Products · Zettlab · NAS
Zettlab D6 Ultra
- Processor
- Intel Core Ultra 5 125H
- Memory (RAM)
- 16, 32 or 96 GB
- Launch price
- $1,400
- Released
- 2026
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 Core Ultra 5 125H | 16.0 GB | 12.0 GB | 90 GB/s | 316 of 622 | $1,400 |
| Intel Core Ultra 5 125H | 32.0 GB | 26.2 GB | 90 GB/s | 350 of 622 | — |
| Intel Core Ultra 5 125H · upgraded to the maker's maximum | 96.0 GB | 83.5 GB | 90 GB/s | 375 of 622 | — |
Specifications 96.0 GB configuration
| Maker | Zettlab |
|---|---|
| Type | NAS |
| Processor | Intel Core Ultra 5 125H NAS (96 GB) · upgraded to the maker's maximum |
| Memory (RAM) | 96.0 GB |
| Usable for AI models | 83.5 GB |
| Memory bandwidth | 90 GB/s |
| FP16 compute | 0.7 TFLOPS |
| Runs models on | CPU cores |
| Drive bays | 6x SATA (3.5/2.5 inch) + 2x M.2 NVMe (PCIe 4.0 x4; 2280/2242/2230) |
| NAS system | ZettOS |
| Containers (Docker) | Yes |
| Virtual machines | Yes |
| Memory upgrade | DDR5 SO-DIMM, up to 5600 MT/s (non-ECC) · 2 slots · up to 96.0 GB per the maker · non-ECC |
| Graphics card options | PCIe: 1x SFF-8654 connector on the rear, PCIe 4.0 x8 (external cabled port, not an internal card slot; needs an…. External GPU: Through the SFF-8654 PCIe 4.0 x8 port with an external dock and power supply. 2x USB4 are also fitted, but…. Maker-supported graphics cards: Maker wiki FAQ (archived 2026-01-02): 'We'll support GTX 40/50 series GPUs' (sic, i.e. NVIDIA 40/50 series; RTX A-series untested). No model list published. |
| Availability | Discontinued (sold used or refurbished) |
| Notes | Intel Core Ultra 5 125H. Maker lists 'Local LLM and AI' and offline AI Q&A for the Ultra models, and TechRadar's review ran Gemma, Phi, QwQ, DeepSeek-R1 and Llama models on the D6 Ultra itself; Core Ultra 5 125H with up to 96 GB DDR5, plus Docker and VMs for other runners. |
| Product page | zettlab.com (opens in a new tab)Discontinued |
Running AI on the Zettlab D6 Ultra
Yes, it runs AI models on the NAS itself. Models run on its CPU cores, and this configuration leaves about 83.5 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 |
|---|---|
| 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) |
AI features from Zettlab
| Feature | What it does | Where 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 (Knowledge QA) | Chat / question answering over the user's own files (RAG) with a built-in large language model that works offline. | On the NAS |
| Local LLM and AI | Maker's compare table lists 'Local LLM and AI' for the Ultra models only, and the headline feature list says 'Local LLM'; model names and speeds are not published. | On the NAS |
| ZettAI local LLM chat (model library) | Chat with a language model hosted on the NAS. Maker's compare table lists 'Local LLM and AI' for the Ultra models only. | On the NAS |
Best LLMs for the Zettlab D6 Ultra 96.0 GB
| Quality | Model | Quant | Memory | Speed | Runs |
|---|---|---|---|---|---|
| 86Excellent quality (A+) · 86 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. | Kolibri 1 (78B-A3.5B) | Q4_K_M | 55.1 GB | 20.9 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 88/100 (quality, fit, speed and memory use) sets the ranking. | Qwen3 Coder Next (80B-A3B) | Q4_K_M | 56.1 GB | 23.9 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 88/100 (quality, fit, speed and memory use) sets the ranking. | Qwen3-Next 80B-A3B Thinking | Q4_K_M | 57.1 GB | 23.9 tok/s | Runs well |
| 79Great quality (A) · 79 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. | Qwen3 Next 80B-A3B Instruct | Q4_K_M | 57.1 GB | 23.9 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 | 74.2 GB | 15.5 tok/s | Runs welltight fit |
| 85Excellent quality (A+) · 85 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. | Flint (40B-A2.5B) | Q4_K_M | 31.8 GB | 28.2 tok/s | Runs well |
| 88Excellent quality (A+) · 88 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. | Qwen3.6 35B-A3B | Q4_K_M | 29.4 GB | 23.9 tok/s | Runs well |
| 88Excellent quality (A+) · 88 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. | MiniCPM-V 4.7 35B-A3B | Q4_K_M | 28.9 GB | 23.9 tok/s | Runs well |
| 88Excellent quality (A+) · 88 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. | Qwen3.5 35B-A3B | Q4_K_M | 29.4 GB | 23.9 tok/s | Runs well |
| 87Excellent quality (A+) · 87 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. | Nex N2 Mini (35B-A3B) | Q4_K_M | 28.9 GB | 23.9 tok/s | Runs well |
Best Image models for the Zettlab D6 Ultra 96.0 GB
| Quality | Model | Quant | Memory | Speed | Runs |
|---|---|---|---|---|---|
| 93Excellent quality (A+) · 93 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. | Qwen-Image 2.1 | FP16 | 57.0 GB | 64.4 min | Very slow |
| 92Excellent quality (A+) · 92 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. | Ideogram 4 | FP16 | 57.3 GB | 26.9 min | Very slow |
| 91Excellent quality (A+) · 91 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. | FLUX.2 [dev] | Q8 GGUF | 61.9 GB | 44.5 min | Very slow |
| 90Excellent quality (A+) · 90 of 100: how capable the model is at FP8, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. | Cosmos3-Super Text2Image (64B) | FP8 | 69.1 GB | 38.7 min | Very slow |
| 90Excellent quality (A+) · 90 of 100: how capable the model is at FP16, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. | Qwen-Image 2512 | FP16 | 63.8 GB | 1.6 h | Very slow |
| 91Excellent quality (A+) · 91 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. | MiniMax H3 Image | FP8 | 72.0 GB | 9.7 min | Very slowtight fit |
Best Video models for the Zettlab D6 Ultra 96.0 GB
| Quality | Model | Quant | Memory | Speed | Runs |
|---|---|---|---|---|---|
| 89Excellent quality (A+) · 89 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. | MiniMax H3 (33B, video + audio) | Q8 GGUF | 68.2 GB | 21.4 h | Very slow |
| 87Excellent quality (A+) · 87 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. | LTX-2.5 (22B, video + audio) | Q8 GGUF | 49.8 GB | 1.9 h | Very slow |
| 86Excellent quality (A+) · 86 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. | Wan 2.2 I2V A14B | FP16 | 58.0 GB | 28.6 h | Very slow |
| 86Excellent quality (A+) · 86 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. | Wan 2.2 T2V A14B | FP16 | 58.0 GB | 28.6 h | Very slow |
| 84Great quality (A) · 84 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. | HunyuanVideo 1.5 (8.3B) | FP16 | 55.2 GB | 32.2 h | Very slow |
Best Decision models for the Zettlab D6 Ultra 96.0 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 | 49 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 | 115 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 | 8.2 GB | 880 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 | 386 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 | 8.2 GB | 880 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 | 11.8 GB | 5.9 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 | 643 ms | 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 8B | Q8_0 | 16.3 GB | 12.0 s | Very slow |
Other products with the Intel Core Ultra 5 125H NAS (96 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.