Muse Spark Open API

Meta's open-weight coding model, trained for agentic coding workflows with reliable tool calling and deep codebase understanding, with a 1M-token context window.

Modalities
Text, Image, VideoText
In / Out price
$1.32/$4.5per 1M
Context window
1.05M tokens
Released
Oct 15, 2026

Muse Spark Open overview

The pelican test: one prompt, every text model, unedited SVG output from Nov 3, 2026.

SVG of a pelican riding a bicycle, written by Muse Spark Open through AI/ML API

Muse Spark Open by Meta

Send text, images, video, audio or PDF documents to the chat completions endpoint and receive text.

Muse Spark Open specs

Model ID
meta/muse-spark-open
Developer
Meta
Context window
1,048,576 tokens
Max output
943,718 tokens
Input
Text, Image, Video
Output
Text
API
OpenAI-compatible, base URL https://api.aimlapi.com/v1

What Is Muse Spark Open?

Muse Spark Open is an open-weight model from Meta optimized for coding. It is trained for agentic coding workflows, in which a model reads a codebase, calls tools and acts on what they return, and Meta positions it on two properties: reliable tool calling and deep codebase understanding. It was released on 15 October 2026 and is available on AI/ML API as meta/muse-spark-open.

The model belongs to Meta's Muse Spark line. Muse Spark 1.3 is the general-purpose API model of that line, and Muse Wonder is Meta's frontier agentic model; Muse Spark Open is the variant published with open weights and tuned for coding.

Specifications

  • Context window: 1,048,576 tokens
  • Input: text, images, video, audio and PDF documents, output: text
  • Capabilities: reasoning, tool calling, vision, file input, streaming

What It Is Built For

The model targets coding agents rather than single-turn code completion. A 1M-token context window lets an agent keep a large part of a repository, its tool outputs and the conversation history in one request, and reasoning tokens let the model plan a change before it makes it. Image, video and PDF input cover the material that sits around code: screenshots of a UI, recordings of a bug, design documents and specifications.

Use cases

Coding agents that work across a repository: reading the relevant files, calling tools such as a shell, a test runner or a search index, and editing code based on what those tools return.

Large-context code tasks, such as reviewing a long diff, answering questions about an unfamiliar codebase or planning a refactor with most of the project in the prompt.

Debugging from mixed inputs, where the model gets a stack trace together with a screenshot, a screen recording or a PDF specification of the expected behaviour.

Teams that want an open-weight Meta model for coding work and use the hosted endpoint for development or overflow capacity.

Capabilities

  • File input
  • Reasoning
  • Streaming
  • Function calling
  • Vision

Muse Spark Open benchmarks by Artificial Analysis

See how Muse Spark Open compares in intelligence, generation speed, cost per task and latency. Data retrieved Nov 3, 2026.

Intelligence

Index v5.0

Speed

Output tokens / second

Cost per task

USD / benchmark task

Benchmark results

Compare 6 models available on AI/ML API across 5 independent benchmarks.

Humanity's Last Exam

Expert-written questions across academic subjects.

Muse Spark Open API pricing

Muse Spark Open pricing in US dollars
UsagePriceUnit
Input$1.321M tokens
Output$4.51M tokens
Cached input$0.15871M tokens

Prices from the AI/ML API price list, checked on Nov 4, 2026.

Muse Spark Open vs other models: token prices

AI/ML API input and output rates for 5 models, per million tokens.

AI/ML API model prices in USD per million tokens
ModelInputOutput
Muse Spark Open$1.32$4.5
Muse Glimmer 30B$0.3703$1.59
Muse Spark 1.3$1.32$4.5
Muse Spark 1.2$1.32$4.5
Muse Wonder$4.23$21.16

How to use the Muse Spark Open API

View docs

Build with your agent

Give your agent the model details, code and documentation.

1Get your API key

Create API key
export AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"

2Make your first request

curl 'https://api.aimlapi.com/v1/chat/completions' \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
  "model": "meta/muse-spark-open",
  "messages": [
    {
      "role": "user",
      "content": "Write a haiku about the ocean."
    }
  ]
}'

Muse Spark Open FAQ

Is Muse Spark Open available on AI/ML API?

Yes. Muse Spark Open is live on AI/ML API as meta/muse-spark-open, through the chat completions endpoint.

What is the context window of Muse Spark Open?

Muse Spark Open has a 1,048,576-token context window and can return up to 943,718 tokens.

What inputs and outputs does Muse Spark Open support?

It accepts text, images, video, audio and PDF documents and returns text. Reasoning, tool calling and streaming are supported.

How is Muse Spark Open different from Muse Spark 1.3?

Muse Spark Open is the open-weight member of Meta's Muse Spark line and is trained specifically for agentic coding, with an emphasis on tool calling and codebase understanding. Muse Spark 1.3 is the general-purpose model of the line. On AI/ML API both are billed at the same per-token rate.

How much does Muse Spark Open cost?

Muse Spark Open costs $1.32 input and $4.5 output per 1M tokens on AI/ML API, billed as you go with no subscription.

What is Muse Spark Open good at?

Meta trained it for agentic coding: multi-step work in which the model reads a codebase, calls tools and edits code based on the results. Its 1M-token context window fits a large part of a repository in a single request.

What is the Muse Spark Open model ID?

Use meta/muse-spark-open as the model parameter. Requests go to the OpenAI-compatible endpoint with your AI/ML API key.

Start building with Muse Spark Open

Muse Spark Open API

meta/muse-spark-open

Build with your agent

Give your agent the model details, code and documentation.

1Get your API key

Create API key
export AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"

2Make your first request

curl 'https://api.aimlapi.com/v1/chat/completions' \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
  "model": "meta/muse-spark-open",
  "messages": [
    {
      "role": "user",
      "content": "Write a haiku about the ocean."
    }
  ]
}'