Zettlab D6

Products · · NAS

Zettlab D6

Processor
Rockchip RK3588
Memory (RAM)
16 GB
Launch price
$600
Released
2025

Product page (opens in a new tab) Full AI report

Specifications

MakerZettlab
TypeNAS
ProcessorRockchip RK3588 NAS (16 GB)
Memory (RAM)16.0 GB
Usable for AI models12.0 GB
Memory bandwidth34 GB/s
FP16 compute0.1 TFLOPS
Runs models onCPU cores
Drive bays6x SATA + 1x M.2 NVMe
NAS systemZettOS
Containers (Docker)Yes
Virtual machinesYes
Memory upgradeLPDDR4x · up to 16.0 GB per the maker · non-ECC
NotesRockchip RK3588. The 6 TOPS NPU runs ZettAI search, categorising and transcription on the device, but the maker's own table says AI Q&A chat runs 'via PC Computing Power'; an LLM on the NAS itself would mean a small model in Docker on the ARM CPU with 16 GB of soldered RAM.
Product pagezettlab.com (opens in a new tab)

Running AI on the Zettlab D6

It can, with limits: expect small models only, at modest speed. 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.

Apps you can install to run models

AppHow it installs
AnythingLLM From the NAS app store
Any Docker image In a container (Docker)
Ollama / Open WebUI or other model runners as Docker containers In a container (Docker)

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

AI features from Zettlab

FeatureWhat it doesWhere the AI runs
ZettAI AI Search Natural-language search across images, audio, video and documents stored on the NAS; maker says processing is 100% on-device. On the NAS
ZettAI AI Categories Automatic sorting and tagging of files and media. On the NAS
ZettAI AI Transcription / AI Clip Audio and video transcription and clip finding. On the NAS
ZettAI AI Q&A (via PC Computing Power) Cloud service or another computer

Best LLMs for the Zettlab D6

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 13.8 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 Zettlab D6

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 21.8 min Very slow
76Great quality (A) · 76 of 100: how capable the model is at FP8, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 4BBlack Forest Labs FP8 10.2 GB 2.9 min Very 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 9.6 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 12.3 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 65.1 min Very slow
87Excellent quality (A+) · 87 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. ERNIE-ImageBaidu Q8 GGUF 11.2 GB 84.8 min Very slowtight fit · encoder unloaded after use

Best Video models for the Zettlab D6

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 63/100 (quality, fit, speed and memory use) sets the ranking. LTX-Video 2BLightricks FP8 10.8 GB 71.8 min Very slowtight fit
83Great quality (A) · 83 of 100: how capable the model is at FP8, whatever it runs on. Match score 62/100 (quality, fit, speed and memory use) sets the ranking. Bernini-R A14B (video generation + editing)ByteDance FP8 10.7 GB 44.8 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 33.0 h Very slowCPU offload
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 T2V 1.3BAlibaba FP16 8.4 GB 13.4 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 14.5 h Very slowencoder unloaded after use

Best Decision models for the Zettlab D6

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 84/100 (quality, fit, speed and memory use) sets the ranking. OpenAI Privacy FilterOpenAI Q8_0 2.4 GB 162 ms Runs well
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 23.6 s Very slow
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 3.5 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 47.9 s Very 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 23.6 s Very slow
84Great quality (A) · 84 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. Jina Reranker v3Jina AI Q8_0 2.4 GB 3.5 s Very slow
90Excellent quality (A+) · 90 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. Skywork Reward V2 Llama 3.1 8BSkywork Q8_0 10.4 GB 94.7 s Very slowtight fit
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. GLiNER2.5 DecideFastino Q8_0 1.2 GB 1.5 s Very slow

Other products with the Rockchip RK3588 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.

Was this page helpful?