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2x Mac Studio M5 Ultra cluster (Thunderbolt 5 RDMA): Muse Spark Open 816B

GPU(s)2x Apple M5 Ultra (unified, Mac Studio)
VRAM / unified memory (GB)
CPU2x Apple M5 Ultra
Motherboard
RAM
PSU
OtherTwo Mac Studios linked by two Thunderbolt 5 cables (RDMA over Thunderbolt, macOS 26.2+, MLX jaccl backend)
Reported total cost
Power

Measured speed (generation tokens/sec)

ModelQuantEnginetok/s
Muse Spark Open 816B-A42BNVFP4, 8,192-token contextMLX, 2-node tensor parallel24.99
Muse Spark Open 816B-A42BNVFP4, 8,192-token contextMLX, 2-node pipeline parallel15.74
Mistral Medium 3.5 128BFP8, 8,192-token contextMLX, 2-node tensor parallel13.69
Qwen3.8 27BBF16, 8,192-token contextMLX, 2-node tensor parallel33.27

Apple Machine Learning Research, 15 Oct 2026 (vendor benchmark, single user, 128 generated tokens). Apple does not state the memory of each Mac in the cluster runs; Muse Spark Open needs ~493 GB in NVFP4 so it does not fit one machine.

Source: https://machinelearning.apple.com/research/mlx-distributed-inference

Blank fields = not stated in the source. We never estimate build data; GPU street prices above are separately sourced and dated.

Rent before you buy: try this model on a cloud GPU for a few dollars first: RunPod

Quick answers: Can 2x Apple M5 Ultra run Mistral Medium 3.5 128B? · Can 2x Apple M5 Ultra run Muse Spark Open 816B-A42B? · Can 2x Apple M5 Ultra run Qwen3.8 27B?