Run Meta's Muse Spark Open locally on a big Mac
Hugging Face's launch post shows how to run Muse Spark Open on Apple silicon through llama.cpp or MLX. It is a very large model, so even the 3-bit MLX quant needs more than 256 GB of RAM. Hugging Face reports about 21 tokens a second on an M3 Ultra with 512 GB. Reasoning can't be switched off, so set it to low for easy tasks to save tokens.
Why it matters
It tells you up front what hardware you really need, before you spend a day downloading weights.
Who it's for
Mac users with high-memory Apple silicon who want to run models locally.
How to try it
- Check you have the memory: a 2-bit quant used about 304 GB and the 3-bit MLX quant about 344 GB in Hugging Face's tests.
- With llama.cpp: llama serve -hf ggml-org/Muse-Spark-Open-816B-A42B-GGUF:Q2_K, then open the built-in web UI on localhost.
- With MLX: mlx_lm.generate --model mlx-community/Muse-Spark-Open-816B-A42B-oQ3e --prompt "..."
- If you don't have that hardware, use a hosted provider instead (see the Muse Spark Open item).
Plan & availability: Free open weights; needs well over 256 GB of RAM even at 3-bit.
Source: @huggingface on huggingface.co ↗
Written by AgentStackList from the original post. Checked Oct 17, 2026. Features, plans and availability can change, so confirm on the source before you rely on it.
muse-spark-openlocalmlxllama-cppopen-weights
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