta key there.
    env:
      ANTHROPIC_BASE_URL: https://api.meta.ai
      ANTHROPIC_CUSTOM_HEADERS: ''
    config:
      apiKey: '{{env.MODEL_API_KEY}}'
      env:
        ANTHROPIC_BASE_URL: https://api.meta.ai
        ANTHROPIC_AUTH_TOKEN: '{{env.MODEL_API_KEY}}'
        ANTHROPIC_CUSTOM_HEADERS: ''
        ANTHROPIC_MODEL: muse-spark-1.1
        ANTHROPIC_DEFAULT_OPUS_MODEL: muse-spark-1.1
        ANTHROPIC_DEFAULT_SONNET_MODEL: muse-spark-1.1
        ANTHROPIC_DEFAULT_HAIKU_MODEL: muse-spark-1.1
        CLAUDE_CODE_SUBAGENT_MODEL: muse-spark-1.1
        ENABLE_TOOL_SEARCH: 'true' # Claude Code disables MCP tool search for non-first-party hosts

warning

Do not omit apiKey, the empty ANTHROPIC_CUSTOM_HEADERS override, or the provider-level env block. The provider forwards its resolved API key into the agent subprocess as ANTHROPIC_API_KEY after env: is applied — if apiKey is unset and a real ANTHROPIC_API_KEY is exported in your shell, that Anthropic credential would be transmitted to Meta's endpoint. Clearing ANTHROPIC_CUSTOM_HEADERS prevents an inherited gateway or proxy secret from being sent to Meta. The provider-level env block matters because the subprocess environment is layered process.env < config.env < provider/suite env: without the pin, a top-level env.ANTHROPIC_BASE_URL in the same config would silently re-route the agent — and your Meta key — to that URL.

Pin every model alias as shown — Meta serves only muse-spark-1.1, and Claude Code otherwise routes background tasks, Plan Mode, or subagents to Claude models the Meta API doesn't serve. See Meta's coding agents guide for the full setup pattern.

Example Usage

providers:
  - id: meta:muse-spark-1.1
  - id: openai:gpt-5.5

prompts:
  - 'Summarize the following in one sentence: {{text}}'

tests:
  - vars:
      text: 'Promptfoo is an open-source tool for testing and evaluating LLM apps.'

Get started with a runnable example:

npx promptfoo@latest init --example provider-meta

API Details

Base URL: https://api.meta.ai/v1 (override with apiBaseUrl; the Messages surface uses the bare host https://api.meta.ai).
OpenAI-compatible chat completions (/chat/completions) and Responses (/responses) endpoints, plus the Anthropic-compatible Messages (/messages) endpoint.
Rate limits apply per team, not per key: 60 RPM / 2M TPM on the free tier, 3,000 RPM / 4M TPM paid.
Full API documentation.

Setup​

Available Models​

Configuration​

Configuration Options​

Cost Tracking​

Responses API​

Messages API​

Using with coding-agent providers​

Codex CLI​

Claude Code​

Example Usage​

API Details​

See Also​