Can the RTX 4060 Laptop 8 GB run LTX-2.5 (22B)?
The smallest sensible file, Q4_K_M (15.1 GB), needs about 19.9 GB — 11.9 GB more than RTX 4060 Laptop 8 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-2.5-Distilled-Q4_K_M.gguf Q4_K_M · realrebelai/LTX-2.5_GGUFs | models/unet | 15.1 GB | Download → |
| Text encoder | gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors Gemma 4 12B + LTX projection INT8 (convrot) · Lightricks/LTX-2.5 | models/text_encoders | 15.4 GB | Download → |
| VAE | ltx-2.5-video-vae-bf16.safetensors LTX-2.5 video VAE (DiffVAE) BF16 · Lightricks/LTX-2.5 | models/vae | 1.5 GB | Download → |
| Also needed | ltx-2.5-audio-vae-bf16.safetensors LTX-2.5 audio VAE + vocoder BF16 · Lightricks/LTX-2.5 | models/vae | 0.4 GB | Download → |
| Total download · keep about the same free on disk | 32.3 GB | |||
Alternatives: Gemma 4 12B + LTX projection BF16 (26.3 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. Only for some workflows: LTX-2.5 latent spatial upscaler x2 (1.0 GB, official two-stage template); Gemma 4 E2B INT8 (prompt enhancer, optional) (5.2 GB, only if prompt enhancer enabled). 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 32.3 GB, plus roughly 6 GB for Windows, ComfyUI and a browser: 38.3 GB in total. With less RAM it still runs, but Windows starts swapping to disk and loading gets very slow. calculated
02Every LTX-2.5 file on 8 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit SAFETENSORS · Lightricks | 42.0 GB | 46.8 GB | 38.8 GB too big | the original weights | Hugging Face → |
| Q8_0 GGUF · realrebelai | 23.6 GB | 28.4 GB | 20.4 GB too big | practically identical to the original | Hugging Face → |
| Q6_K GGUF · realrebelai | 18.7 GB | 23.5 GB | 15.5 GB too big | very close to the original | Hugging Face → |
| Q5_K_M GGUF · realrebelai | 16.8 GB | 21.6 GB | 13.6 GB too big | close; small differences in fine detail | Hugging Face → |
| Q4_K_M ← GGUF · realrebelai | 15.1 GB | 19.9 GB | 11.9 GB too big | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M GGUF · realrebelai | 11.5 GB | 16.3 GB | 8.3 GB too big | noticeable loss of detail | Hugging Face → |
| Q2_K GGUF · realrebelai | 8.8 GB | 13.6 GB | 5.6 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 4 12B (custom LTX-2.5 build): 26.3 GB as 16-bit, 15.4 GB as INT8. 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 encoder itself is too big for VRAM, so let it run from system RAM: slower prompt encoding, same images.
04About this GPU
The RTX 4060 Laptop 8 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 (35–115 W depending on the laptop). The memory verdicts are the same; speed depends heavily on how much power the laptop maker allows.
RTX 4060 Laptop 8 GB: 8 GB GDDR6 · 128-bit · Ada Lovelace · 35–115 W. Everything that runs on the RTX 4060 Laptop 8 GB →
05What more VRAM would change
With 32 GB you could run LTX-2.5 at 8-bit or better (Q8_0, 23.6 GB) with no offloading: for example on the RTX 5090 32 GB.
What changes from the RTX 4060 Laptop 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 LTX-2.5 on a RTX 4060 Laptop 8 GB, send your time per image and peak VRAM and it will appear here, credited.
07Questions
How much VRAM does LTX-2.5 need?
Around 13.6 GB with the smallest file (Q2_K) and 28.4 GB with an 8-bit file (Q8_0), counting working memory and a small system reserve. The full 16-bit file needs about 46.8 GB.
Which LTX-2.5 file should I download for the RTX 4060 Laptop 8 GB?
Q4_K_M (15.1 GB) from realrebelai/LTX-2.5_GGUFs. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.
Is FP8 faster than GGUF on the RTX 4060 Laptop 8 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-2.5 on the RTX 4060 Laptop 8 GB?
About 32.3 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, 48 GB of system RAM or more is recommended.