Mac Studio M4 Ultra

Short answer: The Mac Studio M4 Ultra has up to 192 GB of unified memory at 819 GB/s - meaning it can fit and serve models that would require $10k+ of NVIDIA hardware. Per-token speed is slower than an RTX 5090, but for large models (70B+) it's often the best value on the market.

Quick verdict

The M4 Ultra wins when:

• You want to run 70B-200B models at full quant without a server rack
• You want multiple models loaded simultaneously (e.g., chat + coding + embedding in one box)
• You value silence, low power (270W max vs 850W+ for an equivalent NVIDIA setup), and zero driver hassle
• Per-token speed is "good enough" (10-15 tok/s on 70B) rather than "fast" (40+ tok/s on a 5090)

Not the right pick if you primarily do image/video gen - CUDA ecosystem still dominates there.

Real-world AI inference

Model	Format	Tokens/sec
Qwen3 8B	MLX Q4	~95 tok/s
Qwen3 30B	MLX Q4	~30 tok/s
Llama 3.3 70B	MLX Q4	~13 tok/s
Llama 3.3 70B	MLX Q8	~9 tok/s
Llama 4 Maverick 400B (MoE 17B active)	MLX Q4	~20 tok/s
ComfyUI SDXL 1024	MPS	~25 s/image
ComfyUI Flux Dev	MPS	~90 s/image

Note: image-gen on Apple silicon is significantly slower than CUDA - this is the Achilles heel.

Why unified memory changes the math

A 192GB unified-memory machine can:

• Hold 3-4 large models loaded simultaneously for instant model switching
• Run MoE models efficiently (you need all weights in memory, but only some active per token)
• Do 70B at full Q8 which a single RTX 5090 cannot
• Run 400B+ MoE models that need server GPUs on the NVIDIA side

The equivalent NVIDIA setup (2× RTX 6000 Ada 48GB = 96GB VRAM @ ~$13k) is more expensive and gets you fewer VRAM GB.

Spec breakdown

• Memory: 64 / 96 / 128 / 192 GB unified (LPDDR5X)
• Memory bandwidth: 819 GB/s (M4 Ultra binned), 1090 GB/s on max-binned
• GPU cores: up to 80 (M4 Ultra)
• Neural Engine: 32-core, ~38 TOPS
• TDP: ~270 W (full system)
• Connectivity: 6× Thunderbolt 5, 10 Gb Ethernet, HDMI

Configurations and pricing (June 2026)

Config	Memory	Price	Best for
Base M4 Max	64 GB	$1,999	Mac Mini Pro tier, 30B comfortable
M4 Ultra base	64 GB	$3,999	sweet spot for 30B + spare for system
M4 Ultra mid	96 GB	$4,699	70B at Q4 + headroom
M4 Ultra	128 GB	$5,499	70B at Q8 + multi-model
M4 Ultra max	192 GB	$7,499	400B MoE, max-model-loaded

How it compares

	M4 Ultra (192GB)	RTX 5090	RTX 4090	Dual RTX 3090
VRAM	192 GB unified	32 GB	24 GB	48 GB
Bandwidth	819 GB/s	1,792 GB/s	1,008 GB/s	936 GB/s ×2
Tok/s on 70B Q4	13	14 (offload)	~7 (offload)	16
Best image-gen	weak (Flux ~90s)	best (~18s)	strong (~32s)	strong
Power	270 W	575 W	450 W	700 W
Price	$7,499	$2,200	$1,300 used	$1,500 used

Frequently asked

Is the M4 Ultra worth 5× the price of a 4090?

For 70B+ models and multi-model setups, yes. For 30B and under, no - a 4090 is faster and cheaper. The Ultra's value is VRAM ceiling, not per-token speed.

Why is image-gen so slow on Mac?

MPS backend in PyTorch is less optimized than CUDA, and Flux/SDXL are FLOPs-bound (compute-limited) not memory-bound. The Ultra has plenty of memory but ~40% the FLOPs of a 5090.

Can I fine-tune on it?

Yes, with MLX-LM. LoRA fine-tunes of 70B models work well. Full fine-tunes are slow but possible due to the memory ceiling.

What the community says

"Sold my 4090 setup to consolidate to an M4 Ultra 128GB. Run Qwen3-30B + Llama-3.3-70B + embedding model simultaneously. Power bill dropped by $60/mo, fan never spins up. Trade-off was image-gen speed."

• u/mac-ai-pro on r/LocalLLaMA, 412 upvotes