LTX-2 image-to-video had a known failure: when the described motion was not strong enough, the model produced a nearly static clip. This episode tests the Adapter LoRA update, which the author says fixes that and improves consistency, motion coherence and generalisation - and ships two graphs at 60 fps 1080p, one full-quality and one distilled.

Evidence note: parameters below were parsed from the workflow JSON shipped with this episode (2 files); anything the video reports about results is attributed to the author.

When this is useful

  • Your image-to-video clips come out too static when the prompt is modest.
  • You need 60 fps at 1080p from a single reference image.
  • You want a quality-first and a cost-first graph for the same model family.

Two graphs, one adapter

The adapter fixes the static-clip problem

The Adapter LoRA is trained on top of earlier LTX-2 video work. The concrete failure it addresses: when the text is not explicit enough about motion, the base model would simply not move.

The author reports improved character consistency (in his 10-second two-person example), better motion coherence, better style retention and stronger generalisation.

Non-distilled graph: 25 steps, then 2x upscale

The full-quality graph runs 25 steps in the first pass without an accelerator, then a second sampling pass that does a 2x upscale.

The second pass can use an accelerated model - the author always has. Because the accelerated path runs at CFG 1, the negative prompt is inert there, which is why he wires the LTX-2 negative-prompt enhancement node to make negatives count again.

The prompt side has an automation: paste the official system prompt, then write a short description and a language model polishes it into the final prompt.

Distilled graph: 8 steps, merged adapter, uncensored

The distilled graph swaps in the V6.2 merged model, which is uncensored-capable and has the Adapter LoRA merged in - so the LoRA slot stays empty on purpose.

It is designed to produce good results in 8 steps on the first pass. The author's sample deliberately uses large motion to stress it, and says the amplitude is a prompt choice, not a fixed property.

Audio generation is also improved in this build, per the author.

Negative keywords worth stealing

The distilled path uses the LTX-2 negative-prompt node; the three values control how strongly the negative applies.

Concrete use: put subtitle-related words in the negative keywords so the model does not burn Chinese subtitles into the frame - a small trick that solves a recurring annoyance.

How to run it

  1. Open the graph you want: non-distilled for quality, V6.2 distilled for throughput.
  2. Set width, height and length in seconds, then the frame rate - the author runs 60 fps without trouble.
  3. Write positive and negative prompts; for the non-distilled graph the negative prompt is active.
  4. Non-distilled: run the 25-step first pass, then the 2x upscale second pass.
  5. Distilled: run 8 steps; the adapter is merged, so do not add the LoRA again. Use the negative-prompt node and put subtitle words in the negative keywords if the model keeps burning text into frames.

Parameter basis

ltx2_i2v去蒸馏图到视频一致性60帧1080p - 54 nodes

Item Value (from JSON)
UNET loader ltx-2-19b-dev-fp8_transformer_only.safetensors / default
Dual CLIP gemma_3_12B_it_fp8_e4m3fn.safetensors + ltx-2-19b-embeddings_connector_bf16.safetensors
VAE LTX2_video_vae_bf16.safetensors
Latent size 768x512 · 97 frames · batch 1
LoRA ltx-2-19b-distilled-lora_resized_dynamic_fro09_avg_rank_175_bf16.safetensors @ 0.6; LTX-2-Image2Vid-Adapter.safetensors @ 1

ltx2_i2v蒸馏图到视频一致性60帧1080p - 54 nodes

Item Value (from JSON)
UNET loader ltx2-phr00tmerge-nsfw-v62.safetensors / default
Dual CLIP gemma_3_12B_it_fp8_e4m3fn.safetensors + ltx-2-19b-embeddings_connector_bf16.safetensors
VAE LTX2_video_vae_bf16.safetensors
BasicScheduler steps 8 · scheduler simple · denoise 1
Latent size 768x512 · 97 frames · batch 1
LoRA LTX-2-Image2Vid-Adapter.safetensors @ 1

Honest limits

  • Distilled + CFG 1 means the negative prompt is off unless the LTX-2 negative node is wired; that is a graph detail people miss.
  • The distilled build is uncensored-capable, which shifts responsibility to the user.
  • 60 fps at 1080p is what the author ran, not a guaranteed ceiling on smaller cards.
  • Consistency improvement is described qualitatively; no numeric metric is given.
  • The 10-second two-person example is one sample, not a benchmark set.

Episode resources