Datasheet for local AI49 models98 GPUsData read 2026-09-25
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Can the RTX 5070 Laptop 8 GB run SDXL 1.0?

Image model · 3.5B8 GB GDDR7 · 128-bit · 384 GB/s · Blackwell · 50–100 WData 2026-09-25
Runs well
Yes — and comfortably.

Download 16-bit (6.9 GB). With the model's working memory it needs about 7.1 GB, leaving 0.9 GB spare on 8 GB. Quality: the original weights.

Best file16-bit
File size6.9 GB
VRAM needed~7.1 GB
System RAM16 GB+
Memory map · RTX 5070 Laptop 8 GB7.1 GB / 8 GB
04 GB8 GB
Weights 16-bit · 5.1 GBWorking memory · 1.2 GBReserve · 0.8 GBFree · 0.9 GB
calculated from real file sizes plus working memory. Not yet measured on this setup. How this works.

01What to download

PartFileFolderSize
Checkpointsd_xl_base_1.0.safetensors
16-bit · stabilityai/stable-diffusion-xl-base-1.0
models/checkpoints6.9 GBDownload →
Total download · keep about the same free on disk6.9 GB

One file: the checkpoint already contains the text encoders and the VAE. Sizes read from Hugging Face (2026-09-25). “Download” links start the file directly; the file name links are the same files the official ComfyUI workflows use.

System RAM: 16 GB or more. ComfyUI keeps the model file, the text encoder and the VAE in system RAM and moves them to the GPU as needed. With this set of files that is about 6.9 GB, plus roughly 6 GB for Windows, ComfyUI and a browser: 12.9 GB in total. With less RAM it still runs, but Windows starts swapping to disk and loading gets very slow. calculated

02Every SDXL file on 8 GB

FileSizeNeededOn this cardQualityDownload
16-bit ←
SAFETENSORS · stabilityai
6.9 GB7.1 GBfits · 0.9 GB sparethe original weightsHugging Face →

Sizes from the Hugging Face file listing, read 2026-09-25. “Needed” = file + 1.2 GB working memory for this model + 0.8 GB kept free for the system. The 6.94 GB checkpoint also holds the two text encoders and the VAE. During sampling only the UNet (about 5.1 GB at 16-bit, 2.6B parameters) has to sit in VRAM, so that is the figure used for the 16-bit file.

03The text encoder

The text encoder is inside the checkpoint, so there is nothing extra to download.

04About this GPU

The RTX 5070 Laptop 8 GB is a Blackwell GPU with FP8 and FP4 hardware: ComfyUI computes Comfy-Org's FP8 files natively here, and NVFP4 files (where a model offers them) are faster still. As a laptop GPU it runs at a lower power limit than desktop cards (50–100 W depending on the laptop). The memory verdicts are the same; speed depends heavily on how much power the laptop maker allows.

RTX 5070 Laptop 8 GB: 8 GB GDDR7 · 128-bit · 384 GB/s · Blackwell · 50–100 W. Everything that runs on the RTX 5070 Laptop 8 GB →

05What more VRAM would change

Nothing to gain for this model: the RTX 5070 Laptop 8 GB already runs a top-quality file entirely in VRAM. More memory would only help with bigger images, longer clips or several models at once.

06Measured and reported results

Nobody has sent measured numbers for this pair yet. If you run SDXL on a RTX 5070 Laptop 8 GB, send your time per image and peak VRAM and it will appear here, credited.

07Questions

How much VRAM does SDXL need?

Around 7.1 GB with the smallest file (16-bit), counting working memory and a small system reserve.

Which SDXL file should I download for the RTX 5070 Laptop 8 GB?

16-bit (6.9 GB) from stabilityai/stable-diffusion-xl-base-1.0.

Is FP8 faster than GGUF on the RTX 5070 Laptop 8 GB?

It can be. This GPU has FP8 hardware, and ComfyUI computes FP8 natively for files made for it (Comfy-Org's fp8_scaled files), or for any FP8 file with the --fast fp8_matrix_mult option. GGUF files are unpacked on the fly, which costs some speed.

How much do I need to download for SDXL on the RTX 5070 Laptop 8 GB?

About 6.9 GB for the model file, text encoder and VAE listed on this page, and the same again free on disk. With a 8 GB card, 16 GB of system RAM or more is recommended.