Can the M3 Ultra 96GB run gpt-oss-120b?

Q4 (~73.6GB) exceeds the ~72GB usable; drop to Q3_K_M (~60GB) for a tight fit at a theoretical ~240 tok/s (only 5.1B active MoE params). The A6000's 48GB cannot hold it at all.

M3 Ultra vs A6000 on 70B — which is faster?

Nearly identical: 819 vs 768 GB/s, theoretically ~14 vs ~13 tok/s on 70B Q4 — both 'readable' pace. The difference: the M3 Ultra runs Q6_K comfortably while the A6000 is stuck at tight Q4.

Is the $5,299 M3 Ultra worth it?

For exactly one buyer: someone needing 60-72GB usable VRAM who refuses multi-GPU ops. The June 2026 +$1,300 reprice hurt value; for plain 70B Q4, a $2,800 used A6000 or dual 3090s are far cheaper.

GPU Comparisons / Mac Studio M3 Ultra (96GB) vs RTX A6000

Mac Studio M3 Ultra (96GB) vs RTX A6000 for Local LLMs: Which Should You Pick

Verdict

Need 60-72GB capacity with zero ops: Mac Studio M3 Ultra. Want the CUDA ecosystem at half the price: RTX A6000 — but its 48GB stops at a ceiling-tight 70B Q4.

Spec Comparison

	Mac Studio M3 Ultra (96GB)	RTX A6000
Nominal VRAM	96 GB	48 GB
Usable VRAM (for models)	72.0 GB	48.0 GB
Memory bandwidth	819 GB/s	768 GB/s
Type	Unified memory	Discrete GPU
Release year	2025	2020
MSRP	$5,299	$4,650
Used reference price	—	$2,800
TDP	100 W	300 W

Apple unified memory is counted at 75% usable for models (the rest serves the system/display).

Model Verdict Matrix (Q4_K_M @8K)

Model	VRAM needed	Mac Studio M3 Ultra (96GB)	Theoretical speed	RTX A6000	Theoretical speed
Llama 3.2 3B	4.4 GB	Comfortable	≈312	Comfortable	≈293
Llama 3.1 8B	7.5 GB	Comfortable	≈125	Comfortable	≈117
Qwen3 8B	7.7 GB	Comfortable	≈122	Comfortable	≈115
Phi-4 14B	12.2 GB	Comfortable	≈68	Comfortable	≈64
Mistral Small 3.2 24B	17.5 GB	Comfortable	≈42	Comfortable	≈39
Gemma 3 27B	22.4 GB	Comfortable	≈37	Comfortable	≈34
Qwen3.8 27B	20.7 GB	Comfortable	≈36	Comfortable	≈34
Muse Glimmer 30B	20.1 GB	Comfortable	≈34	Comfortable	≈32
Qwen3 30B-A3B	21.0 GB	Comfortable	≈304	Comfortable	≈285
Qwen3 32B	23.7 GB	Comfortable	≈31	Comfortable	≈29
gpt-oss-20b	14.7 GB	Comfortable	≈279	Comfortable	≈261
Llama 3.3 70B	47.4 GB	Comfortable	≈14	Tight fit	≈13
gpt-oss-120b	73.6 GB	Needs multi-GPU	—	Not feasible	—
DeepSeek-R1 671B	413.1 GB	Not feasible	—	Not feasible	—

Highlighted rows = watershed models where the two cards' verdicts differ. Theoretical speed = bandwidth × 0.75 ÷ per-token weight bytes (active params for MoE); real-world results vary with framework/driver/CPU, ±30%. Speed is hidden for multi-GPU/infeasible verdicts.

Value Comparison

	Mac Studio M3 Ultra (96GB)	RTX A6000
Bandwidth per dollar	0.15 GB/s/$	0.27 GB/s/$
Usable VRAM per dollar	0.014 GB/$	0.017 GB/$

Pricing basis: Mac Studio M3 Ultra (96GB) = MSRP (no used price yet); RTX A6000 = used reference price; used prices are market estimates, see analysis for volatility.

Analysis

Capacity decides first: the M3 Ultra's 96GB unified memory yields ~72GB usable at the 75% rule — 70B runs at Q6_K (~62GB) comfortably, and gpt-oss-120b at Q3_K_M (~60GB) is a tight fit. The A6000's 48GB leaves 70B Q4 (~47.4GB) pressed against the ceiling and gpt-oss-120b entirely out. The matrix watershed is clear: llama-3.3-70b comfortable vs tight, gpt-oss-120b needs-multi vs infeasible.

Speed is a draw while the experience splits: 819 vs 768 GB/s is close, 70B Q4 theoretically ~14 vs ~13 tok/s — both 'readable' pace; the M3 Ultra edges ahead on MoE (gpt-oss-120b Q3 ~240 tok/s). But ~100W vs 300W whole-system draw, silent desktop vs workstation fans, macOS out-of-box (MLX and llama.cpp Metal are both mature) vs a self-built Linux/CUDA stack. Price is the real pain: the M3 Ultra launched at $3,999 and was repriced to $5,299 on 2026-06-25, with the 256/512GB versions discontinued since March 2026 — 96GB is Apple's single-machine ceiling; a used A6000 at ~$2,800 costs half.

Verdict: developers or small teams needing 60GB+ usable VRAM for 120B-class MoE who refuse multi-GPU ops — the M3 Ultra is nearly the only answer (the CUDA-side counterpart is dual A6000s, 96GB at $5,600+ plus ops); if your target stops at 70B Q4 and you can't leave CUDA (vLLM, occasional fine-tuning), the A6000 delivers at half the price. Also note the M3 Ultra's memory can never be upgraded, while a second A6000 can be added later.

FAQ

Can the M3 Ultra 96GB run gpt-oss-120b?: Q4 (~73.6GB) exceeds the ~72GB usable; drop to Q3_K_M (~60GB) for a tight fit at a theoretical ~240 tok/s (only 5.1B active MoE params). The A6000's 48GB cannot hold it at all.
M3 Ultra vs A6000 on 70B — which is faster?: Nearly identical: 819 vs 768 GB/s, theoretically ~14 vs ~13 tok/s on 70B Q4 — both 'readable' pace. The difference: the M3 Ultra runs Q6_K comfortably while the A6000 is stuck at tight Q4.
Is the $5,299 M3 Ultra worth it?: For exactly one buyer: someone needing 60-72GB usable VRAM who refuses multi-GPU ops. The June 2026 +$1,300 reprice hurt value; for plain 70B Q4, a $2,800 used A6000 or dual 3090s are far cheaper.

Related guides

Data verified 2026-09-01