HiDream-I1 Fast on Intel Atom C3758 NAS (16 GB)

Can the Intel Atom C3758 NAS (16 GB) run HiDream-I1 Fast?

Barely: it runs very slowly (CPU offload)

Very slow (CPU offload). At Q8 GGUF it needs about 9.3 GB of 12.0 GB usable and takes about 60.3 min per image.

Best precision: Q8 GGUF
Memory mode: Sequential CPU offload
Time per image: 60.3 min
Output: 1024×1024, 16 steps

Download HiDream-I1 Fast

Recommended for the Intel Atom C3758 NAS (16 GB): q8_gguf. Every other precision has its own download link in the table below.

Quantized files · GGUF for ComfyUI

Smaller GGUF versions for ComfyUI (with the ComfyUI-GGUF node). No sign-in needed; the model’s license still applies.

Download the q8_gguf (Q8_0) file (opens in a new tab)

huggingface.co/city96/HiDream-I1-Fast-gguf (opens in a new tab)

Original weights · Hugging Face

Full-precision files from HiDream.ai, for fine-tuning, vLLM, Transformers, Diffusers or ComfyUI.

huggingface.co/HiDream-ai/HiDream-I1-Fast (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from HiDream.ai. The weights themselves download from Hugging Face.

github.com/HiDream-ai/HiDream-I1 (opens in a new tab)

git clone https://github.com/HiDream-ai/HiDream-I1

Links checked 3 days ago against Hugging Face, Ollama and GitHub.

How it’s rated

Quality 75Great quality (A) · 75 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking.: How capable the model itself is at Q8 GGUF, from its editorial quality tier scaled by the quantization or precision. It’s the same on any hardware that runs this variant. Scale: A+ 85+ · A 70+ · B 55+ · C 40+ · D under 40.
Runs Very slowCPU offload: How well it runs on the Intel Atom C3758 NAS (16 GB): speed, capped by how well it fits in memory. Runs great: 30+ tokens/s (or near the image, video or decision speed target) · Runs well: 10+ tokens/s · Slow: 3+ tokens/s · Very slow: under 3 · Won’t run: doesn’t fit even with offload. A tight fit or RAM offload caps it at Runs well; heavy offload caps it at Slow.

Match score

To order lists, each result also gets a match score out of 100 from four parts. It favors the most capable model that still runs well.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.	33.9 / 45
Memory fitFull marks when the model fits in the share of the NAS’s memory that models can use (the rest stays with the NAS system and its storage services); fewer when it goes past that limit.	12.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	0.8 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	15.0 / 15
Match score	61.6 / 100

The match score orders results; it is not shown as a grade. Quality and Runs are the two ratings in the tables.

Every precision on the Intel Atom C3758 NAS (16 GB)

Quant	Memory needed	Available	Speed	Memory mode	Runs	Quality	Download
`FP16`	14.8 GB	12.0 GB	—	—	Won't run	76Great quality (A) · 76 of 100: how capable the model is at FP16, whatever it runs on. Match score 10/100 (quality, fit, speed and memory use) sets the ranking.	Original weights (opens in a new tab)
`FP8`	8.8 GB	12.0 GB	47.2 min	Sequential CPU offload	Very slowCPU 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.	Original weights (opens in a new tab)
`Q8 GGUF`	9.3 GB	12.0 GB	60.3 min	Sequential CPU offload	Very slowCPU offload	75Great quality (A) · 75 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab)
`Q4 GGUF`	6.5 GB	12.0 GB	62.9 min	Sequential CPU offload	Very slowCPU offload	70Great quality (A) · 70 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 56/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab)
`NF4`	6.2 GB	12.0 GB	57.7 min	Sequential CPU offload	Very slowCPU offload	70Great quality (A) · 70 of 100: how capable the model is at NF4, whatever it runs on. Match score 56/100 (quality, fit, speed and memory use) sets the ranking.	Original weights (opens in a new tab)

Other hardware that runs it

76Great quality (A) · 76 of 100: how capable the model is at FP16, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA RTX PRO 6000 Blackwell FP16 · 7.3 s · Runs great
70Great quality (A) · 70 of 100: how capable the model is at NF4, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 5090 NF4 · 9.2 s · Runs great
76Great quality (A) · 76 of 100: how capable the model is at FP16, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. AMD Ryzen AI Max+ 395 (128 GB) FP16 · 19 s · Runs well
76Great quality (A) · 76 of 100: how capable the model is at FP16, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA RTX Spark N1X (6144-core GPU) (128 GB) FP16 · 22 s · Runs well
74Great quality (A) · 74 of 100: how capable the model is at FP8, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 4090 FP8 · 9.5 s · Runs great (encoder in RAM)
74Great quality (A) · 74 of 100: how capable the model is at FP8, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. AMD Radeon RX 7900 XTX FP8 · 11 s · Runs great (encoder in RAM)

Quick answers

How much memory does HiDream-I1 Fast need on the Intel Atom C3758 NAS 16GB?

At Q8 GGUF it needs about 9.3 GB. The Intel Atom C3758 NAS 16GB has 12.0 GB usable.

How long does HiDream-I1 Fast take on the Intel Atom C3758 NAS 16GB?

About 60.3 min per image at Q8 GGUF and default settings, an estimate scaled from a reference timing by this hardware’s compute speed.

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.