Current model · Meta
Muse Spark Open benchmarks, pricing and specs
Muse Spark Open is a Meta model released on October 15, 2026 that takes text, image, video and audio input and produces text. Its price is not published and accepts up to 1,000,000 tokens of context.
- Context window
- 1M#26 of 64 current models
Data verified October 23, 2026 · Dataset 2026-10-23
Specs
Key facts
- Provider
- Meta
- Model family
- Muse Spark
- Release date
- October 15, 2026
- Status
- Current
- Access
- open weights
- API model id
- Not reported
- Context window
- 1,000,000 tokens
- Max output
- Not reported
- Input
- text, image, video, audio
- Output
- text
- Task families
- text, multimodal
- Declared capabilities
- reasoning, agentic coding, image understanding, video understanding, audio understanding
Charts
Against every current text model
Where Muse Spark Open lands among the current models of its task, on every independent benchmark, on price and on context.
Where it stands
Muse Spark Open is no longer a current model, so it is not ranked; each bar is the share of today's text models its value beats. Each bar is the share of current models it beats.
Price and context
Context window
#26of 64
1M tokens · longer than 22%
Benchmarks
Independent benchmark results
Scores come from independent evaluators that ran the model themselves, pinned to a dated snapshot. Rank is among current models in the same snapshot. Meta's own launch figures are listed under strengths with the publisher named, because they are not measured the same way.
No independent benchmark has published a result for Muse Spark Open yet. It is still compared below on price, context and capabilities.
Fit
Strengths, cautions and best uses
- Strengths
- An 816B mixture-of-experts model with 42B active parameters and a 1M-token context that takes text, image, video and audio input
- Meta reports 89.0% on GPQA Diamond and 76.4% on Terminal-Bench 2.1 at its highest reasoning setting
- Weights on Hugging Face, Amazon SageMaker AI, Google Cloud Model Garden and Microsoft Foundry, with hosted access through Together AI, Fireworks, Groq and OpenRouter
- Cautions
- The Muse Model License limits commercial use; it is not an open-source licence
- Meta does not serve it on its own Model API, so hosted prices come from third parties
- Self-hosting needs at least 700GB of GPU memory in NVFP4 or 2TB in BF16, and no independent benchmark score is recorded here yet
- Best for
- Self-hosted coding and agent work on owned infrastructure
- Long-context multimodal analysis where data must stay in-house
From benchmark to production
Building on Muse Spark Open?
Public scores rarely hold on your own data. We test it against the alternatives on your real tasks, then build the agent or pipeline around the model that wins.
Alternatives
Alternatives to Muse Spark Open
The closest current text models by price. The cheapest model that scores as well or better is listed first; failing that, the cheapest one within 3% of the benchmark's scale.
Nemotron 3.5 Bolt 74B-A9B
- 262K context window vs 1M
- From NVIDIA
Nemotron 3.5 Super VL
- From NVIDIA
Beam 1.0
- From Reflection AI
Muse Wonder
FAQ
Muse Spark Open FAQ
What is the context window of Muse Spark Open?
Muse Spark Open accepts up to 1,000,000 tokens of context. That ranks #26 of 64 current text models by context length.
Is Muse Spark Open open source or API only?
Muse Spark Open is released as open weights that you can run yourself.
What are the best alternatives to Muse Spark Open?
The closest current alternatives by price and measured performance are Nemotron 3.5 Bolt 74B-A9B (262K context window vs 1M), Nemotron 3.5 Super VL (from NVIDIA), Beam 1.0 (from Reflection AI) and Muse Wonder.
Sources
Sources
- Introducing Muse Spark Open · Meta · official · verified October 23, 2026
- Muse Spark Open model card · Meta · official · verified October 23, 2026
Cite this page
Van Data Team. "Muse Spark Open Benchmarks, Pricing and Specs." AI Model Benchmark Dataset 2026-10-23. https://vandatateam.com/ai-model-benchmarks/muse-spark-open
Reuse the data: JSON · CSV · or explore every model in the AI model benchmark comparison.
Production evaluation
Deciding whether Muse Spark Open fits your workload?
Public benchmarks narrow the shortlist. We test the finalists on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.
- Evaluation cases and acceptance thresholds tied to real work
- Model routing, fallbacks and cost controls