System · desktop

Mac Studio M2 Ultra 192 GB

Runs models up to ~240B parameters at 4-bit in unified memory. 192 GB unified memory for very large quantized models.

Unified memory: 192 GB
System RAM: Shared
Runs: 18 of 19model variants, 8K
Estimated cost: ~$6,600

What it runs

Largest models that fit without spilling into system memory, at an 8K contextHow much text the model can consider at once, counted in tokens — roughly ¾ of a word each..

Everything →

Variant
Llama 3.1 70B Instruct
70.6B · Q4_K_M via llama.cpp
Runs well
~12 tok/s est.
Variant
Llama 3.3 70B Instruct
70.6B · Q4_K_M via llama.cpp
Runs well
12.1 tok/s measured
Variant
Mixtral 8x7B Instruct v0.1
46.7B · Q4_K_M via llama.cpp
Runs well
~62 tok/s est.
Variant
Qwen2.5 32B Instruct
32.8B · Q5_K_M via llama.cpp
Runs well
~22 tok/s est.
Variant
Qwen2.5-Coder 32B Instruct
32.8B · Q8_0 via llama.cpp
Runs well
~15 tok/s est.
Variant
DeepSeek-R1-Distill-Qwen-32B
32.8B · Q4_K_M via llama.cpp
Runs well
~25 tok/s est.
Variant
Qwen3 30B-A3B
30.5B · Q8_0 via llama.cpp
Runs well
~129 tok/s est.
Variant
Gemma 3 27B IT
27.4B · Q4_K_M via llama.cpp
Runs well
~30 tok/s est.
Variant
Gemma 2 27B IT
27.2B · Q4_K_M via llama.cpp
Runs well
~30 tok/s est.
Variant
Mistral Small 24B Instruct 2501
23.6B · Q6_K via llama.cpp
Runs well
~26 tok/s est.

Components

1× Hardware Apple M2 Ultra (76-core GPU) soc

Measured performance

Model · quantization	Runtime	Context	Measurements	Source
Llama 3.3 70B Instruct Q4_K_M (LM Studio Community)	llama.cppmetal · b4600	4K	135 tok/s · Prompt processing (512) 12.1 tok/s · Generation (128)	Mutinai illustrative fixtures

Community results

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Reviews

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