Datasheet for local AI49 models98 GPUsData read 2026-09-25
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Can the RTX 4070 Ti Super 16 GB run Wan 2.1 T2V 1.3B?

Video model · 1.3B16 GB GDDR6X · 256-bit · 672 GB/s · Ada LovelaceData 2026-09-25
Runs well
Yes — and comfortably.

Download 16-bit (2.8 GB). With the model's working memory it needs about 5.6 GB, leaving 10.4 GB spare on 16 GB. Quality: the original weights.

Best file16-bit
File size2.8 GB
VRAM needed~5.6 GB
System RAM16 GB+
Memory map · RTX 4070 Ti Super 16 GB5.6 GB / 16 GB
08 GB16 GB
Weights 16-bit · 2.8 GBWorking memory · 2.0 GBReserve · 0.8 GBFree · 10.4 GB
calculated from real file sizes plus working memory. Not yet measured on this setup. How this works.

01What to download

PartFileFolderSize
Modelwan2.1_t2v_1.3B_fp16.safetensors
16-bit · Comfy-Org/Wan_2.1_ComfyUI_repackaged
models/diffusion_models2.8 GBDownload →
Text encoderumt5_xxl_fp8_e4m3fn_scaled.safetensors
UMT5-XXL FP8 (scaled) · Comfy-Org/Wan_2.1_ComfyUI_repackaged
models/text_encoders6.7 GBDownload →
VAEwan_2.1_vae.safetensors
Wan 2.1 VAE · Comfy-Org/Wan_2.1_ComfyUI_repackaged
models/vae0.3 GBDownload →
Total download · keep about the same free on disk9.8 GB

Alternatives: UMT5-XXL FP16 (11.4 GB). The 16-bit text encoder is a little more faithful; the smaller one is chosen here because it loads faster and needs less RAM. 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 9.8 GB, plus roughly 6 GB for Windows, ComfyUI and a browser: 15.8 GB in total. With less RAM it still runs, but Windows starts swapping to disk and loading gets very slow. calculated

02Every Wan 2.1 1.3B file on 16 GB

FileSizeNeededOn this cardQualityDownload
16-bit ←
SAFETENSORS · Comfy-Org
2.8 GB5.6 GBfits · 10.4 GB sparethe original weightsHugging Face →
Q8_0
GGUF · samuelchristlie
1.5 GB4.3 GBfits · 11.7 GB sparepractically identical to the originalHugging Face →
Q6_K
GGUF · samuelchristlie
1.2 GB4.0 GBfits · 12.0 GB sparevery close to the originalHugging Face →
Q5_K_M
GGUF · samuelchristlie
1.1 GB3.9 GBfits · 12.1 GB spareclose; small differences in fine detailHugging Face →
Q4_K_M
GGUF · samuelchristlie
1.0 GB3.8 GBfits · 12.2 GB sparegood; some loss in fine detail and textHugging Face →
Q3_K_M
GGUF · samuelchristlie
0.7 GB3.5 GBfits · 12.5 GB sparenoticeable loss of detailHugging Face →

Sizes from the Hugging Face file listing, read 2026-09-25. “Needed” = file + 2 GB working memory for this model + 0.8 GB kept free for the system.

03The text encoder

UMT5-XXL: 11.4 GB as 16-bit, 6.7 GB as FP8, 3.7 GB as GGUF Q4_K_M. ComfyUI encodes the prompt first and can push the encoder out of VRAM before sampling, so it does not have to fit together with the model. On 16 GB the FP8 encoder fits on its own, so prompt encoding stays fast.

04About this GPU

The RTX 4070 Ti Super 16 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.)

RTX 4070 Ti Super 16 GB: 16 GB GDDR6X · 256-bit · 672 GB/s · Ada Lovelace. Everything that runs on the RTX 4070 Ti Super 16 GB →

05What more VRAM would change

Nothing to gain for this model: the RTX 4070 Ti Super 16 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 Wan 2.1 1.3B on a RTX 4070 Ti Super 16 GB, send your time per image and peak VRAM and it will appear here, credited.

07Questions

How much VRAM does Wan 2.1 1.3B need?

Around 3.5 GB with the smallest file (Q3_K_M) and 4.3 GB with an 8-bit file (Q8_0), counting working memory and a small system reserve. The full 16-bit file needs about 5.6 GB.

Which Wan 2.1 1.3B file should I download for the RTX 4070 Ti Super 16 GB?

16-bit (2.8 GB) from Comfy-Org/Wan_2.1_ComfyUI_repackaged.

Is FP8 faster than GGUF on the RTX 4070 Ti Super 16 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 Wan 2.1 1.3B on the RTX 4070 Ti Super 16 GB?

About 9.8 GB for the model file, text encoder and VAE listed on this page, and the same again free on disk. With a 16 GB card, 16 GB of system RAM or more is recommended.