Can the RTX 3080 10 GB run LTX-2 (19B)?
The smallest sensible file, Q4_K_M (12.8 GB), needs about 17.6 GB — 7.6 GB more than RTX 3080 10 GB has. ComfyUI can still run it by streaming part of the model from system RAM. How much slower that is depends on your ComfyUI version, the file format and the PCIe link — see the note below.
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | ltx-2-19b-dev-Q4_K_M.gguf Q4_K_M · unsloth/LTX-2-GGUF | models/unet | 12.8 GB | Download → |
| Text encoder | gemma_3_12B_it_fp8_scaled.safetensors Gemma 3 12B FP8 (scaled) · Comfy-Org/ltx-2 | models/text_encoders | 13.2 GB | Download → |
| VAE | ltx-2-19b-dev_video_vae.safetensors LTX-2 video VAE · unsloth/LTX-2-GGUF | models/vae | 2.4 GB | Download → |
| Also needed | ltx-2-19b-dev_audio_vae.safetensors LTX-2 audio VAE · unsloth/LTX-2-GGUF | models/vae | 0.2 GB | Download → |
| Also needed | ltx-2-19b-dev_embeddings_connectors.safetensors LTX-2 text embeddings connectors (projection) · unsloth/LTX-2-GGUF | models/text_encoders | 2.9 GB | Download → |
| Total download · keep about the same free on disk | 31.6 GB | |||
Alternatives: Gemma 3 12B FP4 mixed (9.4 GB); Gemma 3 12B BF16 (24.4 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. FP4 files are listed only as alternatives unless the GPU is an RTX 50 (Blackwell). Only for some workflows: LTX-2 spatial upscaler x2 (1.0 GB, official two-stage template). 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: 48 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 31.6 GB, plus roughly 6 GB for Windows, ComfyUI and a browser: 37.6 GB in total. With less RAM it still runs, but Windows starts swapping to disk and loading gets very slow. calculated
02Every LTX-2 file on 10 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit GGUF · unsloth | 37.8 GB | 42.6 GB | 32.6 GB too big | the original weights | Hugging Face → |
| Q8_0 GGUF · unsloth | 20.4 GB | 25.2 GB | 15.2 GB too big | practically identical to the original | Hugging Face → |
| Q6_K GGUF · unsloth | 16.0 GB | 20.8 GB | 10.8 GB too big | very close to the original | Hugging Face → |
| Q5_K_M GGUF · unsloth | 14.3 GB | 19.1 GB | 9.1 GB too big | close; small differences in fine detail | Hugging Face → |
| Q4_K_M ← GGUF · unsloth | 12.8 GB | 17.6 GB | 7.6 GB too big | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M GGUF · unsloth | 10.1 GB | 14.9 GB | 4.9 GB too big | noticeable loss of detail | Hugging Face → |
| Q2_K GGUF · unsloth | 8.1 GB | 12.9 GB | 2.9 GB too big | heavy loss; a last resort | Hugging Face → |
Sizes from the Hugging Face file listing, read 2026-09-25. “Needed” = file + 4 GB working memory for this model + 0.8 GB kept free for the system.
03The text encoder
Gemma 3 12B: 24.4 GB as 16-bit, 13.2 GB as FP8, 9.4 GB as FP4 mixed. 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 10 GB the encoder itself is too big for VRAM, so let it run from system RAM: slower prompt encoding, same images.
04About this GPU
The RTX 3080 10 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 3080 10 GB: 10 GB GDDR6X · 320-bit · 760 GB/s · Ampere. Everything that runs on the RTX 3080 10 GB →
05What more VRAM would change
With 32 GB you could run LTX-2 at 8-bit or better (Q8_0, 20.4 GB) with no offloading: for example on the RTX 5090 32 GB.
What changes from the RTX 3080 10 GB to the RTX 3090 24 GB → · What changes from the RTX 3080 10 GB to the RTX 5070 Ti 16 GB →
06Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run LTX-2 on a RTX 3080 10 GB, send your time per image and peak VRAM and it will appear here, credited.
07Questions
How much VRAM does LTX-2 need?
Around 12.9 GB with the smallest file (Q2_K) and 25.2 GB with an 8-bit file (Q8_0), counting working memory and a small system reserve. The full 16-bit file needs about 42.6 GB.
Which LTX-2 file should I download for the RTX 3080 10 GB?
Q4_K_M (12.8 GB) from unsloth/LTX-2-GGUF. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.
Is FP8 faster than GGUF on the RTX 3080 10 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 LTX-2 on the RTX 3080 10 GB?
About 31.6 GB for the model file, text encoder and VAE listed on this page, and the same again free on disk. With a 10 GB card, 48 GB of system RAM or more is recommended.