Check GPU and free disk space
In PowerShell, confirm your NVIDIA driver sees the GPU. Check that the installation drive has roughly 160 GB free for the app, environment, weights, and outputs.
nvidia-smiInstall LTX Desktop, load gated LTX 2.5 Fast weights, choose local text encoding, render a short clip, and check the saved video on a supported PC or Mac.
Local LTX 2.5 Fast requirements are based on the Lightricks Desktop documentation. Recommended tiers add room for the desktop app, text encoder, and first render.
| Machine | LTX 2.5 Fast · local |
|---|---|
| NVIDIA GPU · under 16 GB | Below publisher minimum; app uses API mode |
| NVIDIA GPU · 16 GB | Publisher minimum; start small |
| NVIDIA GPU · 24–32 GB | Recommended starting range · estimated |
| RTX 5090 · 32 GB | Local mode supported; ample capacity for first render |
| Apple Silicon · 16 GB total | May lack 15 GB free at launch |
| Apple Silicon · 24 GB total | Conditional; check free memory |
| Apple Silicon · 32 GB or more | Recommended starting range · estimated |
| AMD / Intel GPU | Local Desktop mode not documented |
The app requires a compatible runtime and sufficient free system RAM and disk space. This table is not a performance benchmark.
This publisher-supported desktop route uses LTX 2.5 Fast locally. Follow the tab for your operating system, start with a short clip, and confirm the exported file plays.
This setup uses the package documented for this task. Review its source and supported platforms before starting.
Save your machine in My Hardware to get an automatic starting choice. You can always choose any package yourself.
Lightricks documents 16 GB NVIDIA VRAM or 15 GB free Apple Silicon memory at launch. The 24/32 GB recommendation is a YouRunAI headroom estimate, not a publisher benchmark.
Pick your operating system and GPU path. Every command below is for the selected package and runtime.
Windows 10/11, CUDA GPU with at least 16 GB VRAM, 16 GB RAM (32 GB recommended), and about 160 GB free disk space per Lightricks.
In PowerShell, confirm your NVIDIA driver sees the GPU. Check that the installation drive has roughly 160 GB free for the app, environment, weights, and outputs.
nvidia-smiDownload the current Windows installer from the project’s Releases page, install it, and launch the app.
Official Windows installerIn the app’s first-run setup, sign in to Hugging Face and review the LTX 2.5 license if prompted. The local Fast weights are gated; this step requires internet before offline use.
LTX 2.5 weights and licenseOpen Settings → Models and select LTX 2.5 Fast as the active local checkpoint. Check that the app says Local generation. Pro is an API-only option and is not the model used in this guide.
In Settings, select the Local Text Encoder if you want prompts to stay on your machine. It downloads additional weights and uses more memory. The optional API encoder is a separate cloud step.
Open Text to Video, enter a simple scene such as “A red kite over a quiet beach at sunrise,” choose a short duration and modest resolution, then start generation. Wait for the local progress indicator and avoid raising quality settings until the first clip succeeds.
Play the completed clip, confirm it shows the requested subject and motion, and export it to a local file. This first run verifies the complete model, text encoder, decoder, and output path.
The app shows Local generation, completes a short text-to-video render, and exports a file that plays through on your machine. Check the content against your prompt.
This guide covers the local Fast checkpoint only. LTX 2.5 Pro and the optional API text encoder use cloud services.
Confirm the NVIDIA driver is working, the GPU shows at least 16 GB VRAM in nvidia-smi, and restart LTX Desktop. The hardware mode is selected at launch.
LTX checks free memory at launch. Close large apps, fully quit LTX Desktop, and reopen it. It needs 15 GB free, not merely installed.
Sign in to Hugging Face and accept the LTX 2.5 model terms on the linked weights page, then retry the in-app download.
Original instructions, model files, and compatibility notes behind this setup.
Save your machine to see a personalized rating and its reasoning.
Add my hardwareInstall a local runtime, run Qwen3.5 9B, confirm responses, and know when to choose the smaller 4B package.
Connect an open coding-capable model in Ollama to Cline, run a small repository task, and review the result locally.
Use the official FLUX.2 Klein 4B ComfyUI template with exact model files, a first prompt, and an output check.