Can the RTX 3060 Ti 8 GB run Wan 2.1 T2V 1.3B?
Download 16-bit (2.8 GB). With the model's working memory it needs about 5.6 GB, leaving 2.4 GB spare on 8 GB. Quality: the original weights.
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | wan2.1_t2v_1.3B_fp16.safetensors 16-bit · Comfy-Org/Wan_2.1_ComfyUI_repackaged | models/diffusion_models | 2.8 GB | Download → |
| Text encoder | umt5_xxl_fp8_e4m3fn_scaled.safetensors UMT5-XXL FP8 (scaled) · Comfy-Org/Wan_2.1_ComfyUI_repackaged | models/text_encoders | 6.7 GB | Download → |
| VAE | wan_2.1_vae.safetensors Wan 2.1 VAE · Comfy-Org/Wan_2.1_ComfyUI_repackaged | models/vae | 0.3 GB | Download → |
| Total download · keep about the same free on disk | 9.8 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 8 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit ← SAFETENSORS · Comfy-Org | 2.8 GB | 5.6 GB | fits · 2.4 GB spare | the original weights | Hugging Face → |
| Q8_0 GGUF · samuelchristlie | 1.5 GB | 4.3 GB | fits · 3.7 GB spare | practically identical to the original | Hugging Face → |
| Q6_K GGUF · samuelchristlie | 1.2 GB | 4.0 GB | fits · 4.0 GB spare | very close to the original | Hugging Face → |
| Q5_K_M GGUF · samuelchristlie | 1.1 GB | 3.9 GB | fits · 4.1 GB spare | close; small differences in fine detail | Hugging Face → |
| Q4_K_M GGUF · samuelchristlie | 1.0 GB | 3.8 GB | fits · 4.2 GB spare | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M GGUF · samuelchristlie | 0.7 GB | 3.5 GB | fits · 4.5 GB spare | noticeable loss of detail | Hugging 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 8 GB the FP8 encoder fits on its own, so prompt encoding stays fast.
04About this GPU
The RTX 3060 Ti 8 GB (Ampere) has no FP8 compute. FP8 files still load and save memory, but ComfyUI converts them back before the maths, so there is no speed gain — Q8_0 GGUF is the closer-to-original 8-bit choice. ComfyUI can compute INT8 files natively on NVIDIA, which is worth a try where a model offers one.
RTX 3060 Ti 8 GB: 8 GB GDDR6 · 256-bit · 448 GB/s · Ampere. Everything that runs on the RTX 3060 Ti 8 GB →
05What more VRAM would change
Nothing to gain for this model: the RTX 3060 Ti 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.
What changes from the RTX 3060 Ti 8 GB to the RTX 5060 Ti 16 GB →
06Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run Wan 2.1 1.3B on a RTX 3060 Ti 8 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 3060 Ti 8 GB?
16-bit (2.8 GB) from Comfy-Org/Wan_2.1_ComfyUI_repackaged.
Is FP8 faster than GGUF on the RTX 3060 Ti 8 GB?
No. This GPU has no FP8 compute, so ComfyUI converts FP8 weights back before the maths. FP8 only saves memory here; Q8_0 GGUF is the closer-to-original 8-bit pick.
How much do I need to download for Wan 2.1 1.3B on the RTX 3060 Ti 8 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 8 GB card, 16 GB of system RAM or more is recommended.