Muse Spark Open

New

meta/muse-spark-open-20261015

Meta: Muse Spark Open is a multimodal model that processes text, image, video, file, and audio inputs and generates text outputs. It has a context length of 1,048,576 tokens, costs $1.25 per million input tokens and $4.25 per million output tokens, and supports tools and reasoning. It is an open-weight model.

  • tool use
  • structured outputs
  • reasoning
  • open-weight

At a glance

providermeta
releasedOct 15, 2026
context1.0M
input / M$1.25

Specifications

What the API gives you

Context window
1.0M tokens
Max output
944K tokens
Input price
$1.25 / 1M tokens
Output price
$4.25 / 1M tokens
Cache read
$0.15 / 1M tokens
Modalities
text, image, video, file, audio → text
Knowledge cutoff
—
Released
Oct 15, 2026

Measured evidence

Public benchmark record

LMArena WebDev‡
1511 Elo2026-10-16max effort

LMArena data licensed CC-BY-4.0. Aider (Apache-2.0) and SWE-bench (MIT) are open. Design Arena uses blind human preference. ‡ Submitted scaffold plus model result. Compare the harness and effort settings, not only the model name.

Open-weight model on Hugging Face.

Task evidence

How broad is the support?

Each status is exact to this model version and the selected task. Official release claims remain provisional.

  • Best LLM for Code CompletionProvisional evidence

    36% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from Aider Polyglot or LiveBench Coding. 3 of 3 configured evaluation feeds currently have results.

  • Best LLM for Frontend & UIProvisional evidence

    27% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from Design Arena Coding or Design Arena UI. 6 of 6 configured evaluation feeds currently have results.

  • Best Local LLM for CodingProvisional evidence

    21% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from Aider Polyglot or LiveBench Coding. 4 of 4 configured evaluation feeds currently have results.

  • Best LLM for CodingProvisional evidence

    20% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from Aider Polyglot or Design Arena Coding. 7 of 7 configured evaluation feeds currently have results.

  • Best LLM for Debugging & Code ReviewProvisional evidence

    17% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from Aider Polyglot or LiveBench Coding. 5 of 5 configured evaluation feeds currently have results.

Recommendation coverage

Where this model appears

Not currently included in a published recommendation. The task evidence panel above says exactly what is confirmed and what is still missing.

Catalog data via OpenRouter and models.dev. Last checked within the past 6 hours.