Muse Spark Open — local AI model by Meta
Written by Jakub Rusinowski · Last updated
Meta's open-weight release of its Muse Spark line, published on 15 October 2026: an 816B-total, 42B-active mixture-of-experts model that takes text, images, video and audio in, with a 1M-token context. Every expert must be resident, so even Meta's 4-bit (NVFP4) checkpoint is a 533 GB download and Meta asks for at least 700 GB of GPU memory to run it. It is a multi-GPU server model, not a desktop one. If you want Meta's weights on one consumer card, Muse Glimmer 30B is the local member of the line; Ternary Bonsai 2 27B and Qwen3.8 27B are the other single-GPU alternatives in this library.
Variants
The smallest Muse Spark Open variant needs about 497 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache.
| Model | VRAM at Q4 | VRAM | Context | Run it |
|---|---|---|---|---|
| Muse Spark Open 816B → 816B (42B active) | ~497.1 GB | 1,048,576 | cloud-hosted tag |
Memory is quantized weights plus overhead at Q4_K_M, from the same engine as the GPU & VRAM checker.
How to run Muse Spark Open locally
Install Ollama, then pull the tag.
No local Ollama tag. Ollama lists muse-spark-open only as a cloud-hosted ':cloud' tag, which runs on Ollama's servers, not your machine.
Pick a size above for its own VRAM figure, speed estimate and install command.
Licence
Weights are downloadable and commercial use is permitted, subject to the licence’s acceptable-use terms.
Applies to: Muse Spark Open 816BCan I run Muse Spark Open on my GPU?
Muse Spark Open — frequently asked questions
How much VRAM does Muse Spark Open need?
Muse Spark Open needs about 497 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Muse Spark Open 816B (497 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.
Can I run Muse Spark Open on an RTX 4090 (24 GB)?
Muse Spark Open's smallest variant needs about 497 GB, which exceeds a single RTX 4090 (24 GB). Use multiple GPUs, a higher-VRAM card, or Apple Silicon with large unified memory.
What quantization should I use for Muse Spark Open?
Q4_K_M is the best balance of quality and VRAM for Muse Spark Open in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.
How do I run Muse Spark Open with Ollama?
Muse Spark Open has no local Ollama tag — the published tag is cloud-hosted, so running it sends your prompts to a hosted GPU rather than your own machine.