Zettlab D6 Ultra

Products · · NAS

ZettLab D6 Ultra

Processor
Intel Core Ultra 5 125H
Memory (RAM)
32 or 96 GB

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
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

MakerZettlab
TypeNAS
ProcessorIntel Core Ultra 5 125H NAS (96 GB) · upgraded to the maker's maximum
Memory (RAM)96.0 GB
Usable for AI models83.5 GB
Memory bandwidth90 GB/s
FP16 compute0.7 TFLOPS
Runs models onCPU cores
Drive bays6x SATA + 2x M.2 NVMe (PCIe 4.0 x4)
NAS systemZettOS
Containers (Docker)Yes
Memory upgradeDDR5 · up to 96.0 GB per the maker
Graphics card optionsPCIe: SFF-8654 connector carrying PCIe 4.0 x8 (not a standard card slot); GPU use not stated by maker. External GPU: 2x USB4; eGPU support not stated by maker.
AvailabilityAnnounced, not on general sale when checked
NotesIntel Core Ultra 5 125H. Core Ultra 5 125H with Arc graphics, RAM expandable to 96 GB and Docker gives enough for mid-size local models, if the unit ships as described. Announced or in crowdfunding; not on general sale when checked (November 2026).
Product pagezettlab.com (opens in a new tab)

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.

AI features from Zettlab

FeatureWhat it doesWhere the AI runs
ZettAI (photo recognition, OCR, transcription, semantic search) Tags and searches photos, reads text in images, transcribes audio with speaker labels and searches files by meaning, using the 6 TOPS NPU. On the NAS
AI chat / document analysis AI Q&A over files; the maker comparison table lists "Local LLM and AI" on the Ultra models (on the NAS itself). Not independently tested. 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)Aleph Alpha 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)Alibaba 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 ThinkingAlibaba 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 InstructAlibaba 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 120BOpenAI 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)Recursive 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-A3BAlibaba 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-A3BOpenBMB 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-A3BAlibaba 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)Nex-AGI 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 2.1Alibaba 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 4Ideogram 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]Black Forest Labs 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)NVIDIA 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 2512Alibaba 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 ImageMiniMax 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)MiniMax 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)Lightricks 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 A14BAlibaba 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 A14BAlibaba 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)Tencent 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 FilterOpenAI 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 22MMeta 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 v3.5Jina AI 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 DecideFastino 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 v3Jina AI 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 4BAlibaba 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-DecisionsSber AI 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 8BAlibaba 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.

Was this page helpful?