LTX-2
LightricksOthertextvideo

LTX-2

Updated Nov 13, 2026
Parameters
18.9B
Context
8,192
License
Other
Updated
Nov 13, 2026

Will it run on your hardware?

Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest

Runs on your 24 GB - best at Q8_0
3 of 4 quantizations fit LTX-2 with real runtime overhead.
Q4_K_M
11 GB
Q5_K_M
13 GB
Q8_0
20 GB
FP16
38 GB
fits tight too big

Need an exact figure for your context length? Use the VRAM calculator.

Run it locally

Copy-paste - running in under a minute

vLLMOpenAI-compatible API
vllm serve Lightricks/LTX-2

New to this? Start with Ollama · serve to many users with vLLM.

Deep dive

Notes, sources, and the full write-up

LTX-2 is an open-weight video generation model from Lightricks, published on Hugging Face in January 2026. It has 18.9B parameters and is released under a custom license (see the model card).

HardwareLink to this section

At full FP16 precision the weights need about 38 GB of memory; 8-bit quantization brings that to roughly 20 GB. Check the VRAM tiers above to see which GPUs fit it.

PopularityLink to this section

LTX-2 had 296,421 downloads on Hugging Face in the last month and has 1,814 likes.

Run it locallyLink to this section

The weights are on Hugging Face and load with Hugging Face Diffusers (or ComfyUI). Follow the model card for the exact setup and license terms.

Frequently asked

Quick answers to common questions

How much VRAM does LTX-2 need?

LTX-2 with 18.9B parameters needs approximately 11 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.

Is LTX-2 better than other Lightricks models?

LTX-2 has 18.9B parameters with 8,192 context - a strong choice for video-generation, image-to-video.

What license is LTX-2 under?

LTX-2 is released under the Other license, making it suitable for most commercial and personal projects.

What hardware runs LTX-2 well?

With 18.9B parameters, LTX-2 requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.

What is the best quantization for LTX-2?

Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~13 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.

What models compete with LTX-2?

LTX-2 competes with other models in its class. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.

Nearby options

Similar models and compatible hardware by spec