u/Dunc4n1d4h0

Hi,
Sometimes I get this strange color/brightness/contrast change after first few frames, for example starting frames are much have more contrast and brightness. when generating i2v with ltx 2.3. Workflow is nearly as in Comfy template, I just use gguf distilled v1.1 models. Glitch comes in 1st stage, before upscaling.

Is it just unlucky bad seed case or it an be improved?
I tried color match nodes from kj, but every method seems to ad sone kind of banding visible on gradients, so...

Thanks in advance!

Can someone tell me please, how TF should I name my mmproj-BF16.gguf?

I tried every name that came to my mind:
ls:
gemma-3-12b-it-qat-UD-Q5_K_XL.gguf

gemma-3-12b-it-mmproj-BF16.gguf -> mmproj-F16.gguf
gemma-3-12b-it-mmproj-F16.gguf -> mmproj-F16.gguf
gemma-3-12b-it-qat-UD-Q5_K_XL-mmproj-BF16.gguf -> mmproj-BF16.gguf
gemma-3-12b-it-qat-UD-Q5_K_XL-mmproj-F16.gguf -> mmproj-F16.gguf
gemma-3-12b-it-qat-mmproj-BF16.gguf -> mmproj-BF16.gguf
gemma-3-12b-it-qat-mmproj-F16.gguf -> mmproj-F16.gguf
mmproj-BF16.gguf
mmproj-F16.gguf

I even downloaded F16 version.

Still in ComfyUI:
gguf qtypes: F32 (289), Q6_K (87), Q5_K (230), Q4_K (20)
Attempting to recreate sentencepiece tokenizer from GGUF file metadata...
Created tokenizer with vocab size of 262208
Dequantizing token_embd.weight to prevent runtime OOM.
clip missing: ['multi_modal_projector.mm_input_projection_weight', 'multi_modal_projector.mm_soft_emb_norm.weight', 'vision_model.embeddings.patch_embedding.weight', 'vision_model.embeddings.patch_embedding.bias', 'vision_model.embeddings.position_embedding.weight', 'vision_model.encoder.layers.0.layer_norm1.weight', 'vision_model.encoder.layers.0.layer_norm1.bias', 'vision_model.encoder.layers.0.self_attn.q_proj.weight', 'vision_model.encoder.layers.0.self_attn.k_proj.weight', 'vision_model.encoder.layers.0.self_attn.v_proj.weight', 'vision_model.encoder.layers.0.self_attn.out_proj.weight', 'vision_model.encoder.layers.0.layer_norm2.weight', 'vision_model.encoder.layers.0.layer_norm2.bias', 'vision_model.encoder.layers.0.mlp.fc1.weight', 'vision_model.encoder.layers.0.mlp.fc2.weight', 'vision_model.encoder.layers.1.layer_norm1.weight', 'vision_model.encoder.layers.1.layer_norm1.bias', 'vision_model.encoder.layers.1.self_attn.q_proj.weight', 'vision_model.encoder.layers.1.self_attn.k_proj.weight', 'vision_model.encoder.layers.1.self_attn.v_proj.weight',
...