QNAP TS-h1073BXeU

Products · · NAS

QNAP TS-h1073BXeU

Processor
AMD Ryzen Embedded V1780B
Memory (RAM)
8 or 64 GB
Released
2026

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
AMD Ryzen Embedded V1780B 8.0 GB 5.2 GB 21 GB/s 118 of 622 —
AMD Ryzen Embedded V1780B · upgraded to the maker's maximum 64.0 GB 54.4 GB 21 GB/s 170 of 622 —

Specifications 8.0 GB configuration

MakerQNAP
TypeNAS
ProcessorAMD Ryzen Embedded V1780B NAS (8 GB)
Memory (RAM)8.0 GB
Usable for AI models5.2 GB
Memory bandwidth21 GB/s
FP16 compute0.2 TFLOPS
Runs models onCPU cores
Drive bays8 x 3.5-inch SATA 6Gb/s, 3Gb/s
NAS systemQuTS hero
Containers (Docker)Yes
Virtual machinesYes
Memory upgradeDDR4 SODIMM · 2 slots · up to 64.0 GB per the maker
Graphics card optionsPCIe: 1 x PCIe Gen3 x4.
NotesAMD Ryzen Embedded V1780B 4-core/8-thread 3.35 GHz processor. x86-64 with up to 64 GB RAM and Container Station; Ollama runs CPU-only per QNAP's tutorial (>=8 GB for 3B, >=16 GB for 7B models). QNAP does not list a GPU-capable slot for this model, so its own on-prem Qsirch LLM (GPU required) is not available. No token speeds published.
Product pagewww.qnap.com (opens in a new tab)

Running AI on the QNAP TS-h1073BXeU

Yes, it runs AI models on the NAS itself. 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-h1073BXeU 8.0 GB

Quality Model Quant Memory Speed Runs
65Good quality (B) · 65 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. Nemotron Labs Dory 1.0 4BNVIDIA Q5_K_M 4.3 GB 4.9 tok/s Slow
58Good quality (B) · 58 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 E2BGoogle Q4_K_M 4.2 GB 10.3 tok/s Runs well
64Good quality (B) · 64 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. Spark-X2.6 4BSparkLLM Q5_K_M 4.2 GB 4.7 tok/s Slow
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. Nanbeige4.2 3BBOSS Zhipin (Nanbeige) Q4_K_M 5.0 GB 5.7 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 72/100 (quality, fit, speed and memory use) sets the ranking. Unlimited OCR 2 (3B-A0.6B)Baidu Q4_K_M 3.6 GB 34.7 tok/s Runs great
50Fair quality (C) · 50 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 72/100 (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 21.8 tok/s Runs welltight fit
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. Qwen3.5 4BAlibaba Q4_K_M 4.1 GB 5.1 tok/s Slow
59Good quality (B) · 59 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. TMax 4BAi2 Q5_K_M 4.3 GB 4.6 tok/s Slow
58Good quality (B) · 58 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. Nemotron 3.5 Bolt E4BNVIDIA Q3_K_M 5.1 GB 6.8 tok/s Slowtight fit
38Basic quality (D) · 38 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. Unlimited OCR (3B-A0.6B)Baidu Q4_K_M 3.6 GB 34.7 tok/s Runs great

Best Image models for the QNAP TS-h1073BXeU 8.0 GB

Quality Model Quant Memory Speed Runs
72Great quality (A) · 72 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 4BBlack Forest Labs Q4 GGUF 4.6 GB 3.1 min Very slowtight fit · encoder unloaded after use
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 21.1 min Very slowCPU offload
39Basic quality (D) · 39 of 100: how capable the model is at FP8, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. SDXL TurboStability AI FP8 4.2 GB 20 s Runs well
82Great quality (A) · 82 of 100: how capable the model is at FP8, whatever it runs on. Match score 66/100 (quality, fit, speed and memory use) sets the ranking. Z-Image TurboAlibaba (Tongyi) FP8 4.4 GB 7.3 min Very slowCPU offload
28Basic quality (D) · 28 of 100: how capable the model is at FP16, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking. SD TurboStability AI FP16 3.3 GB 12 s Runs great
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 85.1 min Very slowCPU offload

Best Video models for the QNAP TS-h1073BXeU 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 57/100 (quality, fit, speed and memory use) sets the ranking. AnimateDiff v3 (SD 1.5)Shanghai AI Lab FP16 4.7 GB 49.6 min Very slowtight fit
49Fair quality (C) · 49 of 100: how capable the model is at FP8, whatever it runs on. Match score 52/100 (quality, fit, speed and memory use) sets the ranking. LTX-Video 2BLightricks FP8 4.0 GB 72.5 min 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 2.9 h Very slowtight fit · CPU offload

Best Decision models for the QNAP TS-h1073BXeU 8.0 GB

Quality Model Quant Memory Speed Runs
78Great quality (A) · 78 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. OpenAI Privacy FilterOpenAI Q8_0 2.4 GB 123 ms Runs great
86Excellent quality (A+) · 86 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3.5Jina AI Q8_0 1.9 GB 2.7 s Very slow
84Great quality (A) · 84 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3Jina AI Q8_0 1.9 GB 2.7 s Very slow
87Excellent quality (A+) · 87 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Qwen3 Reranker 4BAlibaba Q5_K_M 4.2 GB 17.8 s Very slow
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. GLiNER2.5 DecideFastino Q8_0 1.2 GB 1.2 s Slow
85Excellent quality (A+) · 85 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. zerank-2ZeroEntropy Q5_K_M 4.2 GB 17.8 s Very slow
85Excellent quality (A+) · 85 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. Shieldstral 1.0 3BMistral AI Q6_K 4.4 GB 17.1 s Very slow
80Great quality (A) · 80 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. FRIDA-DecisionsSber AI Q8_0 1.7 GB 2.0 s Very slow

Other products with the AMD Ryzen Embedded V1780B 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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