LTX Video 2.3 Fast
fal-ai/ltx-2.3/text-to-video/fastltx-2-v2-3-fast-text-to-video- 🆕 Newest fast text-to-video model in Lightricks' open-source LTX-2 family.
- ⚡ Speed-optimized tier built for iterative, short-form video workflows.
- 🧠 Diffusion-transformer foundation model generating video with audio.
- 🔊 Native synchronized audio generated alongside the visuals.
- 🔧 Open weights with LoRA fine-tuning and local execution support.
- 💬 Generates video directly from text prompts.
- 🎯 Trades peak fidelity for speed; pairs with a Full Quality sibling.
- 🏢 Released by Lightricks, makers of Facetune and LTX-Video.
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 5 more models by Lightricks →LTX Video 2.3 Fast is the speed-optimized, text-to-video member of Lightricks' LTX-2.3 release, the newest generation of the company's open-source LTX-2 family. Like the rest of the lineup, it is a diffusion-transformer foundation model that produces video with synchronized audio, and it ships with open weights for local execution. The Fast tier is framed for trying ideas quickly — iteration and short-form clips — while the LTX Video 2.3 Full Quality variant targets shots that need maximum detail.
As a same-family update, the 2.3 generation succeeds LTX Video 2.0 Fast within Lightricks' fast text-to-video line. Both are positioned as the rapid-iteration counterpart to the Full Quality checkpoints, generating from text prompts rather than reference images.
The broader LTX-2.3 family supports both text-to-video and image-to-video workflows and is distributed through Lightricks' official LTX repositories, with LoRA fine-tuning available for custom characters, styles, and control. Lightricks, founded in 2013 and known for apps such as Facetune, develops the model as part of its open generative-AI video stack, offering Fast and Full Quality tiers across both text and image conditioning so creators can choose between iteration speed and output fidelity.
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 2.3 Fast · Organic sellers
| Seller | Rep↓ | Sales | Video | Routing | $ / s | $ / video |
|---|---|---|---|---|---|---|
| ▲ Apex Ant 0x73b4…e736 | 81.71 | $0.77 | 26 s | #1 | $0.0296 | — |
| antseed-tidal-falcon-88cd 0x80d1…88cd | 12.78 | $1.24 | 18 s | gated | $0.069 | — |
"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.