If you are training a video LoRA in 2026, you are likely choosing between LTX Video 2.3 and LTX-2 — two different models from Lightricks, both available for custom LoRA training via fal.ai. The naming is confusing: LTX-2 sounds like it should be newer than LTX Video 2.3, but the relationship between the models is more nuanced than version number suggests. This guide explains the actual differences and which model to target for your training use case.
What Is LTX Video 2.3?
LTX Video 2.3 (also written LTX-V 2.3) is the current generation of Lightricks' primary video generation model. It uses a diffusion transformer architecture trained on video content with capabilities for text-to-video, image-to-video, video extension, and reference video conditioning. The 2.3 designation refers to a substantial improvement over earlier LTX Video releases — better motion coherence, improved subject consistency, and significantly better handling of complex prompts.
For LoRA training, LTX Video 2.3 is the established choice. The training infrastructure is mature: the fal.ai fal-ai/train-ltxv endpoint handles LTX Video 2.3 LoRA training, and the ecosystem of IC-LoRA variants (identity control, motion tracking, style conditioning) has been built specifically for this model. Community resources, training guides, and prompt engineering knowledge are all developed around LTX Video 2.3.
What Is LTX-2?
LTX-2 is a distinct product line from Lightricks — specifically their audio-video generation model. Where LTX Video 2.3 generates video from text and image inputs, LTX-2 was designed to handle audio-visual synchronization: generating video that is driven by or synchronized with audio input. Think lip sync, music video generation, and audio-reactive motion.
LTX-2 is available on fal.ai via the fal-ai/ltx2-video-trainer endpoint. The model supports LoRA training with a focus on audio-visual content — character animation driven by speech, motion synchronized with music, and similar audio-reactive applications.
The key distinction: LTX Video 2.3 is the text/image-to-video model; LTX-2 is the audio-video model. They are parallel products designed for different primary workflows, not sequential versions where one replaces the other.
Architecture Differences
LTX Video 2.3 runs at resolutions up to 1280x720 and generates clips up to 121 frames (approximately 5 seconds at 24fps). The model accepts text prompts, image references, and conditioning from reference videos. Its training on the fal.ai platform uses a rank-based LoRA approach where rank determines the size and specificity of the learned adaptation — lower rank for style and motion LoRAs, higher rank for character identity LoRAs that need to preserve fine facial and body detail.
LTX-2 is architected around audio conditioning as a primary input modality. The model's internal representation includes audio feature processing that LTX Video 2.3 does not have. For audio-driven video generation — animating a character's face from speech audio, generating motion from a music track — this audio conditioning produces significantly better results than trying to achieve the same with LTX Video 2.3 and text prompts describing desired motion.
LoRA Training: Which Model to Target
Train on LTX Video 2.3 if:
- Your primary use case is text-to-video or image-to-video with custom subjects, styles, or motion patterns
- You need character LoRAs that preserve visual identity across scenes (face, body, clothing)
- Your target workflow uses standard text prompts to drive generation
- You want the broadest compatibility — LTX Video 2.3 LoRAs work across the fal.ai ecosystem and in local ComfyUI setups that support LTXV
- You are using specialized conditioning modes like IC-LoRA for identity consistency or motion-track LoRAs for specific movement patterns
Train on LTX-2 if:
- Your content requires audio-visual synchronization — lip sync, audio-reactive motion, music video generation
- You are building a character LoRA specifically for spoken dialogue animation where the lip sync quality matters
- Your workflow already uses the LTX-2
fal-ai/ltx2-video-trainerendpoint and you want custom adaptations within that model - You are working in an audio-first production pipeline where video is derived from audio rather than the reverse
Practical Recommendation for Most Projects
For the majority of video LoRA training use cases — character LoRAs, style LoRAs, motion LoRAs, product LoRAs — train on LTX Video 2.3. The ecosystem is more mature, the training infrastructure is more developed, and the IC-LoRA variants give you significant control options that LTX-2 training does not yet match.
LTX-2 training makes sense specifically when audio-visual synchronization is a core requirement of your output. If you are building content where dialogue animation or audio-reactive motion is the primary deliverable, LTX-2's audio conditioning produces meaningfully better results for those specific tasks.
The practical answer for most creators: start with LTX Video 2.3. It covers the broader range of use cases, has more community resources, and will work in more playback and generation contexts. Move to LTX-2 training when your specific use case requires audio-visual capabilities that LTX Video 2.3 cannot handle.
Training Both: A Practical Consideration
For studios producing both standard video content and audio-driven content, there is an argument for training parallel LoRAs on both models — a character LoRA on LTX Video 2.3 for standard scene work, and a separate character LoRA on LTX-2 for dialogue-heavy sequences that require accurate lip sync. The models are compatible with this parallel approach, and the training cost is manageable on a credit-based system.
Grix LoRA Trainer at grixai.com/lora supports training on both LTX Video 2.3 (live) and LTX-2 (coming soon), with automatic captioning, recipe-based configuration, and a built-in testing studio. The same interface, the same credit system, the same .safetensors output format — you change the model target, not your entire workflow.
FAQ
Is LTX-2 newer than LTX Video 2.3?
They are parallel products, not sequential versions. LTX Video 2.3 is a text/image-to-video model; LTX-2 is an audio-video model. The "2" in LTX-2 refers to the second generation of Lightricks' audio-video model line, not a generational successor to LTX Video 2.3.
Will LTX Video 2.3 LoRAs work with LTX-2?
No — LoRAs are model-specific. A LoRA trained on LTX Video 2.3 will not work on LTX-2 and vice versa. If you need the same custom subject or style in both models, you need to train separate LoRAs for each.
Which model has better output quality?
They are optimized for different outputs. LTX Video 2.3 produces better text-to-video quality for prompts describing scenes, characters, and motion. LTX-2 produces better audio-synchronized motion quality. Comparing them on the same task type is not meaningful because they are designed for different primary use cases.
What rank should I use for LTX Video 2.3 LoRA training?
For character LoRAs: rank 32-64. For style LoRAs: rank 16-32. For motion LoRAs: rank 8-16. Higher rank captures more detail but requires more training data and credits. A full guide is available at Grix's LTX rank guide.
How do I train a LoRA on LTX Video 2.3 without code?
Use Grix LoRA Trainer — 4-step wizard, automatic captioning, no API calls required. From $5 for a test run.