Meta AIProprietary

Muse Spark 1.2 by Meta Superintelligence Labs

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Muse Spark 1.2 is the coding-focused foundation model released by Meta Superintelligence Labs on August 5, 2026, co-trained with the Muse Code terminal agent it powers. It has a 1,048,576-token context window and accepts text, image, video and PDF input. On Meta's published charts it scores 82.9% on Terminal-Bench 2.1, 59.3% on DeepSWE v1.1 and 70.6% on Meta's internal coding benchmark, up from 76.2%, 53.0% and 68.3% for Muse Spark 1.1, placing it second behind Claude Opus 5 on all three. Pricing is $1.25 per million input tokens and $4.25 per million output tokens, with a data-contributor tier more than ten times cheaper. Meta publishes no parameter count or architecture details.

Parameters

Undisclosed

Context Window

1M

License

Proprietary

Release Date

2026-08-05

API Pricing

Input Price (per 1M tokens)

$1.25

Output Price (per 1M tokens)

$4.25

Billing Mode: per 1M tokens

Strengths

  • Near Opus-tier agentic coding at a fraction of the cost (82.9% on Terminal-Bench 2.1)
  • Jointly trained with the Muse Code harness for long-horizon, multi-turn workflows
  • 1,048,576-token context with text, image, video and PDF input

Weaknesses

  • Places second behind Claude Opus 5 on all three of Meta's own coding benchmarks
  • Closed weights; no self-hosting or fine-tuning
  • No published parameter count or architecture details, limiting independent verification

Use Cases

  • Autonomous multi-step coding agents over large repositories
  • Multi-file change and refactoring automation
  • Long-running background engineering agents

Deep Analysis

Context Window

1,048,576 tokens

Accepts text, image, video and PDF input

API Price

$1.25 / $4.25 per 1M

Data-contributor tier ~10x cheaper ($0.10/$0.20)

Terminal-Bench 2.1

82.9%

With Muse Code; 2nd behind Claude Opus 5 (86.7%)

DeepSWE v1.1

59.3%

3rd, behind Opus 5 (65.0%) and GPT-5.6 Terra (64.8%)

Meta Internal Coding

70.6%

Up from 68.3% on Muse Spark 1.1

Weights

Proprietary

No self-hosting or fine-tuning; no param count published

Strengths

  • Near Opus-tier agentic coding at a fraction of the cost (82.9% Terminal-Bench 2.1).
  • Jointly trained with the Muse Code harness, so it shines on long-horizon, multi-turn workflows.
  • 1M context with text, image, video and PDF input for multimodal coding tasks.
  • A data-contributor tier ~10x cheaper lowers the barrier for experimental use.

Weaknesses

  • Places second behind Claude Opus 5 on all three of Meta own coding benchmarks.
  • Closed weights: no self-hosting, fine-tuning, or independent architecture verification.
  • No published parameter count, limiting external scrutiny.

Competitor Comparison

ModelArenaSWEGPQAPrice
Muse Spark 1.282.9% (Terminal-Bench 2.1)59.3% (DeepSWE 1.1)N/A$1.25/$4.25
Claude Opus 586.7% (Terminal-Bench 2.1)65.0% (DeepSWE 1.1)N/A$10/$50
GPT-5.6 Terra81.8% (Terminal-Bench 2.1)64.8% (DeepSWE 1.1)N/AN/A
Grok 4.581.6% (Terminal-Bench 2.1)N/AN/AN/A

Muse Spark 1.2 is Meta Superintelligence Labs coding-focused foundation model, released August 5, 2026 and co-trained with the Muse Code terminal agent it powers. A 1M-token context with text, image, video and PDF input makes it a strong, comparatively cheap agentic-coding engine, second only to Claude Opus 5 on Meta own charts.

Analysis generated: 2026-09-19