QNAP TS-1277

Products · · NAS

QNAP TS-1277

Processor
AMD Ryzen 5 1600 / 7 1700 / 2600 / 2700
Memory (RAM)
8, 16 or 64 GB
Released
2017

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
AMD Ryzen 5 1600 / 7 1700 / 2600 / 2700 8.0 GB 5.2 GB 43 GB/s 150 of 622 —
AMD Ryzen 5 1600 / 7 1700 / 2600 / 2700 16.0 GB 12.0 GB 43 GB/s 173 of 622 —
AMD Ryzen 5 1600 / 7 1700 / 2600 / 2700 · upgraded to the maker's maximum 64.0 GB 54.4 GB 43 GB/s 208 of 622 —

Specifications 16.0 GB configuration

MakerQNAP
TypeNAS
ProcessorAMD Ryzen 5 1600 / 7 1700 / 2600 / 2700 NAS (16 GB)
Memory (RAM)16.0 GB
Usable for AI models12.0 GB
Memory bandwidth43 GB/s
FP16 compute0.3 TFLOPS
Runs models onCPU cores
Drive bays8 x 3.5-inch + 4 x 2.5-inch SATA 6Gb/s, 3Gb/s + M.2: 2 x M.2 22110/2280/2260/2242 SATA 6Gb/s slots
NAS systemQTS
Containers (Docker)Yes
Virtual machinesYes
Memory upgradeUDIMM DDR4 · 4 slots · up to 64.0 GB per the maker
Graphics card optionsPCIe: 3 Slot 1: PCIe Gen 3 x8 Slot 2: PCIe Gen 3 x4 Slot 3: PCIe Gen 2 x4. Maker-supported graphics cards: QNAP product page: AMD Radeon and NVIDIA graphics cards; no current model list.
AvailabilityDiscontinued (sold used or refurbished)
NotesAMD Ryzen 5 1600 6-core/12-thread 3.2 GHz processor (Turbo Core to 3.6 GHz). x86-64 Ryzen 5 1600 CPU, up to 64 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-1277

Yes, it runs AI models on the NAS itself. Models run on its CPU cores, and this configuration leaves about 12.0 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

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

Best LLMs for the QNAP TS-1277 16.0 GB

Quality Model Quant Memory Speed Runs
78Great quality (A) · 78 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 12BGoogle Q4_K_M 9.5 GB 3.0 tok/s Slow
77Great quality (A) · 77 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. K2 Horizon 7BInstitute of Foundation Models Q5_K_M 9.2 GB 3.3 tok/s Slow
66Good quality (B) · 66 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. Mellum2.1 Thinking (12B-A2.5B)JetBrains Q4_K_M 9.1 GB 13.9 tok/s Runs well
75Great quality (A) · 75 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. MiMo V2.6 Distill Qwen 9BXiaomi Q5_K_M 8.5 GB 3.2 tok/s Slow
75Great quality (A) · 75 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. SenseNova Loop 9B PreviewSenseTime Q5_K_M 8.9 GB 3.1 tok/s Slow
58Good quality (B) · 58 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. Maple Preview (20B-A1B)DeepGrove Q3_K_M 11.6 GB 28.6 tok/s Runs welltight fit
74Great quality (A) · 74 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. Ornith 1.5 9BDeepReinforce Q5_K_M 8.7 GB 3.1 tok/s Slow
73Great quality (A) · 73 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 9BAlibaba Q5_K_M 8.7 GB 3.1 tok/s Slow
72Great quality (A) · 72 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. Ornith 1.0 9BDeepReinforce Q5_K_M 8.7 GB 3.1 tok/s Slow
71Great quality (A) · 71 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. TMax 9BAi2 Q5_K_M 8.2 GB 3.4 tok/s Slow

Best Image models for the QNAP TS-1277 16.0 GB

Quality Model Quant Memory Speed Runs
84Great quality (A) · 84 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. FLUX 3 Image KleinBlack Forest Labs Q4 GGUF 10.2 GB 11.6 min Very slow
76Great quality (A) · 76 of 100: how capable the model is at FP8, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 4BBlack Forest Labs FP8 10.2 GB 1.5 min Slow
78Great quality (A) · 78 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. Z-Image TurboAlibaba (Tongyi) Q4 GGUF 10.1 GB 5.1 min Very slow
79Great quality (A) · 79 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. ERNIE-Image TurboBaidu Q4 GGUF 11.3 GB 6.5 min Very slowtight fit
76Great quality (A) · 76 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. Z-ImageAlibaba (Tongyi) Q4 GGUF 10.1 GB 34.5 min Very slow
78Great quality (A) · 78 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 9BBlack Forest Labs Q4 GGUF 8.0 GB 3.8 min Very slowencoder unloaded after use

Best Video models for the QNAP TS-1277 16.0 GB

Quality Model Quant Memory Speed Runs
49Fair quality (C) · 49 of 100: how capable the model is at FP8, whatever it runs on. Match score 64/100 (quality, fit, speed and memory use) sets the ranking. LTX-Video 2BLightricks FP8 10.8 GB 38.0 min Slowtight fit
83Great quality (A) · 83 of 100: how capable the model is at FP8, whatever it runs on. Match score 63/100 (quality, fit, speed and memory use) sets the ranking. Bernini-R A14B (video generation + editing)ByteDance FP8 10.7 GB 23.7 h Very slowtight fit · CPU offload
74Great quality (A) · 74 of 100: how capable the model is at FP8, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking. HY-OmniWeaving (8.3B, unified video)Tencent FP8 7.8 GB 17.5 h Very slowCPU offload
55Good quality (B) · 55 of 100: how capable the model is at FP16, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking. Wan 2.1 T2V 1.3BAlibaba FP16 8.4 GB 7.1 h Very slowencoder unloaded after use
55Good quality (B) · 55 of 100: how capable the model is at FP16, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking. Wan 2.1 VACE 1.3BAlibaba FP16 10.1 GB 7.7 h Very slowencoder unloaded after use

Best Decision models for the QNAP TS-1277 16.0 GB

Quality Model Quant Memory Speed Runs
78Great quality (A) · 78 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking. OpenAI Privacy FilterOpenAI Q8_0 2.4 GB 97 ms Runs great
86Excellent quality (A+) · 86 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. Jina Reranker v3.5Jina AI Q8_0 2.4 GB 2.1 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 4BAlibaba Q8_0 6.1 GB 13.9 s Very slow
84Great quality (A) · 84 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. Jina Reranker v3Jina AI Q8_0 2.4 GB 2.1 s Very slow
89Excellent quality (A+) · 89 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Qwen3 Reranker 8BAlibaba Q6_K 8.6 GB 28.3 s Very slow
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. GLiNER2.5 DecideFastino Q8_0 1.2 GB 913 ms Slow
88Excellent quality (A+) · 88 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. zerank-2ZeroEntropy Q8_0 6.1 GB 13.9 s Very slow
90Excellent quality (A+) · 90 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Skywork Reward V2 Llama 3.1 8BSkywork Q8_0 10.4 GB 55.7 s Very slowtight fit

Other products with the AMD Ryzen 5 1600 / 7 1700 / 2600 / 2700 NAS (16 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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