QNAP TS-435XeU

Products · · NAS

QNAP TS-435XeU

Processor
Marvell OCTEON TX2 CN9130
Memory (RAM)
4 or 32 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
Marvell OCTEON TX2 CN9130 4.0 GB 2.0 GB 19 GB/s 33 of 622 —
Marvell OCTEON TX2 CN9130 · upgraded to the maker's maximum 32.0 GB 26.2 GB 19 GB/s 40 of 622 —

Specifications 32.0 GB configuration

MakerQNAP
TypeNAS
ProcessorMarvell OCTEON TX2 CN9130 NAS (32 GB) · upgraded to the maker's maximum
Memory (RAM)32.0 GB
Usable for AI models26.2 GB
Memory bandwidth19 GB/s
FP16 compute0.1 TFLOPS
Runs models onCPU cores
Drive bays4 x 3.5-inch SATA 6Gb/s, 3Gb/s + 2 x M.2 2280 PCIe Gen 3 x1 slots
NAS systemQTS
Containers (Docker)Yes
Virtual machinesNo
Memory upgradeDDR4 SODIMM · 1 slot · up to 32.0 GB per the maker · ECC
NotesMarvell OCTEON TX2 CN9130 / CN9131 ARMv8 Cortex-A72 4-core 2.2GHz processor. 64-bit ARM CPU with 32 GB max RAM and Container Station (Docker). QNAP's Ollama tutorial targets x86_64 and says only a few ARM-based models are supported; no GPU option. Expect only small (1-3B) models on CPU, if the container runs at all. No speed figures published.
Product pagewww.qnap.com (opens in a new tab)

Running AI on the QNAP TS-435XeU

It can, with limits: expect small models only, at modest speed. Models run on its CPU cores, and this configuration leaves about 26.2 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 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-435XeU 32.0 GB

Quality Model Quant Memory Speed Runs
94Excellent quality (A+) · 94 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.8 27BAlibaba Q6_K 26.0 GB 0.2 tok/s Very slowtight fit
93Excellent quality (A+) · 93 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.6 27BAlibaba Q6_K 26.0 GB 0.2 tok/s Very slowtight fit
92Excellent quality (A+) · 92 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 27BAlibaba Q6_K 26.0 GB 0.2 tok/s Very slowtight fit
90Excellent quality (A+) · 90 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. Nanbeige4.3 33BBOSS Zhipin (Nanbeige) Q4_K_M 24.6 GB 0.2 tok/s Very slowtight fit
87Excellent quality (A+) · 87 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Muse Glimmer 30BMeta Q4_K_M 21.0 GB 0.3 tok/s Very slow
89Excellent quality (A+) · 89 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. TMax 27BAi2 Q6_K 25.7 GB 0.2 tok/s Very slowtight fit
78Great quality (A) · 78 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.6 35B-A3BAlibaba Q3_K_M 20.5 GB 3.5 tok/s Slow
78Great quality (A) · 78 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. MiniCPM-V 4.7 35B-A3BOpenBMB Q3_K_M 20.1 GB 3.5 tok/s Slow
78Great quality (A) · 78 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 35B-A3BAlibaba Q3_K_M 20.5 GB 3.5 tok/s Slow
87Excellent quality (A+) · 87 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. Fara 1.5 27BMicrosoft Q6_K 25.7 GB 0.2 tok/s Very slowtight fit

Best Image models for the QNAP TS-435XeU 32.0 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 81/100 (quality, fit, speed and memory use) sets the ranking. Krea 2 TurboKrea FP8 20.2 GB 26.7 min Very slow
87Excellent quality (A+) · 87 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. ERNIE-ImageBaidu Q8 GGUF 18.9 GB 2.9 h Very slow
83Great quality (A) · 83 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.2 [klein] 9BBlack Forest Labs Q8 GGUF 20.5 GB 14.3 min Very slow
85Excellent quality (A+) · 85 of 100: how capable the model is at NF4, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. Ideogram 4Ideogram NF4 21.8 GB 3.2 h Very slow
90Excellent quality (A+) · 90 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. FLUX 3 Image KleinBlack Forest Labs Q8 GGUF 12.8 GB 45.3 min Very slow
78Great quality (A) · 78 of 100: how capable the model is at FP16, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 4BBlack Forest Labs FP16 18.1 GB 6.9 min Very slow

Best Video models for the QNAP TS-435XeU 32.0 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 72/100 (quality, fit, speed and memory use) sets the ranking. Bernini-R A14B (video generation + editing)ByteDance FP8 20.3 GB 78.4 h Very slowencoder unloaded after use
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 138.2 h Very slow
74Great quality (A) · 74 of 100: how capable the model is at FP8, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. HY-OmniWeaving (8.3B, unified video)Tencent FP8 24.6 GB 54.9 h Very slowtight fit
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 124.4 h Very slow
79Great quality (A) · 79 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. LTX-2.3Lightricks Q4 GGUF 24.5 GB 58.0 h Very slowtight fit · encoder unloaded after use

Best Decision models for the QNAP TS-435XeU 32.0 GB

Quality Model Quant Memory Speed Runs
90Excellent quality (A+) · 90 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. Qwen3 Reranker 4BAlibaba Q8_0 7.3 GB 165.6 s Very slow
90Excellent quality (A+) · 90 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. Qwen3 Reranker 8BAlibaba Q8_0 11.7 GB 337.4 s Very slow
90Excellent quality (A+) · 90 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. Skywork Reward V2 Llama 3.1 8BSkywork Q8_0 10.4 GB 667.8 s Very slow
88Excellent quality (A+) · 88 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. zerank-2ZeroEntropy Q8_0 7.3 GB 165.6 s Very slow
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 3.6 GB 24.7 s Very slow
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. Shieldstral 1.0 3BMistral AI Q8_0 7.0 GB 158.6 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 3.6 GB 24.7 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. Intern-Decision 4BShanghai AI Lab Q8_0 7.6 GB 94.1 s Very slow

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.

Was this page helpful?