LTX-Video 2B on NVIDIA RTX 5000 Ada Generation Laptop GPU

Can the NVIDIA RTX 5000 Ada Generation Laptop GPU run LTX-Video 2B?

77 pts

Yes, it runs well

Runs well. At FP8 it needs about 10.8 GB of 16.0 GB usable, with an estimated speed of 37 s.

Best precision: FP8
Memory mode: Everything on GPU
Time per clip: 37 s
Output: 768×512, 121 frames, 30 steps

Download LTX-Video 2B

Quantized files · GGUF for ComfyUI

Smaller GGUF versions for ComfyUI (with the ComfyUI-GGUF node). No sign-in needed; the model’s license still applies.

huggingface.co/city96/LTX-Video-gguf (opens in a new tab)

Original weights · Hugging Face

Full-precision files from Lightricks, for fine-tuning, vLLM, Transformers, Diffusers or ComfyUI.

huggingface.co/Lightricks/LTX-Video (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from Lightricks. The weights themselves download from Hugging Face.

github.com/Lightricks/LTX-Video (opens in a new tab)

git clone https://github.com/Lightricks/LTX-Video

Links checked 6 days ago against Hugging Face, Ollama and GitHub.

How the A grade is scored

Every result gets up to 100 points from four parts. The points decide the letter grade.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.	22.1 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.	25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	15.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	15.0 / 15
Total	77.1 / 100	77 ptsGreat (A) · 77 of 100 points: Model quality 22.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every precision on the NVIDIA RTX 5000 Ada Generation Laptop GPU

Precision	Memory needed	Available	Time per output	Memory mode	Fit	Grade · points	Download
`FP16`	8.0 GB	16.0 GB	43 s	Text encoder offloaded	Runs well	68 ptsGood (B) · 68 of 100 points: Model quality 22.5/45, Memory fit 20.0/25, Speed 15.0/15, Memory use 11.5/15	Original weights (opens in a new tab)
`FP8`	10.8 GB	16.0 GB	37 s	Everything on GPU	Runs well	77 ptsGreat (A) · 77 of 100 points: Model quality 22.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15	Original weights (opens in a new tab)

Other hardware that runs it

77 ptsGreat (A) · 77 of 100 points: Model quality 22.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 AMD Radeon RX 7900 XTX FP16 · 28 s
77 ptsGreat (A) · 77 of 100 points: Model quality 22.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 3090 FP16 · 47 s
77 ptsGreat (A) · 77 of 100 points: Model quality 22.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4090 FP16 · 25 s
77 ptsGreat (A) · 77 of 100 points: Model quality 22.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 AMD Radeon RX 9070 XT FP8 · 30 s
77 ptsGreat (A) · 77 of 100 points: Model quality 22.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4060 Ti 16GB FP8 · 60 s
77 ptsGreat (A) · 77 of 100 points: Model quality 22.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4070 Ti SUPER FP8 · 36 s

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.