Can the RTX 4050 Laptop 6 GB run Stable Diffusion 3.5 Large?
Not entirely. Even Q4_1 is 1.6 GB over 6 GB, so ComfyUI keeps part of it in system RAM.
Nothing fits entirely, but Q4_1 (5.3 GB) overflows by only about 1.6 GB. ComfyUI keeps that part in system RAM automatically: slower than a full fit, but usable.
01With more VRAM
With 12 GB you could run SD 3.5 Large at 8-bit or better (Q8_0, 8.8 GB) with no offloading: for example on the RTX 5070 12 GB, RTX 4070 Super 12 GB, RTX 4070 12 GB.
02Every SD 3.5 Large file on 6 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit SAFETENSORS · stabilityai | 16.5 GB | 18.8 GB | 12.8 GB too big | the original weights | Hugging Face → |
| Q8_0 GGUF · city96 | 8.8 GB | 11.1 GB | 5.1 GB too big | practically identical to the original | Hugging Face → |
| Q5_1 GGUF · city96 | 6.3 GB | 8.6 GB | 2.6 GB too big | close; small differences in fine detail | Hugging Face → |
| Q4_1 ← GGUF · city96 | 5.3 GB | 7.6 GB | spills 1.6 GB | good; some loss in fine detail and text | Hugging Face → |
“Needed” adds 1.5 GB of working memory for SD 3.5 Large and a 0.8 GB reserve. Sizes 2026-10-01.
03What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | sd3.5_large-Q4_1.gguf Q4_1 · city96/stable-diffusion-3.5-large-gguf | models/unet | 5.3 GB | Download → |
| Text encoder | t5xxl_fp8_e4m3fn.safetensors T5-XXL FP8 · Comfy-Org/stable-diffusion-3.5-fp8 | models/text_encoders | 4.9 GB | Download → |
| Text encoder | clip_l.safetensors CLIP-L · Comfy-Org/stable-diffusion-3.5-fp8 | models/text_encoders | 0.2 GB | Download → |
| Text encoder | clip_g.safetensors CLIP-G · Comfy-Org/stable-diffusion-3.5-fp8 | models/text_encoders | 1.4 GB | Download → |
| VAE | diffusion_pytorch_model.safetensors SD 3.5 VAE (gated repo: log in and accept the licence first) · stabilityai/stable-diffusion-3.5-large | models/vae | 0.2 GB | Download → |
| Total download · keep about the same free on disk | 12.0 GB | |||
Alternatives: T5-XXL FP16 (9.8 GB). Sizes from Hugging Face, 2026-10-01.
04Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run SD 3.5 Large on a RTX 4050 Laptop 6 GB, send your time per image and peak VRAM and it will appear here, credited.
05About the RTX 4050 Laptop 6 GB
The RTX 4050 Laptop 6 GB is an Ada Lovelace GPU with hardware FP8, so ComfyUI can compute Comfy-Org's FP8 files natively: small and fast. (Plain FP8 files use FP8 maths with the --fast fp8_matrix_mult option.) As a laptop GPU it runs at a lower power limit than desktop cards (35–115 W depending on the laptop). The memory verdicts are the same; speed depends heavily on how much power the laptop maker allows.
6 GB GDDR6 · 96-bit · Ada Lovelace · 35–115 W. Everything that runs on it →
06Questions
How much VRAM does SD 3.5 Large need?
Around 7.6 GB with the smallest file (Q4_1) and 11.1 GB with an 8-bit file (Q8_0). The full 16-bit file needs about 18.8 GB.
Which SD 3.5 Large file should I download for the RTX 4050 Laptop 6 GB?
Q4_1 (5.3 GB) from city96/stable-diffusion-3.5-large-gguf. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.
How much do I need to download for SD 3.5 Large on the RTX 4050 Laptop 6 GB?
12.0 GB: sd3.5_large-Q4_1.gguf, t5xxl_fp8_e4m3fn.safetensors, clip_l.safetensors, clip_g.safetensors, diffusion_pytorch_model.safetensors.