LTX Video 2.5 Fast
- 🏢 Lightricks' open-weights LTX video family, fast image-to-video tier
- 🧠 LTX-2.5 built as a 22B dual-stream diffusion transformer
- ⚡ Distilled checkpoint runs in a few steps, not twenty
- 🎯 Animates a still image into video with synchronized audio
- 🆕 Replaces LTX-2.3 Fast; LoRAs need retraining for new latents
- 🔧 Available via Diffusers and the official inference package
- 📚 Open weights, permissive terms below a revenue threshold
- 🌐 Pairs with a Pro tier for finished, production-quality renders
Lightricks is a creative technology company founded in January 2013, widely recognized for its popular selfie-editing app Facetune. Originally focused on mobile video and image editing tools, the company has expanded significantly into generative AI, developing its own video…
Explore 6 more models by Lightricks →LTX Video 2.5 Fast is the speed-optimized image-to-video tier of Lightricks' LTX-2.5 generation, released in 2026. You supply a still image plus a prompt, and the model animates it, producing synchronized audio alongside the picture rather than dubbing it afterwards. It sits alongside LTX Video 2.5 Fast for prompt-only generation and LTX Video 2.5 Pro for higher-fidelity finals.
Architecturally, LTX-2.5 is described as a 22-billion-parameter asymmetric dual-stream diffusion transformer paired with a Gemma-based text encoder and separate video and audio autoencoders. The "Fast" designation corresponds to the distilled checkpoint, which Lightricks describes as built for iteration and running in a handful of denoising steps where the full model needs roughly twenty.
Compared with its predecessor LTX Video 2.3 Fast, Lightricks positions 2.5 as the recommended starting point for new projects, particularly where workflows depend on multi-shot continuity, editing existing footage, or fine-tuning to a specific domain. The 2.5 line adds capabilities such as retake for regenerating a single stretch of a clip, dialogue replacement, keyframe interpolation, and in-context LoRA adapters for pose, depth, inpainting, relighting and upscaling. One migration caveat: the latent space changed, so custom LoRAs trained on 2.3 must be retrained.
The weights are published openly with training and inference code, under terms permitting commercial use below a stated revenue threshold.
This About section is AI-generated from public sources via VeniceStats + Venice inference, with no human editing. It may contain inaccuracies.
Daily usage · LTX Video 2.5 Fast · Organic sellers
No seller is currently announcing LTX Video 2.5 Fast on the Antseed network. Last on-chain activity: 24 Oct 2026, 22:21.
Sellers join and leave with normal network churn, so this can be temporary. The page keeps the model's on-chain usage history and lists sellers again the moment one announces it.
"Best price" and the seller table are live Antseed catalog data (advertised $/1M tokens — or $ per generated image for unit-billed image models — not settled amounts). Reputation = buyer trust score (0-100, the Antseed SDK's own formula). "Routing" = the SDK's default buyer routing (what the VPR desktop app ships with): a trust ≥ 60 gate on the effective reputation, then cheapest-first among routable sellers; live failover state (per-peer cooldowns) is buyer-side runtime and not included. Model knowledge (TLDR, provider, About) via the VeniceStats enrichment layer. Advertised catalog, not the model used in any specific purchase. "Usage on Antseed" counts only settlements whose buyers share the per-model split on-chain (metadata v2/v3, opt-in), so every usage figure is a lower bound.