Model reference · open weights

LTX-2.3

Available as managed deployment Licence fee Video drbaph · community Image→video 1 variants 509 dl/mo

LTX-2.3 is an open-weight video model from drbaph. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.

Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.

What it is

Released bydrbaph
TypeVideo models
TaskImage→video
Runs withdiffusers
Released2026-03-05
Popularity509 downloads / month
LicenceCommercial licence needed

About

What LTX-2.3 is

FP8 quantized versions of the LTX-2.3 22B models by Lightricks.

Read the full model card

Quantized Checkpoints

NameOriginalSize
ltx-2.3-22b-dev-fp8_mixed.safetensorsltx-2.3-22b-dev~30 GB
ltx-2.3-22b-distilled-fp8_mixed.safetensorsltx-2.3-22b-distilled~30 GB

Quantization Details

  • Format: float8_e4m3fn (E4M3, max=448)
  • Method: Static per-tensor W8A8 quantization
  • Scope: Transformer blocks 1–42 (block 0 and last 5 blocks kept in BF16)
  • Targets: All linear projection weight matrices in attn1, attn2, audio_attn1, audio_attn2, audio_to_video_attn, video_to_audio_attn, ff.net, audio_ff.net — specifically to_q, to_k, to_v, to_out.0, ff.net.0.proj, ff.net.2 and their audio equivalents
  • Scale: Per-tensor weight_scale = max(|W|) / 448 stored as F32 scalar alongside each weight. Static input_scale = 1.0 placeholder matching the source model format
  • Non-quantized: Biases, norms, scale_shift_tables, gate_logits kept as BF16/F32
  • Quantized tensors: 1176 / 5947 total (28 patterns × 42 blocks)
  • Output size: ~29.94 GB (down from ~46 GB BF16)

Original Model

This is a quantized derivative of Lightricks/LTX-2.3. All original model details, usage instructions, and license terms apply.

LTX-2.3 is a DiT-based audio-video foundation model designed to generate synchronized video and audio within a single model.

Citation

@article{hacohen2025ltx2,
  title={LTX-2: Efficient Joint Audio-Visual Foundation Model},
  author={HaCohen, Yoav and Brazowski, Benny and Chiprut, Nisan and Bitterman, Yaki and Kvochko, Andrew and Berkowitz, Avishai and Shalem, Daniel and Lifschitz, Daphna and Moshe, Dudu and Porat, Eitan and Richardson, Eitan and Guy Shiran and Itay Chachy and Jonathan Chetboun and Michael Finkelson and Michael Kupchick and Nir Zabari and Nitzan Guetta and Noa Kotler and Ofir Bibi and Ori Gordon and Poriya Panet and Roi Benita and Shahar Armon and Victor Kulikov and Yaron Inger and Yonatan Shiftan and Zeev Melumian and Zeev Farbman},
  journal={arXiv preprint arXiv:2601.03233},
  year={2025}
}

From the published model card. Full card on the HuggingFace links in the sidebar.

How it works

How video models work

Prompt / imagestart pointTemporal diffusionframes over timeVideoMP4 clipA video model generates a sequence of coherent frames from your prompt or a starting image.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys drbaph-ltx-2-3 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (drbaph-ltx-2-3 below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/videos/generations \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"drbaph-ltx-2-3","prompt":"a drone shot over a forest"}'

Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.

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