Muse Spark Open
The most capable US open-weights model: multimodal in, 1M context, runs on your own hardware.
Overall Intelligence
#20
of 56
8.2 pts behind #1
0
races led
0
weeks at #1
80.5
score
- Released
- Oct 15, 2026
- 4 days ago
- Context
- 1M
- 64K max output
- Price
- $0.6 / $2.4
- per 1M in/out · $1.05 blended
- Speed
- 125 tok/s
- 1.4s to first token
- Modalities
- text · image · audio · video
- outputs text
- Weights
- Open
- ~816B MoE (~42B active)
The 30-second version
The most capable US open-weights model. Muse Spark Open takes text and images, handles 1M tokens of context and runs on your own hardware.
- 1Leads the open-weights pack from US labs in our current snapshot.
- 2Self-host for privacy, customisation and fine-tuning.
- 3Multimodal input and a 1M-token context.
- 4Behind the closed frontier by several points on the hardest tasks.
What you need to know
Purpose
Give developers a frontier-adjacent model they can own, fine-tune and deploy anywhere.
What Meta optimised for
Open, efficient and fine-tunable, with permissive-enough licensing for most companies.
Unique strengths
- Open weights with multimodal input.
- Efficient inference.
- Fine-tuning friendly.
Where it ranks
Current snapshot · illustrative scores · click any race to watch it
Spark OpenBest on each axis
Overall
Coding
Hard Reasoning
Math
Science
Writing & Language
Multimodal
Tool Use & Agents
Overall Intelligence over time
Best use cases
01
Private deployments
Regulated data that cannot leave your infrastructure.
02
Fine-tuned specialists
Domain models for legal, medical or support use.
03
Edge and on-prem
Running close to users or data.
Strengths
Openness
Weights available for self-hosting and customisation.
Weaknesses
Frontier gap
Several points behind the closed leaders on hard reasoning.
When to choose it, and when not to
Pick something else when…
- You need the absolute best quality and do not need to self-host.
Update history
The distilled version first; open any release for the deeper breakdown.