QNAP TS-464U-RP

Products · · NAS

QNAP TS-464U-RP

Processor
Intel Celeron N5105 / N5095
Memory (RAM)
4, 8 or 16 GB
Released
2022

Product page (opens in a new tab) Full AI report

Configurations

Pick one to see which models it runs. More memory lets larger models fit; bandwidth sets how fast they answer.

Configuration Memory Usable for AI Bandwidth LLMs that run well Launch price
Intel Celeron N5105 / N5095 4.0 GB 2.0 GB 24 GB/s 52 of 622 —
Intel Celeron N5105 / N5095 8.0 GB 5.2 GB 24 GB/s 70 of 622 —
Intel Celeron N5105 / N5095 · upgraded to the maker's maximum 16.0 GB 12.0 GB 24 GB/s 72 of 622 —

Specifications 8.0 GB configuration

MakerQNAP
TypeNAS
ProcessorIntel Celeron N5105 / N5095 NAS (8 GB)
Memory (RAM)8.0 GB
Usable for AI models5.2 GB
Memory bandwidth24 GB/s
FP16 compute0.1 TFLOPS
Runs models onCPU cores
Drive bays4 x 3.5-inch SATA 6Gb/s, 3Gb/s
NAS systemQTS
Containers (Docker)Yes
Virtual machinesYes
Memory upgradeDDR4 SODIMM · 2 slots · up to 16.0 GB per the maker
Graphics card optionsPCIe: 1 ; Slot 1: PCIe Gen 3 x2.
NotesIntel Celeron N5095 4-core/4-thread processor, burst up to 2.9 GHz. x86-64 low-power CPU with only 16 GB max RAM. Ollama in Container Station works CPU-only, but QNAP's tutorial says >=8 GB for 3B and >=16 GB for 7B models and warns larger models can hang the NAS. No GPU option documented. No token speeds published.
Product pagewww.qnap.com (opens in a new tab)

Running AI on the QNAP TS-464U-RP

It can, with limits: expect small models only, at modest speed. Models run on its CPU cores, and this configuration leaves about 5.2 GB for them after the NAS system and its storage services. The grades below assume the NAS isn’t busy with backups or media work at the same time. More memory is the upgrade that matters most: see the configurations.

Apps you can install to run models

AppHow it installs
Ollama In a container (Docker)
Open WebUI In a container (Docker)

Apps that run LLMs on a NAS, with their container images

AI features from QNAP

FeatureWhat it doesWhere the AI runs
QuMagie + QNAP AI Core Photo management with on-device face, object and scene recognition (QNAP AI Core image-recognition engine). On the NAS
Qsirch AI Semantic Search Natural-language/semantic file and image search computed locally; QNAP requires a 64-bit x86 NAS with at least 8 GB RAM. On the NAS
Qsirch RAG Search (cloud LLM mode) Chat with NAS files using a cloud LLM (Gemini, OpenAI, Azure OpenAI or OpenAI-compatible API); the model runs remotely. Cloud service or another computer
AI Service Center (beta) cloud models Central hub for connecting NAS apps to cloud models (OpenAI, Azure OpenAI, Gemini, Claude, OpenAI-compatible); local model library is limited to x86 NAS with a tested GPU (third-party report). Cloud service or another computer

Best LLMs for the QNAP TS-464U-RP 8.0 GB

Quality Model Quant Memory Speed Runs
64Good quality (B) · 64 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. Nemotron Labs Dory 1.0 4BNVIDIA Q4_K_M 3.9 GB 3.0 tok/s Slow
58Good quality (B) · 58 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 E2BGoogle Q4_K_M 4.2 GB 5.2 tok/s Slow
59Good quality (B) · 59 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. MiniCPM5 2BOpenBMB Q6_K 3.4 GB 3.3 tok/s Slow
58Good quality (B) · 58 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. Nemotron 3.5 Bolt E4BNVIDIA Q3_K_M 5.1 GB 3.5 tok/s Slowtight fit
50Fair quality (C) · 50 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. Ling 3.0 Tiny (8B-A1.3B)Ant Group (inclusionAI) Q3_K_M 5.1 GB 11.5 tok/s Runs welltight fit
55Good quality (B) · 55 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. Spark-X2.6 4BSparkLLM Q3_K_M 3.3 GB 3.8 tok/s Slow
57Good quality (B) · 57 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. Nanbeige4.2 3BBOSS Zhipin (Nanbeige) Q3_K_M 4.5 GB 3.7 tok/s Slowtight fit
57Good quality (B) · 57 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 E4BGoogle Q3_K_M 5.1 GB 3.5 tok/s Slowtight fit
41Fair quality (C) · 41 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. Unlimited OCR 2 (3B-A0.6B)Baidu Q4_K_M 3.6 GB 18.8 tok/s Runs well
52Fair quality (C) · 52 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 4BAlibaba Q3_K_M 3.6 GB 3.3 tok/s Slow

Best Image models for the QNAP TS-464U-RP 8.0 GB

Quality Model Quant Memory Speed Runs
90Excellent quality (A+) · 90 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. FLUX 3 Image KleinBlack Forest Labs Q8 GGUF 4.3 GB 57.8 min Very slowCPU offload
72Great quality (A) · 72 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 4BBlack Forest Labs Q4 GGUF 4.6 GB 8.5 min Very slowtight fit · encoder unloaded after use
82Great quality (A) · 82 of 100: how capable the model is at FP8, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking. Z-Image TurboAlibaba (Tongyi) FP8 4.4 GB 19.8 min Very slowCPU offload
81Great quality (A) · 81 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 64/100 (quality, fit, speed and memory use) sets the ranking. ERNIE-ImageBaidu Q4 GGUF 4.1 GB 3.9 h Very slowCPU offload
81Great quality (A) · 81 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 64/100 (quality, fit, speed and memory use) sets the ranking. MOSS-Image SFTOpenMOSS Q8 GGUF 4.1 GB 2.4 h Very slowCPU offload
39Basic quality (D) · 39 of 100: how capable the model is at FP8, whatever it runs on. Match score 64/100 (quality, fit, speed and memory use) sets the ranking. SDXL TurboStability AI FP8 4.2 GB 55 s Slow

Best Video models for the QNAP TS-464U-RP 8.0 GB

Quality Model Quant Memory Speed Runs
35Basic quality (D) · 35 of 100: how capable the model is at FP16, whatever it runs on. Match score 55/100 (quality, fit, speed and memory use) sets the ranking. AnimateDiff v3 (SD 1.5)Shanghai AI Lab FP16 4.7 GB 2.3 h Very slowtight fit
49Fair quality (C) · 49 of 100: how capable the model is at FP8, whatever it runs on. Match score 50/100 (quality, fit, speed and memory use) sets the ranking. LTX-Video 2BLightricks FP8 4.0 GB 3.3 h Very slowCPU offload
44Fair quality (C) · 44 of 100: how capable the model is at FP8, whatever it runs on. Match score 46/100 (quality, fit, speed and memory use) sets the ranking. CogVideoX 2BZhipu AI FP8 4.7 GB 7.9 h Very slowtight fit · CPU offload

Best Decision models for the QNAP TS-464U-RP 8.0 GB

Quality Model Quant Memory Speed Runs
86Excellent quality (A+) · 86 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3.5Jina AI Q8_0 1.9 GB 17.2 s Very slow
87Excellent quality (A+) · 87 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. Qwen3 Reranker 4BAlibaba Q5_K_M 4.2 GB 114.8 s Very slow
84Great quality (A) · 84 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3Jina AI Q8_0 1.9 GB 17.2 s Very slow
85Excellent quality (A+) · 85 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. zerank-2ZeroEntropy Q5_K_M 4.2 GB 114.8 s Very slow
85Excellent quality (A+) · 85 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. Shieldstral 1.0 3BMistral AI Q6_K 4.4 GB 110.0 s Very slow
78Great quality (A) · 78 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. OpenAI Privacy FilterOpenAI Q8_0 2.4 GB 777 ms Slow
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. GLiNER2.5 DecideFastino Q8_0 1.2 GB 7.6 s Very slow
82Great quality (A) · 82 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. mxbai-rerank-large v2Mixedbread Q8_0 2.7 GB 44.1 s Very slow

Other products with the Intel Celeron N5105 / N5095 NAS (8 GB)

Spec sources

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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