QNAP TDS-h2489FU R2

Products · · NAS

QNAP TDS-h2489FU R2

Processor
Intel Xeon Silver (4100 to 4300 series)
Memory (RAM)
64, 128, 256 or 512 GB
Launch price
$13,999
Released
2025

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 Xeon Silver (4100 to 4300 series) 64.0 GB 54.4 GB 115 GB/s 358 of 619 $13,999
Intel Xeon Silver (4100 to 4300 series) 128 GB 113 GB 115 GB/s 366 of 619 —
Intel Xeon Silver (4100 to 4300 series) 256 GB 230 GB 115 GB/s 366 of 619 —
Intel Xeon Silver (4100 to 4300 series) 512 GB 471 GB 115 GB/s 366 of 619 —

Specifications 256 GB configuration

MakerQNAP
TypeNAS
ProcessorIntel Xeon Silver (4100 to 4300 series) NAS (256 GB)
Memory (RAM)256 GB
Usable for AI models230 GB
Memory bandwidth115 GB/s
FP16 compute1.0 TFLOPS
Runs models onCPU cores
Drive bays24 (16 x 2.5-inch U.2 PCIe NVMe + 8 x 2.5-inch U.2 PCIe NVMe/SATA 6Gbps) + 2 x M.2 2280 (NVMe PCIe Gen 3 or…
NAS systemQuTS hero
Containers (Docker)Yes
Virtual machinesYes
Memory upgradeDDR4 RDIMM · 32 slots · up to 1,024 GB per the maker · ECC
Graphics card optionsPCIe: 4 ; Slot 1: PCIe Gen4 x16 or Gen4 x8.
Notes2 x Intel Xeon Silver 4314 16-core/32-thread processor, up to 3.4 GHz or 2 x Intel Xeon Silver 4309Y 8-core/16-thread…. x86-64 with up to 1024 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 TDS-h2489FU R2

Yes, it runs AI models on the NAS itself. Models run on its CPU cores, and this configuration leaves about 230 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
QuAgent (beta) + AI Service Center (beta) Conversational NAS assistant on QTS 6.1 / QuTS hero h6.1; uses either a cloud model or an on-premises model (compatible GPU recommended). QNAP lists x86 NAS "x74 series and above", TVS-AI and QAI series as supported. Cloud service or another computer

Best LLMs for the QNAP TDS-h2489FU R2 256 GB

Quality Model Quant Memory Speed Runs
91Excellent quality (A+) · 91 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 87/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.8 Flash Next (125B-A6B)Alibaba Q4_K_M 129 GB 11.0 tok/s Runs well
92Excellent quality (A+) · 92 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. Step 3.7 Flash (198B-A11B)StepFun Q6_K 185 GB 4.3 tok/s Slow
91Excellent quality (A+) · 91 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. Step 3.5 Flash (196B-A11B)StepFun Q6_K 183 GB 4.3 tok/s Slow
89Excellent quality (A+) · 89 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. Inkling Small (276B-A12B)Thinking Machines Lab Q4_K_M 182 GB 5.6 tok/s Slow
91Excellent quality (A+) · 91 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. MiMo V2.6 Flash (310B-A15B)Xiaomi Q4_K_M 209 GB 4.5 tok/s Slowtight fit
92Excellent quality (A+) · 92 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. GLM-5.3 Flash (320B-A18B)Zhipu AI Q4_K_M 215 GB 3.8 tok/s Slowtight fit
89Excellent quality (A+) · 89 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. DeepSeek V4 Flash (284B-A13B)DeepSeek Q4_K_M 205 GB 5.2 tok/s Slowtight fit
90Excellent quality (A+) · 90 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. Naive N0.5 Flash (309B-A15.5B)Naive AI Q4_K_M 208 GB 4.4 tok/s Slowtight fit
89Excellent quality (A+) · 89 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. MiMo V2.5 (310B-A15B)Xiaomi Q4_K_M 209 GB 4.5 tok/s Slowtight fit
89Excellent quality (A+) · 89 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. DeepSeek V4 Flash (April 2026)DeepSeek Q5_K_M 226 GB 4.3 tok/s Slowtight fit

Best Image models for the QNAP TDS-h2489FU R2 256 GB

Quality Model Quant Memory Speed Runs
90Excellent quality (A+) · 90 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. HunyuanImage 3.0 (80B-A13B)Tencent FP16 170 GB 49.3 min Very slow
92Excellent quality (A+) · 92 of 100: how capable the model is at FP16, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Cosmos3-Super Text2Image (64B)NVIDIA FP16 133 GB 32.9 min Very slow
92Excellent quality (A+) · 92 of 100: how capable the model is at FP16, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [dev]Black Forest Labs FP16 116 GB 29.6 min Very slow
92Excellent quality (A+) · 92 of 100: how capable the model is at FP16, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. Krea 2 TurboKrea FP16 37.4 GB 3.5 min Very slow
92Excellent quality (A+) · 92 of 100: how capable the model is at FP16, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. Ideogram 4Ideogram FP16 57.3 GB 20.5 min Very slow
93Excellent quality (A+) · 93 of 100: how capable the model is at FP16, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. Qwen-Image 2.1Alibaba FP16 57.0 GB 49.3 min Very slow

Best Video models for the QNAP TDS-h2489FU R2 256 GB

Quality Model Quant Memory Speed Runs
88Excellent quality (A+) · 88 of 100: how capable the model is at FP16, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. Cosmos3-Super Image2Video (64B)NVIDIA FP16 139 GB 30.8 h Very slow
90Excellent quality (A+) · 90 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. MiniMax H3 (33B, video + audio)MiniMax FP16 113 GB 14.2 h Very slow
88Excellent quality (A+) · 88 of 100: how capable the model is at FP16, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. LTX-2.5 (22B, video + audio)Lightricks FP16 82.5 GB 74.8 min Very slow
88Excellent quality (A+) · 88 of 100: how capable the model is at FP16, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. Kandinsky 6.0 Pro (29B, video + audio)Sber AI FP16 85.4 GB 40.3 h Very slow
86Excellent quality (A+) · 86 of 100: how capable the model is at FP16, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. LTX-2.3Lightricks FP16 75.4 GB 5.5 h Very slow

Best Decision models for the QNAP TDS-h2489FU R2 256 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 50 ms Runs great
68Good quality (B) · 68 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. Llama Prompt Guard 2 22MMeta Q8_0 0.7 GB 117 ms Runs great
86Excellent quality (A+) · 86 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 v3.5Jina AI Q8_0 19.9 GB 899 ms Slow
80Great quality (A) · 80 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. GLiNER2.5 DecideFastino Q8_0 1.2 GB 394 ms Runs well
84Great quality (A) · 84 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3Jina AI Q8_0 19.9 GB 899 ms Slow
90Excellent quality (A+) · 90 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. Qwen3 Reranker 4BAlibaba Q8_0 23.6 GB 6.0 s Very slow
90Excellent quality (A+) · 90 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. Qwen3 Reranker 8BAlibaba Q8_0 28.0 GB 12.2 s Very slow
80Great quality (A) · 80 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. FRIDA-DecisionsSber AI Q8_0 1.7 GB 656 ms Slow

Other products with the Intel Xeon Silver (4100 to 4300 series) NAS (256 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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