Can the RTX 4090 Laptop 16 GB run LTX-2.3 (22B)?
Not at full quality. The 16-bit and 8-bit files are too big for the RTX 4090 Laptop 16 GB; the largest that fits is Q3_K_M (10.8 GB).
Q3_K_M (10.8 GB) fits with only 0.4 GB to spare (about 15.6 GB of 16 GB). Quality: noticeable loss of detail.
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | ltx-2.3-22b-dev-Q3_K_M.gguf Q3_K_M · unsloth/LTX-2.3-GGUF | models/unet | 10.8 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-2.3-22b-dev_video_vae.safetensors LTX-2.3 video VAE · unsloth/LTX-2.3-GGUF | models/vae | 1.5 GB | Download → |
| Also needed | ltx-2.3-22b-dev_audio_vae.safetensors LTX-2.3 audio VAE · unsloth/LTX-2.3-GGUF | models/vae | 0.4 GB | Download → |
| Also needed | ltx-2.3-22b-dev_embeddings_connectors.safetensors LTX-2.3 text embeddings connectors (projection) · unsloth/LTX-2.3-GGUF | models/text_encoders | 2.3 GB | Download → |
| Total download · keep about the same free on disk | 28.1 GB | |||
Alternatives: Gemma 3 12B FP4 mixed (9.4 GB); Gemma 3 12B BF16 (24.4 GB). FP4 files are listed only as alternatives unless the GPU is an RTX 50 (Blackwell). Only for some workflows: LTX-2.3 spatial upscaler x2 1.1 (1.0 GB, official two-stage template). Sizes from Hugging Face, 2026-10-01.
System RAM: 48 GB or more. These files take about 28.1 GB of RAM while loaded, 34.1 GB with Windows and ComfyUI. What happens with less. calculated
02Every LTX-2.3 file on 16 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit GGUF · unsloth | 42.0 GB | 46.8 GB | 30.8 GB too big | the original weights | Hugging Face → |
| Q8_0 GGUF · unsloth | 22.8 GB | 27.6 GB | 11.6 GB too big | practically identical to the original | Hugging Face → |
| Q6_K GGUF · unsloth | 17.8 GB | 22.6 GB | 6.6 GB too big | very close to the original | Hugging Face → |
| Q5_K_M GGUF · unsloth | 16.1 GB | 20.9 GB | 4.9 GB too big | close; small differences in fine detail | Hugging Face → |
| Q4_K_M GGUF · unsloth | 14.3 GB | 19.1 GB | 3.1 GB too big | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M ← GGUF · unsloth | 10.8 GB | 15.6 GB | fits · 0.4 GB spare | noticeable loss of detail | Hugging Face → |
| Q2_K GGUF · unsloth | 8.3 GB | 13.1 GB | fits · 2.9 GB spare | heavy loss; a last resort | Hugging Face → |
“Needed” adds 4 GB of working memory for LTX-2.3 and a 0.8 GB reserve. Sizes 2026-10-01.
03Measured and reported results
Nobody has sent measured numbers for this pair yet. If you run LTX-2.3 on a RTX 4090 Laptop 16 GB, send your time per image and peak VRAM and it will appear here, credited.
04With more VRAM
With 32 GB you could run LTX-2.3 at 8-bit or better (Q8_0, 22.8 GB) with no offloading: for example on the RTX 5090 32 GB.
05About the RTX 4090 Laptop 16 GB
The RTX 4090 Laptop 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.) As a laptop GPU it runs at a lower power limit than desktop cards (80–150 W depending on the laptop). The memory verdicts are the same; speed depends heavily on how much power the laptop maker allows.
16 GB GDDR6 · 256-bit · Ada Lovelace · 80–150 W. Everything that runs on it →
06Questions
How much VRAM does LTX-2.3 need?
Around 13.1 GB with the smallest file (Q2_K) and 27.6 GB with an 8-bit file (Q8_0). The full 16-bit file needs about 46.8 GB.
Which LTX-2.3 file should I download for the RTX 4090 Laptop 16 GB?
Q3_K_M (10.8 GB) from unsloth/LTX-2.3-GGUF. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.
How much do I need to download for LTX-2.3 on the RTX 4090 Laptop 16 GB?
28.1 GB: ltx-2.3-22b-dev-Q3_K_M.gguf, gemma_3_12B_it_fp8_scaled.safetensors, ltx-2.3-22b-dev_video_vae.safetensors, ltx-2.3-22b-dev_audio_vae.safetensors, ltx-2.3-22b-dev_embeddings_connectors.safetensors.