Can the RTX 4080 Super 16 GB run LTX-2 (19B)?
Download Q3_K_M (10.1 GB). With the model's working memory it needs about 14.9 GB, leaving 1.1 GB spare on 16 GB. Quality: noticeable loss of detail. For better quality, Q4_K_M (12.8 GB) also runs, with about 1.6 GB spilling into system RAM — a little slower, still practical.
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | ltx-2-19b-dev-Q3_K_M.gguf Q3_K_M · unsloth/LTX-2-GGUF | models/unet | 10.1 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 | 28.8 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 28.8 GB, plus roughly 6 GB for Windows, ComfyUI and a browser: 34.8 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 16 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit GGUF · unsloth | 37.8 GB | 42.6 GB | 26.6 GB too big | the original weights | Hugging Face → |
| Q8_0 GGUF · unsloth | 20.4 GB | 25.2 GB | 9.2 GB too big | practically identical to the original | Hugging Face → |
| Q6_K GGUF · unsloth | 16.0 GB | 20.8 GB | 4.8 GB too big | very close to the original | Hugging Face → |
| Q5_K_M GGUF · unsloth | 14.3 GB | 19.1 GB | 3.1 GB too big | close; small differences in fine detail | Hugging Face → |
| Q4_K_M GGUF · unsloth | 12.8 GB | 17.6 GB | spills 1.6 GB | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M ← GGUF · unsloth | 10.1 GB | 14.9 GB | fits · 1.1 GB spare | noticeable loss of detail | Hugging Face → |
| Q2_K GGUF · unsloth | 8.1 GB | 12.9 GB | fits · 3.1 GB spare | 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 16 GB the FP8 encoder fits on its own, so prompt encoding stays fast.
04About this GPU
The RTX 4080 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 4080 Super 16 GB: 16 GB GDDR6X · 256-bit · 736 GB/s · Ada Lovelace. Everything that runs on the RTX 4080 Super 16 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 4080 Super 16 GB to the RTX 5090 32 GB →
06Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run LTX-2 on a RTX 4080 Super 16 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 4080 Super 16 GB?
Q3_K_M (10.1 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 4080 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 LTX-2 on the RTX 4080 Super 16 GB?
About 28.8 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, 48 GB of system RAM or more is recommended.