Stable Diffusion 3.5 Large Turbo on Intel Core i5-1240P / i5-1340P NAS (16 GB)
Can the Intel Core i5-1240P / i5-1340P NAS (16 GB) run Stable Diffusion 3.5 Large Turbo?
Barely: it runs very slowly (encoder unloaded after use)
Very slow (encoder unloaded after use). At Q4 GGUF it needs about 7.5 GB of 12.0 GB usable and takes about 3.0 min per image.
- Best precision
Q4 GGUF- Memory mode
- Text encoder offloaded
- Time per image
- 3.0 min
- Output
- 1024×1024, 4 steps
Download Stable Diffusion 3.5 Large Turbo
Recommended for the Intel Core i5-1240P / i5-1340P NAS (16 GB): q4_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 q4_gguf (Q4_0) file (opens in a new tab)
huggingface.co/city96/stable-diffusion-3.5-large-turbo-gguf (opens in a new tab)
Original weights · Hugging Face
Full-precision files from Stability AI, for fine-tuning, vLLM, Transformers, Diffusers or ComfyUI.
huggingface.co/stabilityai/stable-diffusion-3.5-large-turbo (opens in a new tab)
Official repo · GitHub
Reference code, inference scripts and docs from Stability AI. The weights themselves download from Hugging Face.
github.com/Stability-AI/sd3.5 (opens in a new tab)
git clone https://github.com/Stability-AI/sd3.5How it’s rated
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 quality | 25.9 / 45 | |
|---|---|---|
| Memory fit | 20.0 / 25 | |
| Speed | 3.5 / 15 | |
| Memory use | 14.3 / 15 | |
| Match score | 63.8 / 100 |
Every precision on the Intel Core i5-1240P / i5-1340P NAS (16 GB)
| Quant | Memory needed | Available | Speed | Memory mode | Runs | Quality | Download |
|---|---|---|---|---|---|---|---|
FP16 | 8.1 GB | 12.0 GB | 3.1 min | Sequential CPU offload | Very slowCPU offload | 62Good quality (B) · 62 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. | Original weights (opens in a new tab) |
FP8 | 10.7 GB | 12.0 GB | 2.3 min | Text encoder offloaded | Very slowtight fit · encoder unloaded after use | 60Good quality (B) · 60 of 100: how capable the model is at FP8, whatever it runs on. Match score 64/100 (quality, fit, speed and memory use) sets the ranking. | Original weights (opens in a new tab) |
Q8 GGUF | 11.3 GB | 12.0 GB | 2.9 min | Text encoder offloaded | Very slowtight fit · encoder unloaded after use | 61Good quality (B) · 61 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 64/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q4 GGUF | 7.5 GB | 12.0 GB | 3.0 min | Text encoder offloaded | Very slowencoder unloaded after use | 57Good quality (B) · 57 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 63/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Other hardware that runs it
-
61Good quality (B) · 61 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 7900 XTX
-
61Good quality (B) · 61 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 3090
-
61Good quality (B) · 61 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4090
-
62Good quality (B) · 62 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.
Apple M4 Max (64 GB)
-
57Good quality (B) · 57 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 9070 XT
-
57Good quality (B) · 57 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4060 Ti 16GB
Quick answers
How much memory does Stable Diffusion 3.5 Large Turbo need on the Intel Core i5-1240P / i5-1340P NAS 16GB?
At Q4 GGUF it needs about 7.5 GB. The Intel Core i5-1240P / i5-1340P NAS 16GB has 12.0 GB usable.
How long does Stable Diffusion 3.5 Large Turbo take on the Intel Core i5-1240P / i5-1340P NAS 16GB?
About 3.0 min per image at Q4 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.