What AI models can the Intel Core Ultra 7 255H / 9 285H NAS (64 GB) run?

Unified memory: 64.0 GB
Usable for models: 36.5 GB
Memory bandwidth: 102 GB/s
Runs models on: GPU (Vulkan)
Released: 2025

494 / 622 LLMs run Best: Qwen3.6 35B-A3B 61 / 61 Image models run Best: Z-Image Turbo 41 / 43 Video models run Best: Bernini-R A14B (video generation + editing) 69 / 70 Decision models run Best: Jina Reranker v3.5

A NAS with this chip can run models on its GPU (Vulkan), sharing system memory with the NAS. We plan around 36.5 GB for models, what is left after the NAS system and its storage services. Models run in a container (Docker) or the maker’s app store, and speeds assume the NAS isn’t busy with storage work.

More about this hardware

Maker	Intel
Type	NAS (network attached storage) processor
GPU share of memory	57% (what the GPU can typically be given for a model)
Chip	Intel Core Ultra 7 255H / 9 285H
AI accelerator	Intel Arc 140T integrated graphics, sharing system memory.
NAS models with this chip	Topton N25 14-bay dual-10GbE NAS motherboard (Core Ultra 5 225H / 7 255H / 9 285H) · UGREEN NASync iDX6011 Pro
Memory type	System RAM, shared with the NAS operating system and its storage services
Bandwidth figure	102.4 GB/s, estimated, see the note below
Note	One profile for every NAS built on this chip. Memory speed is an estimate from the chip’s supported memory in a typical NAS fitting; a unit with one memory module runs slower than one with two. Speed assumes the NAS is not busy with storage work.
Specifications	www.toptonpc.com

Apps that run models well on the Intel Core Ultra 7 255H / 9 285H NAS (64 GB)

Linux

For a typical model that fits in memory. Each model page picks the best app for that model on this hardware. All apps

2 products with the Intel Core Ultra 7 255H / 9 285H NAS (64 GB)

N25 14-bay dual-10GbE NAS motherboard (Core Ultra 5 225H / 7 255H / 9 285H)Topton · NAS · 32 or 64 GB · $791Product page (opens in a new tab)
NASync iDX6011 ProUGREEN · NAS · 64 GB · $6,000Product page (opens in a new tab)

Best LLMs for the Intel Core Ultra 7 255H / 9 285H NAS (64 GB)

Quality	Model	Quant	Memory	Speed	Runs
88Excellent quality (A+) · 88 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 94/100 (quality, fit, speed and memory use) sets the ranking.	Qwen3.6 35B-A3BAlibaba	`Q4_K_M`	25.6 GB	35.8 tok/s	Runs great
88Excellent quality (A+) · 88 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 94/100 (quality, fit, speed and memory use) sets the ranking.	MiniCPM-V 4.7 35B-A3BOpenBMB	`Q4_K_M`	25.2 GB	35.8 tok/s	Runs great
88Excellent quality (A+) · 88 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking.	Qwen3.5 35B-A3BAlibaba	`Q4_K_M`	25.6 GB	35.8 tok/s	Runs great
87Excellent quality (A+) · 87 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking.	Nex N2 Mini (35B-A3B)Nex-AGI	`Q4_K_M`	25.1 GB	35.8 tok/s	Runs great
85Excellent quality (A+) · 85 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking.	Flint (40B-A2.5B)Recursive	`Q4_K_M`	28.0 GB	42.0 tok/s	Runs great
86Excellent quality (A+) · 86 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking.	KAT-Coder V2.5 Dev (35B-A3B)Kuaishou	`Q4_K_M`	24.8 GB	35.8 tok/s	Runs great
86Excellent quality (A+) · 86 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking.	Sage-A1.5 35B-A3BInternScience	`Q4_K_M`	25.6 GB	35.8 tok/s	Runs great
85Excellent quality (A+) · 85 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking.	Ornith 1.5 35B-A3BDeepReinforce	`Q4_K_M`	25.6 GB	35.8 tok/s	Runs great
84Great quality (A) · 84 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking.	Apodex 1.1 Mini (35B-A3B)Apodex	`Q4_K_M`	25.6 GB	35.8 tok/s	Runs great
84Great quality (A) · 84 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking.	Ornith 1.0 35B-A3BDeepReinforce	`Q4_K_M`	25.6 GB	35.8 tok/s	Runs great
82Great quality (A) · 82 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking.	Agents-A1 35B-A3BInternScience	`Q4_K_M`	25.1 GB	35.8 tok/s	Runs great
82Great quality (A) · 82 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking.	Qwen AgentWorld 35B-A3BAlibaba	`Q4_K_M`	24.8 GB	35.8 tok/s	Runs great

Best Image models for the Intel Core Ultra 7 255H / 9 285H NAS (64 GB)

Quality	Model	Quant	Memory	Speed	Runs
84Great quality (A) · 84 of 100: how capable the model is at FP16, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.	Z-Image TurboAlibaba (Tongyi)	`FP16`	22.7 GB	23 s	Runs well
85Excellent quality (A+) · 85 of 100: how capable the model is at FP16, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.	ERNIE-Image TurboBaidu	`FP16`	26.4 GB	30 s	Runs well
82Great quality (A) · 82 of 100: how capable the model is at FP8, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.	FLUX.2 [klein] 9BBlack Forest Labs	`FP8`	19.9 GB	15 s	Runs well
91Excellent quality (A+) · 91 of 100: how capable the model is at FP16, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.	FLUX 3 Image KleinBlack Forest Labs	`FP16`	22.4 GB	53 s	Slow
78Great quality (A) · 78 of 100: how capable the model is at FP16, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.	FLUX.2 [klein] 4BBlack Forest Labs	`FP16`	18.1 GB	9.3 s	Runs great
90Excellent quality (A+) · 90 of 100: how capable the model is at FP8, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking.	Krea 2 TurboKrea	`FP8`	20.2 GB	36 s	Runs well

Best Video models for the Intel Core Ultra 7 255H / 9 285H NAS (64 GB)

Quality	Model	Quant	Memory	Speed	Runs
83Great quality (A) · 83 of 100: how capable the model is at FP8, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking.	Bernini-R A14B (video generation + editing)ByteDance	`FP8`	26.0 GB	1.7 h	Very slow
66Good quality (B) · 66 of 100: how capable the model is at FP8, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking.	LTX-Video 13B 0.9.8 (distilled)Lightricks	`FP8`	30.1 GB	8.4 min	Runs well
86Excellent quality (A+) · 86 of 100: how capable the model is at FP8, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking.	LTX-2.5 (22B, video + audio)Lightricks	`FP8`	35.2 GB	13.4 min	Slowtight fit · encoder unloaded after use
78Great quality (A) · 78 of 100: how capable the model is at FP8, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking.	SCAIL-2 14B (character animation)Zhipu AI	`FP8`	29.8 GB	2.8 h	Very slow
74Great quality (A) · 74 of 100: how capable the model is at FP8, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking.	HY-OmniWeaving (8.3B, unified video)Tencent	`FP8`	24.6 GB	74.2 min	Very slow

Best Decision models for the Intel Core Ultra 7 255H / 9 285H NAS (64 GB)

Quality	Model	Quant	Memory	Speed	Runs
86Excellent quality (A+) · 86 of 100: how capable the model is at F16, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking.	Jina Reranker v3.5Jina AI	`F16`	5.0 GB	73 ms	Runs great
84Great quality (A) · 84 of 100: how capable the model is at F16, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking.	Jina Reranker v3Jina AI	`F16`	5.0 GB	73 ms	Runs great
80Great quality (A) · 80 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking.	FRIDA-DecisionsSber AI	`F16`	2.4 GB	45 ms	Runs great
80Great quality (A) · 80 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking.	GLiNER2.5 DecideFastino	`F16`	1.7 GB	28 ms	Runs great
80Great quality (A) · 80 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking.	Qwen3 Reranker 0.6BAlibaba	`F16`	5.0 GB	73 ms	Runs great
76Great quality (A) · 76 of 100: how capable the model is at F16, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.	Llama Prompt Guard 2 86MMeta	`F16`	1.2 GB	32 ms	Runs great
76Great quality (A) · 76 of 100: how capable the model is at F16, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.	mxbai-rerank-base v2Mixedbread	`F16`	4.5 GB	60 ms	Runs great
82Great quality (A) · 82 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking.	mxbai-rerank-large v2Mixedbread	`Q8_0`	5.2 GB	151 ms	Runs well

Best LLMs by task on this hardware Open in Model Finder

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.