Products · QNAP · NAS

QNAP QAI-h1290FX

Processor: AMD EPYC 7002 / 7003 series
Memory (RAM): 128 or 512 GB
Released: 2026

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	128 GB	113 GB	205 GB/s	441 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

Maker	QNAP
Type	NAS
Processor	AMD 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 models	471 GB
Memory bandwidth	205 GB/s
FP16 compute	1.0 TFLOPS
Runs models on	CPU cores
Drive bays	12 x 2.5-inch U.2 PCIe NVMe / SATA 6Gbps
NAS system	QuTS hero
Containers (Docker)	Yes
Virtual machines	Yes
Memory upgrade	DDR4 RDIMM · 8 slots · up to 1,024 GB per the maker · ECC
Graphics card options	PCIe: 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: NVIDIA RTX PRO 6000 Blackwell Max-Q (96 GB), NVIDIA RTX PRO 4500 Blackwell (32 GB) as factory options; Intel Arc Pro B70 support added in QuTS hero h6.1 (BIOS update from QNAP support required).
Notes	AMD EPYC 7302P 16-core/32-thread processor, up to 3.3 GHz. Purpose-built Edge AI storage server: EPYC 7302P, 128 GB RAM (max 1 TB), sold with an NVIDIA RTX PRO Blackwell GPU and Ollama/Open WebUI/AnythingLLM container templates.
Product page	www.qnap.com (opens in a new tab)

Running AI on the QNAP QAI-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

App	How it installs
Ollama, AnythingLLM, Stable Diffusion	From the NAS app store
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)

Apps that run LLMs on a NAS, with their container images

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
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
Preloaded AI container templates (Ollama, Open WebUI, AnythingLLM, Whisper)	QNAP-provided Container Station templates for local LLM chat, RAG and speech-to-text on the built-in NVIDIA GPU; Stable Diffusion, ComfyUI, n8n and vLLM listed as planned.	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

Best LLMs for the QNAP QAI-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 QAI-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 QAI-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 QAI-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)

TS-h1290FXQNAP · NAS · 64, 128, 256 or 512 GBProduct page (opens in a new tab)
TS-h2490FUQNAP · NAS · 32, 64, 128, 256 or 512 GB · $8,999Product page (opens in a new tab)
TS-h1090FUQNAP · NAS · 32, 64, 128, 256 or 512 GB · $7,099Product page (opens in a new tab)
FS6420Synology · NAS · 64 or 512 GBProduct page (opens in a new tab)
SA6400Synology · NAS · 32 or 512 GBProduct page (opens in a new tab)Discontinued
RS11626xs+Synology · NAS · 64 or 512 GBProduct page (opens in a new tab)
HL15 2.0 (Fully Built & Burned In)45HomeLab · NAS · 16, 32, 64, 128, 256 or 512 GB · $2,920Product page (opens in a new tab)
HL15 Beast (Fully Built, ASRock Rack / EPYC)45HomeLab · NAS · 16, 32, 64, 128, 256 or 512 GB · $3,419Product page (opens in a new tab)

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.