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Home/Open source/LTX-2.5
Open source

LTX-2.5

Lightricks, open-sourced 2026-08 under a community licence (not Apache 2.0 — commercial use needs a separate licence). Weights are free; the cost is all hardware: a discrete GPU with 12GB VRAM is the floor, 24GB is comfortable (full FP16 wants 24GB+; on a 12GB card you need INT8 quantisation plus offload and lose more than half the speed). For serious work look at a 4090 / 5090-class card — more VRAM means less quantisation hacking.

24 GB
VRAM floor
22B+12B
Parameters
1
open-weight models

Open source Highest bar

Weights are free, hardware is not: you buy the GPU up front (one-time estimate, may rise) and still pay for power and time. Six of the twelve are Apache 2.0 (HappyHorse-1.0, SANA-WM, Bernini, MAGI-2, LingBot-Video, LongLive 2.0); LTX-2 and LTX-2.5 use community licences and SANA-Video uses the NVIDIA Open Model License. Hardware runs from one RTX 5090 to 8× H100. See all 12 →

Hardware requirements, as published

VRAM floor
No GB figure in the README — only quantisation flags (fp8-cast / nvfp4)
Official hardware
Any FP8-capable CUDA GPU; fp8-scaled-mm is fastest on Hopper, NVFP4 needs Blackwell (SM≥10)
Output
Default 1024×1536 @ 24fps; 4K is 3840×2176
Size
22B transformer + Gemma 4 12B text encoder, roughly 66 GiB to download
Licence
Community licence (repo ships LICENSE / LICENSE-2_x; confirm commercial terms separately)
In cases of GPU memory constraints, consider --quantization fp8-cast --offload {cpu, disk}.LTX-2 GitHub README + packages/ltx-pipelines/docs/optimization.md
1 records · showing Specs checked 2026-11-10 · hardware 2026-10-21
# Platform / model Layer VRAM · setup One-time hardware
— OSSLTX-2.5 ↗Lightricks · 2026-08 · community licence · 22B + 12B encoder Open source 24 GB12GB only with FP8 + offload ≈ ¥24,000 · one-time1× RTX 4090 24GB · estimate, may rise
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