SD Turbo on Intel Celeron J4025 / J4005 NAS (8 GB)

Can the Intel Celeron J4025 / J4005 NAS (8 GB) run SD Turbo?

Yes, but slowly

Slow. At FP16 it needs about 3.3 GB of 5.2 GB usable and takes about 44 s per image.

Best precision: FP16
Memory mode: Everything on GPU
Time per image: 44 s
Output: 512×512, 1 steps

Download SD Turbo

Original weights · Hugging Face

Full-precision files from Stability AI, for fine-tuning, vLLM, Transformers, Diffusers or ComfyUI.

huggingface.co/stabilityai/sd-turbo (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from Stability AI. The weights themselves download from Hugging Face.

github.com/Stability-AI/generative-models (opens in a new tab)

git clone https://github.com/Stability-AI/generative-models

Links checked 7 days ago against Hugging Face, Ollama and GitHub.

How it’s rated

Quality 28Basic quality (D) · 28 of 100: how capable the model is at FP16, whatever it runs on. Match score 59/100 (quality, fit, speed and memory use) sets the ranking.: How capable the model itself is at FP16, 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 Slow: How well it runs on the Intel Celeron J4025 / J4005 NAS (8 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.	12.6 / 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.	25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	7.1 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	14.5 / 15
Match score	59.3 / 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 Celeron J4025 / J4005 NAS (8 GB)

Quant	Memory needed	Available	Speed	Memory mode	Runs	Quality	Download
`FP16`	3.3 GB	5.2 GB	44 s	Everything on GPU	Slow	28Basic quality (D) · 28 of 100: how capable the model is at FP16, whatever it runs on. Match score 59/100 (quality, fit, speed and memory use) sets the ranking.	Original weights (opens in a new tab)

Other hardware that runs it

28Basic quality (D) · 28 of 100: how capable the model is at FP16, whatever it runs on. Match score 62/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 4060 FP16 · 0.3 s · Runs great
28Basic quality (D) · 28 of 100: how capable the model is at FP16, whatever it runs on. Match score 59/100 (quality, fit, speed and memory use) sets the ranking. Apple M1 (16 GB) FP16 · 2.0 s · Runs great
28Basic quality (D) · 28 of 100: how capable the model is at FP16, whatever it runs on. Match score 59/100 (quality, fit, speed and memory use) sets the ranking. Apple M4 (16 GB) FP16 · 1.4 s · Runs great
28Basic quality (D) · 28 of 100: how capable the model is at FP16, whatever it runs on. Match score 58/100 (quality, fit, speed and memory use) sets the ranking. Intel Arc B580 FP16 · 0.3 s · Runs great
28Basic quality (D) · 28 of 100: how capable the model is at FP16, whatever it runs on. Match score 58/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 3060 12GB FP16 · 0.3 s · Runs great
28Basic quality (D) · 28 of 100: how capable the model is at FP16, whatever it runs on. Match score 58/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 4070 SUPER FP16 · 0.2 s · Runs great

Quick answers

How much memory does SD Turbo need on the Intel Celeron J4025 / J4005 NAS 8GB?

At FP16 it needs about 3.3 GB. The Intel Celeron J4025 / J4005 NAS 8GB has 5.2 GB usable.

How long does SD Turbo take on the Intel Celeron J4025 / J4005 NAS 8GB?

About 44 s per image at FP16 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.