Meta Model API

Everruns runs Muse models through Meta Model API. The dedicated meta driver uses Meta’s OpenAI-compatible Responses API at https://api.meta.ai/v1, including streaming, parallel tool calls, reasoning replay, message phases, hosted tool search, and server-managed response history.

Configure in Everruns

Create an API key in the Meta Model API dashboard.
Go to Settings → Providers and click Add provider.
Choose Meta Model API, paste the key, and save.
Sync models to import the Muse models available to your team.

The hosted endpoint is used by default. An optional base URL can point the driver at a compatible proxy; model discovery is disabled for non-Meta hosts.

Muse Spark 1.3 tiers

Muse Spark 1.3 is built for long-horizon coding and multi-step agentic work, with native tool calling and MCP support. Both 1.3 model IDs have a 1,048,576-token context window and accept text, images, audio, video, and PDFs while producing text.

Model	Data use	Input / cached input / output per million tokens
`muse-spark-1.3`	Prompts and completions are not used to train Meta models	$1.25 / $0.15 / $4.25
`muse-spark-1.3-contributor`	Prompts and completions are used to train and improve Meta models; rate-limited by tokens	$0.10 / $0.002 / $0.20

Choose the Contributor model only when the organization accepts its data-use terms. The distinction is part of the model ID, so changing tiers is an explicit model selection rather than a hidden provider setting.

The previous muse-spark-1.2 and muse-spark-1.2-contributor IDs remain available with the same tiers and pricing.

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