QNAP TS-h1290FX

Products · · NAS

QNAP TS-h1290FX

Processor
AMD EPYC 7002 / 7003 series
Memory (RAM)
64, 128, 256 or 512 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
AMD EPYC 7002 / 7003 series 64.0 GB 54.4 GB 205 GB/s 420 of 619 —
AMD EPYC 7002 / 7003 series 128 GB 113 GB 205 GB/s 441 of 619 —
AMD EPYC 7002 / 7003 series 256 GB 230 GB 205 GB/s 457 of 619 —
AMD EPYC 7002 / 7003 series · upgraded to 512 GB (the maker lists up to 1 TB) 512 GB 471 GB 205 GB/s 459 of 619 —

Specifications 512 GB configuration

MakerQNAP
TypeNAS
ProcessorAMD EPYC 7002 / 7003 series NAS (512 GB) · upgraded to 512 GB (the maker lists up to 1 TB)
Memory (RAM)512 GB
Usable for AI models471 GB
Memory bandwidth205 GB/s
FP16 compute1.0 TFLOPS
Runs models onCPU cores
Drive bays12 x 2.5-inch U.2 PCIe NVMe / SATA 6Gbps
NAS systemQuTS hero
Containers (Docker)Yes
Virtual machinesYes
Memory upgradeDDR4 RDIMM · 8 slots · up to 1,024 GB per the maker · ECC
Graphics card optionsPCIe: 4 ; Slot 1: PCIe Gen 4 x16 ; Slot 2: PCIe Gen 4 x16 ; Slot 3: PCIe Gen 4 x8 ; Slot 4: PCIe Gen 4 x16. Maker-supported graphics cards: QNAP FAQ: graphics card in PCIe slot 4. QNAP's on-prem RAG tutorial recommends NVIDIA RTX 6000 Ada or RTX 4000 Ada (also RTX PRO 6000 Blackwell Max-Q).
NotesAMD EPYC 7232P/7252 8-core/16-thread processor, up to 3.2 GHz or AMD EPYC 7302P 16-core/32-thread processor, up to 3.3…. EPYC 7232P/7302P tower with 64-256 GB ECC RAM (max 1 TB) and four PCIe Gen4 slots; QNAP names the TS-h1290FX with an NVIDIA RTX 6000 Ada or RTX 4000 Ada as its recommended platform for on-premises Qsirch RAG (LLM Core). Same chassis as the QAI-h1290FX. Ollama also runs CPU-only in Container Station.
Product pagewww.qnap.com (opens in a new tab)

Running AI on the QNAP TS-h1290FX

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
LLM Core + Qsirch on-premises RAG Runs open LLMs locally on an NVIDIA GPU in the NAS (GPU set to Container Station mode) for Qsirch RAG; QNAP lists DeepSeek R1 7B-32B, Gemma3 1B-27B, gpt-oss 20B, Mistral 7B, Phi-4 14B (Q4_K_M). On the NAS
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-h1290FX 512 GB

Quality Model Quant Memory Speed Runs
96Excellent quality (A+) · 96 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. MiniMax M3.1 Flash (428B-A23B)MiniMax Q6_K 391 GB 4.2 tok/s Slow
92Excellent quality (A+) · 92 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. Ling 3.1 Flash 1019 (560B-A25B)Ant Group (inclusionAI) Q4_K_M 387 GB 5.5 tok/s Slow
93Excellent quality (A+) · 93 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. K2-Horizon (375B-A23B)Institute of Foundation Models Q6_K 351 GB 4.2 tok/s Slow
93Excellent quality (A+) · 93 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. MiniMax M3 (427B)MiniMax Q6_K 389 GB 3.8 tok/s Slow
91Excellent quality (A+) · 91 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. Beam 1.0 (501B-A23B)Reflection AI Q5_K_M 394 GB 4.8 tok/s Slow
90Excellent quality (A+) · 90 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. Ling 3.1 Flash (560B-A25B)Ant Group (inclusionAI) Q4_K_M 387 GB 5.5 tok/s Slow
94Excellent quality (A+) · 94 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. Step 5 Preview (600B-A27B)StepFun Q5_K_M 468 GB 4.2 tok/s Slowtight fit
90Excellent quality (A+) · 90 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. GLM-4.7 (355B-A32B)Zhipu AI Q5_K_M 296 GB 3.6 tok/s Slow
91Excellent quality (A+) · 91 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.8 Flash Next (125B-A6B)Alibaba Q4_K_M 148 GB 21.6 tok/s Runs well
88Excellent quality (A+) · 88 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. Qwen3 Coder 480B-A35BAlibaba Q5_K_M 381 GB 3.3 tok/s Slow

Best Image models for the QNAP TS-h1290FX 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 41.1 min Very slow
92Excellent quality (A+) · 92 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. Cosmos3-Super Text2Image (64B)NVIDIA FP16 133 GB 27.4 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 24.7 min Very slow
92Excellent quality (A+) · 92 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. Krea 2 TurboKrea FP16 37.4 GB 2.9 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 17.1 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 41.1 min Very slow

Best Video models for the QNAP TS-h1290FX 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 72/100 (quality, fit, speed and memory use) sets the ranking. Cosmos3-Super Image2Video (64B)NVIDIA FP16 139 GB 25.7 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 11.9 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 62.3 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 33.6 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 4.6 h Very slow

Best Decision models for the QNAP TS-h1290FX 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 44 ms Runs great
68Good quality (B) · 68 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. Llama Prompt Guard 2 22MMeta Q8_0 0.7 GB 103 ms Runs great
80Great quality (A) · 80 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. GLiNER2.5 DecideFastino Q8_0 1.2 GB 345 ms Runs well
86Excellent quality (A+) · 86 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. Jina Reranker v3.5Jina AI Q8_0 39.2 GB 780 ms Slow
84Great quality (A) · 84 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 v3Jina AI Q8_0 39.2 GB 780 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 5.2 s Very slow
66Good quality (B) · 66 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. GLiClass Base v3Knowledgator Q8_0 0.8 GB 136 ms Runs well
80Great quality (A) · 80 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. FRIDA-DecisionsSber AI Q8_0 1.7 GB 574 ms Slow

Other products with the AMD EPYC 7002 / 7003 series NAS (512 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.

Was this page helpful?