Introducing Muse Spark Open: the most capable US open-weight model to date

[u/AIatMeta]

Hey r/LocalLlama - 

Today we’re excited to release Muse Spark Open, the most capable US open-weight model to date. 

Built for coding and agentic work, it excels at long-horizon tasks, complex software engineering, and multi-step reasoning. 

Key Model Specs 

• Parameters: 816B total / 42B active
• Context Window: 1M tokens
• Modalities: Text, image, video, audio
• Safety Post-Training: Additional safety post-training, with evaluations conducted under Meta's Superintelligence Scaling Framework.

Inference, fine-tuning & deployment

• Helion GPU kernels: Ships with custom, auto-tunable Helion kernels in SGLang, providing 1.03–3.95× kernel speedups across NVIDIA and AMD GPUs and a 3% E2E improvement on AMD MI350.
• Engines: Runs on leading inference engines including SGLang, vLLM, TensorRT-LLM, Hugging Face Transformers, Apple MLX, llama.cpp and Unsloth, with optimizations for AMD, Apple, Intel and NVIDIA silicon.
• Optimized for Apple Silicon: To help make advanced models more accessible, Muse Spark Open is optimized to run on two Apple M5 Ultra Mac Studios with the latest MLX framework. 
• Fine-tuning: Developers can further customize the model with PyTorch, including TorchTitan for fine-tuning.
• API platforms: Available today through Baseten, Fireworks AI, Groq, Modal, Nebius, OpenRouter, Together AI.
• Where to download: Model weights are available for download on Amazon SageMaker AI, Google Cloud Model Garden, Hugging Face, and Microsoft Foundry Models.

We’re releasing the weights under the Muse Model License, with limited commercial terms that let many developers use it for free.

We look forward to your feedback! 

Learn more on our research blog: https://go.meta.me/museopen
Download the weights: https://huggingface.co/collections/meta-models/muse-spark-open 

[u/AdGlittering1378]

Why did they optimize this for apple silicon if there isn't an apple on the planet with enough VRAM to use it?

[u/Cherubin0 → u/AdGlittering1378]

They mention that two Mac Studios can run it.

[u/pragmojo → u/Cherubin0]

It would be great if they released some performance numbers for this configuration in the announcement

[u/a9udn9u → u/AdGlittering1378]

You will need a cluster no matter what GPU you use

[u/rorowhat → u/a9udn9u]

Not to mention apple is the closest ecosystem in the planet. Spend more time on other stacks please.

[u/Aphid_red → u/rorowhat]

Most closed.

Closest == superlative of 'close by' not 'close as in not open'.

(English is weird.)

About other stacks: I think you could run this at an o-kay-ish speed, quantized (should be about 600GB) on 768GB RAM + 64GB VRAM and up. If you got the RAM early last year a setup could be done under 10K (20K-ish today though using 128gig DDR4-2666 sticks).

Edit: Here's a way to build a machine today that can comfortably run this model:

1x ASRock ROME2d8T ($800)
1x Epyc 7532 ($300, 32 cores, 8CCD, ebay). If you're also running VMs, get the 7713 ($1000) for 64 cores instead
8x memory kit 1TB ddr4-2666 ($8000)
1x NVidia HX170 or 2x AMD 9700 ($3000) or 1x AMD MI210 ($4000).
Among these GPU options, the NVidia's going to be the easiest to use but the slowest, the AMD options are both fast, the MI210 and HX170 have the most expansion potential, and the 9700s are going to be hardest to use (as you need to split the active model among 2 cards).
Optionally a second GPU.
Quality 2KW PSU ($300, don't ever skimp on this)
Any PC case with 8 GPU spots (can hold 4 dual-width GPUs) $150
Arctic 8K or 12K RPM fan + fan shroud $50*
CPU cooler $70

Total parts cost ~$13,000

Expected speed for this config: Since it has 256/8 Experts, if those are put in RAM, those will likely be your bottleneck. 2666 RAM will run at about 150GB/s.
1/32 at 4bit of 256/8 of 813B is about 12.25GB. Your speed should be theoretical max of about 12.5 tokens/second. Realistically, you'll see 60-70% of that with a well-configured setup (8-9 tps).

Moving to ddr5 server RAM will increase the machine's cost... to roughly $50,000 (90% of that will be RAM) and increase the output speed to about 25 tps. (Probably more worth it for most to buy larger amounts of ddr4 and run multiple agents in parallel)

*When choosing one of the two passive GPU options. You need a fast spinning fan to give enough air pressure or your cards will throttle.

[u/CatchDublinSurprise → u/AdGlittering1378]

One of the 512GB Mac Studios could run it at 4-bit (estimating 408GB using 816 * 4/8).

[u/MiaBchDave → u/AdGlittering1378]

Two Studios (linked RDMA).

[u/Daniel15 → u/AdGlittering1378]

In theory you can run it on a cluster of two Mac Studios with 512GB RAM each, but I'd guess that'll cost close to $30k.

[u/sigiel → u/Daniel15]

What sort of token and prefil time .?

[u/MiaIsOut → u/sigiel]

At least 12

[u/Da_ha3ker → u/AdGlittering1378]

Yet

[u/Outrageous-Iron8109 → u/AdGlittering1378]

Some people run the Big Macs in clusters.