QNAP TVS-AIh1688ATX

Hardware · Intel

What AI models can the Intel Core Ultra 5 225 / 7 265 / 9 285 (desktop) NAS (32 GB) run?

RAM
32.0 GB
Usable for models
26.2 GB
Memory bandwidth
90 GB/s
Runs models on
CPU cores
Released
2024
463 / 621 LLMs run Best: Qwen3.6 35B-A3B 58 / 61 Image models run Best: Krea 2 Turbo 37 / 43 Video models run Best: Bernini-R A14B (video generation + editing) 67 / 70 Decision models run Best: OpenAI Privacy Filter

A NAS with this chip runs models on its processor cores, so memory speed sets the pace: small models (about 1-4B) answer at a usable speed, bigger ones are slow. We plan around 26.2 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

MakerIntel
TypeNAS (network attached storage) processor
Share of memory for models82% (what the NAS system and its storage services typically leave free at this size)
ChipIntel Core Ultra 5 225 / 7 265 / 9 285 (desktop)
AI acceleratorNone. Models run on the processor cores.
NAS models with this chipQNAP TVS-AIh1688ATX · 45HomeLab Signature Series X4 · 45HomeLab X4 (45HomeLab x Unraid)
Memory typeSystem RAM, shared with the NAS operating system and its storage services
Bandwidth figure89.6 GB/s, estimated, see the note below
NoteOne 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.
Specificationswww.qnap.com

Apps that run models well on the Intel Core Ultra 5 225 / 7 265 / 9 285 (desktop) NAS (32 GB)

Linux

  1. OllamaOne command with Ollama’s own build of this model.
  2. llama.cppUsually the first to support new model architectures.
  3. KoboldCpp

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

3 products with the Intel Core Ultra 5 225 / 7 265 / 9 285 (desktop) NAS (32 GB)

Best LLMs for the Intel Core Ultra 5 225 / 7 265 / 9 285 (desktop) NAS (32 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 91/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.6 35B-A3BAlibaba Q4_K_M 24.8 GB 27.7 tok/s Runs welltight fit
88Excellent quality (A+) · 88 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. MiniCPM-V 4.7 35B-A3BOpenBMB Q4_K_M 24.3 GB 27.7 tok/s Runs welltight fit
88Excellent quality (A+) · 88 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. Qwen3.5 35B-A3BAlibaba Q4_K_M 24.8 GB 27.7 tok/s Runs welltight fit
87Excellent quality (A+) · 87 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 90/100 (quality, fit, speed and memory use) sets the ranking. Nex N2 Mini (35B-A3B)Nex-AGI Q4_K_M 24.3 GB 27.7 tok/s Runs welltight fit
87Excellent quality (A+) · 87 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 90/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 26B-A4BGoogle Q4_K_M 18.8 GB 22.3 tok/s Runs well
86Excellent quality (A+) · 86 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 90/100 (quality, fit, speed and memory use) sets the ranking. KAT-Coder V2.5 Dev (35B-A3B)Kuaishou Q4_K_M 24.0 GB 27.7 tok/s Runs welltight fit
86Excellent quality (A+) · 86 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 90/100 (quality, fit, speed and memory use) sets the ranking. Sage-A1.5 35B-A3BInternScience Q4_K_M 24.8 GB 27.7 tok/s Runs welltight fit
83Great quality (A) · 83 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 90/100 (quality, fit, speed and memory use) sets the ranking. GLM-4.7 Flash (30B-A3B)Zhipu AI Q4_K_M 22.2 GB 27.7 tok/s Runs well
85Excellent quality (A+) · 85 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. Ornith 1.5 35B-A3BDeepReinforce Q4_K_M 24.8 GB 27.7 tok/s Runs welltight fit
84Great quality (A) · 84 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. Apodex 1.1 Mini (35B-A3B)Apodex Q4_K_M 24.8 GB 27.7 tok/s Runs welltight fit
84Great quality (A) · 84 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. Ornith 1.0 35B-A3BDeepReinforce Q4_K_M 24.8 GB 27.7 tok/s Runs welltight fit
80Great quality (A) · 80 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking. Hunyuan Hy-Memory 30B-A3BTencent Q4_K_M 21.8 GB 27.7 tok/s Runs well

Best Image models for the Intel Core Ultra 5 225 / 7 265 / 9 285 (desktop) NAS (32 GB)

Quality Model Quant Memory Speed Runs
90Excellent quality (A+) · 90 of 100: how capable the model is at FP8, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. Krea 2 TurboKrea FP8 20.2 GB 3.8 min Very slow
82Great quality (A) · 82 of 100: how capable the model is at FP8, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 9BBlack Forest Labs FP8 19.9 GB 1.6 min Slow
78Great quality (A) · 78 of 100: how capable the model is at FP16, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 4BBlack Forest Labs FP16 18.1 GB 58 s Slow
87Excellent quality (A+) · 87 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. ERNIE-ImageBaidu Q8 GGUF 18.9 GB 24.6 min Very slow
85Excellent quality (A+) · 85 of 100: how capable the model is at NF4, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. Ideogram 4Ideogram NF4 21.8 GB 26.7 min Very slow
90Excellent quality (A+) · 90 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. FLUX 3 Image KleinBlack Forest Labs Q8 GGUF 12.8 GB 6.4 min Very slow

Best Video models for the Intel Core Ultra 5 225 / 7 265 / 9 285 (desktop) NAS (32 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 73/100 (quality, fit, speed and memory use) sets the ranking. Bernini-R A14B (video generation + editing)ByteDance FP8 20.3 GB 11.0 h Very slowencoder unloaded after use
74Great quality (A) · 74 of 100: how capable the model is at FP8, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. HY-OmniWeaving (8.3B, unified video)Tencent FP8 24.6 GB 7.7 h Very slowtight fit
70Great quality (A) · 70 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. Wan 2.2 S2V 14B (speech to video)Alibaba Q4 GGUF 21.6 GB 19.4 h Very slow
68Good quality (B) · 68 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. Wan 2.1 I2V 14B 480PAlibaba Q4 GGUF 20.6 GB 17.5 h Very slow
79Great quality (A) · 79 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. LTX-2.3Lightricks Q4 GGUF 24.5 GB 8.2 h Very slowtight fit · encoder unloaded after use

Best Decision models for the Intel Core Ultra 5 225 / 7 265 / 9 285 (desktop) NAS (32 GB)

Quality Model Quant Memory Speed Runs
78Great quality (A) · 78 of 100: how capable the model is at F16, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking. OpenAI Privacy FilterOpenAI F16 3.8 GB 37 ms Runs great
68Good quality (B) · 68 of 100: how capable the model is at F16, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. Llama Prompt Guard 2 22MMeta F16 0.8 GB 99 ms Runs great
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. GLiNER2.5 DecideFastino Q8_0 1.2 GB 288 ms Runs well
86Excellent quality (A+) · 86 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3.5Jina AI Q8_0 3.6 GB 657 ms Slow
66Good quality (B) · 66 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. GLiClass Base v3Knowledgator Q8_0 0.8 GB 114 ms Runs great
84Great quality (A) · 84 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3Jina AI Q8_0 3.6 GB 657 ms Slow
64Good quality (B) · 64 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. DeBERTa v3 Base Zero-shot v2.0Moritz Laurer Q8_0 0.8 GB 108 ms Runs great
74Great quality (A) · 74 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. GLiClass ModernBERT Large v3Knowledgator Q8_0 1.1 GB 236 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.

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