QNAP TS-2888X

Products · · NAS

QNAP TS-2888X

Processor
Intel Xeon W-2100 series
Memory (RAM)
32, 64, 128, 256 or 512 GB
Released
2018

Product page (opens in a new tab)Discontinued 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 W-2100 series 32.0 GB 26.2 GB 85 GB/s 343 of 619 —
Intel Xeon W-2100 series 64.0 GB 54.4 GB 85 GB/s 358 of 619 —
Intel Xeon W-2100 series 128 GB 113 GB 85 GB/s 366 of 619 —
Intel Xeon W-2100 series 256 GB 230 GB 85 GB/s 366 of 619 —
Intel Xeon W-2100 series 512 GB 471 GB 85 GB/s 366 of 619 —

Specifications 512 GB configuration

MakerQNAP
TypeNAS
ProcessorIntel Xeon W-2100 series NAS (512 GB)
Memory (RAM)512 GB
Usable for AI models471 GB
Memory bandwidth85 GB/s
FP16 compute0.8 TFLOPS
Runs models onCPU cores
Drive bays8 x 3.5-inch + 20 x 2.5-inch
NAS systemQTS
Containers (Docker)Yes
Virtual machinesYes
Memory upgradeRDIMM DDR4 · 8 slots · up to 512 GB per the maker · ECC
Graphics card optionsPCIe: 8 Slot 1: PCIe Gen 3 x8 or x4 (CPU) Slot 2: PCIe Gen 3 x4 (CPU) Slot 3: PCIe Gen 3 x8 or x4 (CPU) Slot 4…. Maker-supported graphics cards: QNAP product page: up to four high-end graphics cards (8 PCIe Gen3 slots, cards up to 330 mm); no current model list.
AvailabilityDiscontinued (sold used or refurbished)
NotesIntel Xeon W-2195 18-core 2.3 GHz Processor (burst up to 4.3 GHz). x86-64 Xeon W-2195 CPU, up to 512 GB RAM, Container Station (Docker) and Virtualization Station. PCIe slot with GPU pass-through listed on the maker spec sheet, so a discrete GPU can be added (check card size and PSU).
Product pagewww.qnap.com (opens in a new tab)Discontinued

Running AI on the QNAP TS-2888X

Yes, it runs AI models on the NAS itself. Models run on its CPU cores, and this configuration leaves about 471 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 + Open WebUI In a container (Docker)
Ollama / Open WebUI or any other LLM server image In a container (Docker)
Any Linux VM running an LLM runtime In a virtual machine
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
Qsirch RAG Search (cloud LLM mode) Natural-language search and Q&A over NAS files; retrieval runs on the NAS but the LLM is a cloud API (Gemini, OpenAI, Azure OpenAI or OpenAI-compatible). Cloud service or another computer
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 on-premises RAG / LLM Core Runs open models (DeepSeek R1, Gemma 3, gpt-oss 20B, Mistral 7B, Phi-4) locally for RAG search. Requires an NVIDIA GPU assigned to Container Station; QNAP states CPU-only is not supported. Needs QuTS hero h5.2.1+ and Qsirch 6.0.0+. On the NAS
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. On the NAS

Best LLMs for the QNAP TS-2888X 512 GB

Quality Model Quant Memory Speed Runs
92Excellent quality (A+) · 92 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. Intern-S2 (397B-A17B)Shanghai AI Lab Q5_K_M 325 GB 3.1 tok/s Slow
92Excellent quality (A+) · 92 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. Nex N2 Pro (397B-A17B)Nex-AGI Q5_K_M 320 GB 3.1 tok/s Slow
92Excellent quality (A+) · 92 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 397B-A17BAlibaba Q5_K_M 325 GB 3.1 tok/s Slow
93Excellent quality (A+) · 93 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. DeepSeek V4 Flash (284B-A13B)DeepSeek Q6_K 288 GB 3.4 tok/s Slow
91Excellent quality (A+) · 91 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. Ornith 1.5 397B-A17BDeepReinforce Q5_K_M 325 GB 3.1 tok/s Slow
93Excellent quality (A+) · 93 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. MiMo V2.6 Flash (310B-A15B)Xiaomi Q5_K_M 259 GB 3.6 tok/s Slow
91Excellent quality (A+) · 91 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. DeepSeek V4 Flash (April 2026)DeepSeek Q6_K 277 GB 3.4 tok/s Slow
92Excellent quality (A+) · 92 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. Inkling Small (276B-A12B)Thinking Machines Lab Q6_K 257 GB 3.7 tok/s Slow
92Excellent quality (A+) · 92 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. Naive N0.5 Flash (309B-A15.5B)Naive AI Q5_K_M 258 GB 3.4 tok/s Slow
91Excellent quality (A+) · 91 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. MiMo V2.5 (310B-A15B)Xiaomi Q5_K_M 259 GB 3.6 tok/s Slow

Best Image models for the QNAP TS-2888X 512 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 74/100 (quality, fit, speed and memory use) sets the ranking. HunyuanImage 3.0 (80B-A13B)Tencent FP16 170 GB 58.3 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. Cosmos3-Super Text2Image (64B)NVIDIA FP16 133 GB 38.9 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. FLUX.2 [dev]Black Forest Labs FP16 116 GB 35.0 min Very slow
92Excellent quality (A+) · 92 of 100: how capable the model is at FP16, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. Krea 2 TurboKrea FP16 37.4 GB 4.2 min Very slow
92Excellent quality (A+) · 92 of 100: how capable the model is at FP16, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. Ideogram 4Ideogram FP16 57.3 GB 24.3 min Very slow
93Excellent quality (A+) · 93 of 100: how capable the model is at FP16, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. Qwen-Image 2.1Alibaba FP16 57.0 GB 58.3 min Very slow

Best Video models for the QNAP TS-2888X 512 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 71/100 (quality, fit, speed and memory use) sets the ranking. Cosmos3-Super Image2Video (64B)NVIDIA FP16 139 GB 36.4 h Very slow
90Excellent quality (A+) · 90 of 100: how capable the model is at FP16, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. MiniMax H3 (33B, video + audio)MiniMax FP16 113 GB 16.8 h Very slow
88Excellent quality (A+) · 88 of 100: how capable the model is at FP16, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. LTX-2.5 (22B, video + audio)Lightricks FP16 82.5 GB 88.4 min Very slow
88Excellent quality (A+) · 88 of 100: how capable the model is at FP16, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. Kandinsky 6.0 Pro (29B, video + audio)Sber AI FP16 85.4 GB 47.6 h Very slow
86Excellent quality (A+) · 86 of 100: how capable the model is at FP16, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. LTX-2.3Lightricks FP16 75.4 GB 6.5 h Very slow

Best Decision models for the QNAP TS-2888X 512 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 48 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 114 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 39.2 GB 875 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 383 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 39.2 GB 875 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 42.8 GB 5.8 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 638 ms Slow
66Good quality (B) · 66 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. GLiClass Base v3Knowledgator Q8_0 0.8 GB 151 ms Runs well

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?