Products · QNAP · 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 128 GB configuration
| Maker | QNAP |
|---|---|
| Type | NAS |
| Processor | Intel Xeon W-2100 series NAS (128 GB) |
| Memory (RAM) | 128 GB |
| Usable for AI models | 113 GB |
| Memory bandwidth | 85 GB/s |
| FP16 compute | 0.8 TFLOPS |
| Runs models on | CPU cores |
| Drive bays | 8 x 3.5-inch + 20 x 2.5-inch |
| NAS system | QTS |
| Containers (Docker) | Yes |
| Virtual machines | Yes |
| Memory upgrade | RDIMM DDR4 · 8 slots · up to 512 GB per the maker · ECC |
| Graphics card options | PCIe: 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. |
| Availability | Discontinued (sold used or refurbished) |
| Notes | Intel 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 page | www.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 113 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
| App | How 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) |
AI features from QNAP
| Feature | What it does | Where 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 128 GB
| Quality | Model | Quant | Memory | Speed | Runs |
|---|---|---|---|---|---|
| 90Excellent quality (A+) · 90 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking. | Kolibri 1 (78B-A3.5B) | Q6_K | 73.8 GB | 12.5 tok/s | Runs well |
| 84Great quality (A) · 84 of 100: how capable the model is at MXFP4, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. | gpt-oss 120B | MXFP4 | 76.5 GB | 13.1 tok/s | Runs well |
| 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. | Nemotron 3.5 Super VL 120B-A12B | Q4_K_M | 85.6 GB | 5.4 tok/s | Slow |
| 81Great quality (A) · 81 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. | Qwen3-Next 80B-A3B Thinking | Q4_K_M | 59.4 GB | 20.3 tok/s | Runs well |
| 81Great quality (A) · 81 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. | Qwen3 Coder Next (80B-A3B) | Q4_K_M | 58.4 GB | 20.3 tok/s | Runs well |
| 81Great quality (A) · 81 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. | Qwen3.8 Flash Next (125B-A6B) | Q3_K_M | 98.0 GB | 13.5 tok/s | Runs welltight fit |
| 79Great quality (A) · 79 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. | Qwen3 Next 80B-A3B Instruct | Q4_K_M | 59.4 GB | 20.3 tok/s | Runs well |
| 77Great quality (A) · 77 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. | Ling 3.0 Flash (127B-A5B) | Q4_K_M | 87.8 GB | 12.3 tok/s | Runs well |
| 83Great quality (A) · 83 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. | Nemotron 3 Super 120B-A12B | Q4_K_M | 85.1 GB | 5.4 tok/s | Slow |
| 88Excellent quality (A+) · 88 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. | Qwen3.6 35B-A3B | Q4_K_M | 31.7 GB | 20.3 tok/s | Runs well |
Best Image models for the QNAP TS-2888X 128 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 80/100 (quality, fit, speed and memory use) sets the ranking. | Cosmos3-Super Text2Image (64B) | FP8 | 69.1 GB | 35.0 min | Very slow |
| 88Excellent quality (A+) · 88 of 100: how capable the model is at FP8, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. | HunyuanImage 3.0 (80B-A13B) | FP8 | 86.9 GB | 52.5 min | Very slow |
| 91Excellent quality (A+) · 91 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 [dev] | Q8 GGUF | 61.9 GB | 40.2 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. | Ideogram 4 | 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 79/100 (quality, fit, speed and memory use) sets the ranking. | Qwen-Image 2.1 | FP16 | 57.0 GB | 58.3 min | Very slow |
| 90Excellent quality (A+) · 90 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. | Qwen-Image 2512 | FP16 | 63.8 GB | 87.5 min | Very slow |
Best Video models for the QNAP TS-2888X 128 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 82/100 (quality, fit, speed and memory use) sets the ranking. | LTX-2.5 (22B, video + audio) | 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 80/100 (quality, fit, speed and memory use) sets the ranking. | Kandinsky 6.0 Pro (29B, video + audio) | 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 80/100 (quality, fit, speed and memory use) sets the ranking. | LTX-2.3 | FP16 | 75.4 GB | 6.5 h | Very slow |
| 89Excellent quality (A+) · 89 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. | MiniMax H3 (33B, video + audio) | Q8 GGUF | 68.2 GB | 19.4 h | Very slow |
| 82Great quality (A) · 82 of 100: how capable the model is at FP16, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. | LTX-2 (19B, video + audio) | FP16 | 75.4 GB | 6.5 h | Very slow |
Best Decision models for the QNAP TS-2888X 128 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 Filter | 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 22M | 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 v3.5 | Q8_0 | 10.5 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 Decide | 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 v3 | Q8_0 | 10.5 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 4B | Q8_0 | 14.2 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-Decisions | 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 v3 | 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.