PlagueKind - Minimax H3 - LTX Workflow - Ease of use - Eros | Sulphur Compatible | FaceID<h1 id="disclaimer-read-this">DISCLAIMER READ THIS</h1>Update my nodepack BEFORE downloading and opening any workflow I release. I won't be responding to comments about the node errors like that anymore.## H3 Minimax### V9 Notes- UPDATE NODEPACK TO V1.4.7 AND COMFYUI TO NEWEST VERSION.- New mode for sparse, comfy engine, better quality and faster.- Added Int8 Kernel.- I set 0.7 sparsity because it's not much slower on comfy engine, mess with it.- Added H3 cache, default is safe.- Added Bypass for R2V VAE.- Upscaling is still WIP, mess with it.### V8 Notes- Update nodepack to v1.4.3 first- Added my turbo lora, functional strength up to 5.0- Test default settings, they should be good for most prompts.- If you don't like mine on it's own, try blending the disabled fast lora with it, looks really good.- Res multi step simple also works well.- Added tiled upscaling, thanks to lora daddy.## V7 Notes- Update to nodepack V1.4.2 BEFORE OPENING the workflow.- SLA has reference protection now, speeds up R2V signficantly, also fixed slowdown from max ref size. Turning it off gives a speed boost for barely any loss.- Added blocksize 32 to improve quality. if you want the old slightly faster behavior enter subgraph, set blocksize 64.- 768 Dareties turbo added combined with the old Dareties for 6 steps.- Use Seeds_2 + Sgm_Uniform for best quality. (slower, but 4 steps looks great). Old dareties 1str, or 768 at 0.75str- If using single audio sources like one voice, use shift 3 audio for cleaner voice. if there is music underneath and sound effects, try audio shift 5## V6 Notes- SLA node overhaul, vast improvement of control and quality.- Added ER_SDE ODE override.Sparse Density Notes:0.80-0.85 - "match pytorch quality"0.9 - Default - Minimal Degredation 15-20% faster than 0.850.95 - HUGE boost for longer hi res generations, can introduce minor degredation## V5.6 Notes- Unified resize now has Aspect ratio selector- Changed default sampler to sa_solver - I needed to make this because changing unified resize breaks old workflows. update nodepack before loading the workflow## V5.5 Notes- Major'ish Overhaul of the layout, and wiring.- Disabling Sparse falls back to comfy attention.## V5 Notes- I've added my Sparse attention node. No other speedups required. up to 2.5x speedup.- Switched to dareties lora. Use with shift 8/3 0.8 strength 6-8 steps. this lora works great for all modes.- Memory Chunking if you go to high with sparse, it causes slow down. for me beyond 2-4 caused slowdown on 16gb vram.- Don't mess with the sparse settings on the subgraph unless you have to.- Make sure to update my node pack to atleast 1.3.1- Make sure you're on the newest pytorch+cu combo supported.<hr />### SupportIf you find this project useful and want to support development:Monero (XMR):<pre><code>865BrcfWLdwELwuq5faV1uVTbh93zVK6AUYLY2c3mX6sFfAGRfS6axe1kBTYYKuM7ccN7zBZDAZvnT7E4NKmUazySdbpc7p</code></pre>## V4 Notes- Sage begone, welcome comfy attn. update comfyui, sage without sage issues.- Switched to 4 step 768 lora. Use with shift 6/3 0.8 strength 6-8 steps, or 1.0 with 4-6 steps.- Added hybrid model so you don't need to swap anymore, start with 25. 30 higher quality slightly less ref strength.- When ref swapping a video use er_sde/beta- Added original audio mode, avoids degradation and vae decode / Allows you to make music videos etc. it's in the reference subgraph.- Added minimax mode and mode selection to lora stack, so update node pack.## V3.1 Notes- Sage begone, welcome comfy attn. update comfyui, sage without sage issues.- Switched to 8 step new lora, these 2 new things combined behave very close to non turbo non sage.## V3 Notes- Added R2V mode.## V2.1 Notes- Added preview node.## V2 Notes- Added int8 convrot video vae- Kijai resized turbo lora, best at 0.6-0.7 strength.- Memory chunks return. huge speed up for me. 4 was pretty much the cap for 16gb vram.---### Requirements- [ComfyUI-PlagueKind-Nodes](<a target="_blank" rel="ugc" href="https://github.com/PlagueKind/Comfyui-PlagueKind-Nodes">https://github.com/PlagueKind/Comfyui-PlagueKind-Nodes</a>)- [ComfyUI-KJNodes](<a target="_blank" rel="ugc" href="https://github.com/kijai/ComfyUI-KJNodes">https://github.com/kijai/ComfyUI-KJNodes</a>)- [Rgthree-comfy](<a target="_blank" rel="ugc" href="https://github.com/rgthree/rgthree-comfy">https://github.com/rgthree/rgthree-comfy</a>)- [Nvidia_RTX_Nodes_ComfyUI](<a target="_blank" rel="ugc" href="https://github.com/Comfy-Org/Nvidia_RTX_Nodes_ComfyUI">https://github.com/Comfy-Org/Nvidia_RTX_Nodes_ComfyUI</a>)- [ComfyUI-VideoHelperSuite](<a target="_blank" rel="ugc" href="https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite">https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite</a>)- [ComfyUI-H3-Motion-Context-MultiRef](<a target="_blank" rel="ugc" href="https://github.com/seitanism/ComfyUI-H3-Motion-Context-MultiRef">https://github.com/seitanism/ComfyUI-H3-Motion-Context-MultiRef</a>)- [ComfyUI_PowerShiftScheduler](<a target="_blank" rel="ugc" href="https://github.com/silveroxides/ComfyUI_PowerShiftScheduler">https://github.com/silveroxides/ComfyUI_PowerShiftScheduler</a>)---### Diffusion Model[minimax_h3_hybrid_fl2va_ref2va_b25-49-int8.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/smhfacct/Minimax-H3-fl2va-ref2va-hybrid-models/resolve/main/minimax_h3_hybrid_fl2va_ref2va_b25-49-int8.safetensors">https://huggingface.co/smhfacct/Minimax-H3-fl2va-ref2va-hybrid-models/resolve/main/minimax_h3_hybrid_fl2va_ref2va_b25-49-int8.safetensors</a>)[minimax_h3_hybrid_fl2va_ref2va_b30-49-int8.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/smhfacct/Minimax-H3-fl2va-ref2va-hybrid-models/resolve/main/minimax_h3_hybrid_fl2va_ref2va_b30-49-int8.safetensors">https://huggingface.co/smhfacct/Minimax-H3-fl2va-ref2va-hybrid-models/resolve/main/minimax_h3_hybrid_fl2va_ref2va_b30-49-int8.safetensors</a>)### VAE[minimax_h3_audio_vae_fp32.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/Comfy-Org/MiniMax-H3/resolve/main/vae/minimax_h3_audio_vae_fp32.safetensors">https://huggingface.co/Comfy-Org/MiniMax-H3/resolve/main/vae/minimax_h3_audio_vae_fp32.safetensors</a>)[minimax_h3_video_vae_int8_convrot.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/Kijai/MiniMax-H3-experimental/resolve/main/minimax_h3_video_vae_int8_convrot.safetensors">https://huggingface.co/Kijai/MiniMax-H3-experimental/resolve/main/minimax_h3_video_vae_int8_convrot.safetensors</a>)[vae_approx/taeh3.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/Kijai/MiniMax-H3-TAE/resolve/main/vae_approx/taeh3.safetensors">https://huggingface.co/Kijai/MiniMax-H3-TAE/resolve/main/vae_approx/taeh3.safetensors</a>)### Text Encoder[qwen3vl_32b_minimax_h3_int8_convrot.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/Comfy-Org/MiniMax-H3/resolve/main/text_encoders/qwen3vl_32b_minimax_h3_int8_convrot.safetensors">https://huggingface.co/Comfy-Org/MiniMax-H3/resolve/main/text_encoders/qwen3vl_32b_minimax_h3_int8_convrot.safetensors</a>)### Frame Interpolation[film_net_fp16.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/Comfy-Org/frame_interpolation/resolve/main/frame_interpolation/film_net_fp16.safetensors">https://huggingface.co/Comfy-Org/frame_interpolation/resolve/main/frame_interpolation/film_net_fp16.safetensors</a>)### Latent Upscaler[minimax_h3_latent_upscaler_3d_bf16.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/LBH-123-AI/Minimax_h3_latent_Upscaler/resolve/main/minimax_h3_latent_upscaler_3d_bf16.safetensors">https://huggingface.co/LBH-123-AI/Minimax_h3_latent_Upscaler/resolve/main/minimax_h3_latent_upscaler_3d_bf16.safetensors</a>)### Turbo Loras[H3-PK-Parasyte-Turbo.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/Plaguekind/H3-Lora/resolve/main/H3-PK-Parasyte-Turbo.safetensors">https://huggingface.co/Plaguekind/H3-Lora/resolve/main/H3-PK-Parasyte-Turbo.safetensors</a>)[fasth3_6step.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/Plaguekind/H3-Lora/resolve/main/otherturbo/fasth3_6step.safetensors">https://huggingface.co/Plaguekind/H3-Lora/resolve/main/otherturbo/fasth3_6step.safetensors</a>)supporting file required. make the folder models/h3_adaln[h3_silu_temb_grid.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/deAPI-ai/minimax-h3-33b-int8/resolve/main/loras/h3_silu_temb_grid.safetensors">https://huggingface.co/deAPI-ai/minimax-h3-33b-int8/resolve/main/loras/h3_silu_temb_grid.safetensors</a>)---## V1.5 Notes- Added the option for T2V.- When using T2V, set scale mode of Target Dimension node to Dimensions (WxH) or you will get a square video.- Added FSR RCAS sharpening, 0.3 strength looks natural.- FFLF is unreliable at res above 640, don't know why, it's like this on default WF as well.- Target Dimension node controls the generation size only, refs are passed elsewhere.- Don't touch the other hidden resize nodes as they only control ref size and are set to max.- Euler + Linear Quadratic seems to be the best combo with between 15-20 steps.- I didn't add easy cache because it ruins the quality noticeably,- If you have time or a powerful card, try heunpp2 sampler. It's phenomenal.## LTX 2.3## V8 Notes- Updated everything to LTX 2.5.- Lora stack still seems to work.## V7 Notes- Added FaceID tracking.- Changed DMD Lora for smoother output.- Steps required 4-10. 6 seems good enough.- Pruna Video VAE for speed boost.- Int8 Convrot TE.- Any FPS choice seems to work.- Increase IMG Preprocess for extra movement.- ComfyUI broke subgraphs so I adapted.- Make sure you're on atleast 10s-nodes 1.9.6### SupportIf you find this project useful and want to support development:Monero (XMR):`865BrcfWLdwELwuq5faV1uVTbh93zVK6AUYLY2c3mX6sFfAGRfS6axe1kBTYYKuM7ccN7zBZDAZvnT7E4NKmUazySdbpc7p`Thank you for your support.## V6 Notes- Updated Eros to 1.4 much better.- You can disable all optional lora apart from distill and eros if you want. The others do enhance the output though.- Added Volume Boost option.- Using DMD for audio and video.- Use 0.715, 0.2412, 0.0 2x FPS sigma if you see jitter## V5 Notes- Using decoupled distillation for video and audio, and smaller loras. - REQUIRED.- Updated to Eros 1.3- FPS bumped to 30fps default.- 60fps native with 120fps via 2x now compatible.- Added an actually useable NVFP4 model, even though int8 convrot is more or less the same size and speed.- You can regain speed by disabling one of the optional loras, start with sulphur.## V4 Notes- New reference node injects reference directly into the model, mostly eliminating any drift.- New DMD distill lora, fixes issues of original distill which broke decompression method and prompt adherence, no need to write a paragraph anymore. Preprocess returns for enhanced movement.- Use 6-13 steps, default 8-9.- INT8 Triton VAE for fast decode.- INT8 Convrot added for increased speed on all cards.- JoyAI lora another lora similar to omninft, this helps adherence, dialog, interaction and more.- If using the nvfp4 transformer make sure to describe anatomy that isn't already visible in the image. I don't recommend using the nvfp4 text encoder for realism.---## V3 NotesTURN DOWN NEW EROS LORA TO 0.7 I SET IT AT 0.9 and it doesn't look correct like that.- Added Prompt Relay Node for advanced timeline prompting while keeping simplicity.- Added VHS save video. AV1/WEBM CRF0 produces virtually lossless video with extremely small file size.- Updated Eros Lora.- Moved RTX VSR into sampler graph.## V2 Notes- Upscale and 2x fps have added tiled sampler to improve speed. if you don't like the output, experiment with cfg pp sampler, or add 0.715 to sigma. Current sigma are done on purpose to retain identity and quality of first pass.## V1 Notes- Focused Mainly on Speed and ease of usability while retaining single pass quality and likeness.- First pass is more or less optimized.- Identity Retention is pretty good.- First pass balanced for speed and quality.- Upscale and 2x fps work but will be optimized later.- I would avoid using RTX VSR with the whole chain active unless you have like 96gb ram.- Nvfp4 models are only for Blackwell, using them will not save you speed if you don't have Blackwell, but they should still work.- Default settings of the first pass should produce good quality and sharp. I personally like to use this for a single pass and just render straight at 1280.- Bumped FPS to 30 because it looks way bettwen imo, quality seems clearer overall and it gets rid of that ltx base fps look.---## Memory Chunk Note- This saves vram and speeds up it/s especially on longer videos- With 16gb of VRAM 3 chunks seems optimal for me- If you get triton errors, enter the model loader subgraph and disable use triton kernels---## Requirements- [ComfyUI-PlagueKind-Nodes](<a target="_blank" rel="ugc" href="https://github.com/PlagueKind/Comfyui-PlagueKind-Nodes">https://github.com/PlagueKind/Comfyui-PlagueKind-Nodes</a>)- [ComfyUI-KJNodes](<a target="_blank" rel="ugc" href="https://github.com/kijai/ComfyUI-KJNodes">https://github.com/kijai/ComfyUI-KJNodes</a>)- [Rgthree-comfy](<a target="_blank" rel="ugc" href="https://github.com/rgthree/rgthree-comfy">https://github.com/rgthree/rgthree-comfy</a>)- [10s-nodes](<a target="_blank" rel="ugc" href="https://github.com/TenStrip/10S-Comfy-nodes">https://github.com/TenStrip/10S-Comfy-nodes</a>)- [Nvidia_RTX_Nodes_ComfyUI](<a target="_blank" rel="ugc" href="https://github.com/Comfy-Org/Nvidia_RTX_Nodes_ComfyUI">https://github.com/Comfy-Org/Nvidia_RTX_Nodes_ComfyUI</a>)---### Model Choices[ltx-2.5-22b-distilled-transformer-comfy-int8-convrot.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/Lightricks/LTX-2.5/resolve/main/diffusion_models/ltx-2.5-22b-distilled-transformer-comfy-int8-convrot.safetensors">https://huggingface.co/Lightricks/LTX-2.5/resolve/main/diffusion_models/ltx-2.5-22b-distilled-transformer-comfy-int8-convrot.safetensors</a>)### Latent Upscalers[ltx-2.5-latent-spatial-upscaler-x2-bf16-1.0.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/Lightricks/LTX-2.5/resolve/main/latent_upscale_models/ltx-2.5-latent-spatial-upscaler-x2-bf16-1.0.safetensors">https://huggingface.co/Lightricks/LTX-2.5/resolve/main/latent_upscale_models/ltx-2.5-latent-spatial-upscaler-x2-bf16-1.0.safetensors</a>)[ltx-2.5-latent-temporal-upscaler-x2-bf16-1.0.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/Lightricks/LTX-2.5/resolve/main/latent_upscale_models/ltx-2.5-latent-temporal-upscaler-x2-bf16-1.0.safetensors">https://huggingface.co/Lightricks/LTX-2.5/resolve/main/latent_upscale_models/ltx-2.5-latent-temporal-upscaler-x2-bf16-1.0.safetensors</a>)### VAE[ltx-2.5-audio-vae-bf16.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/Lightricks/LTX-2.5/resolve/main/vae/ltx-2.5-audio-vae-bf16.safetensors">https://huggingface.co/Lightricks/LTX-2.5/resolve/main/vae/ltx-2.5-audio-vae-bf16.safetensors</a>)[ltx-2.5-video-vae-conv-bf16.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/Lightricks/LTX-2.5/resolve/main/vae/ltx-2.5-video-vae-conv-bf16.safetensors">https://huggingface.co/Lightricks/LTX-2.5/resolve/main/vae/ltx-2.5-video-vae-conv-bf16.safetensors</a>)### Text Encoder[gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/Lightricks/LTX-2.5/resolve/main/text_encoders/gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors">https://huggingface.co/Lightricks/LTX-2.5/resolve/main/text_encoders/gemma4-12b-with-proj-ltx-2.5-comfy-int8-convrot.safetensors</a>)### FaceID LoRA[Best_FaceID_v1.0_LoRA.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/Alissonerdx/LTX-Best-Face-ID/resolve/main/Best_FaceID_v1.0_LoRA.safetensors">https://huggingface.co/Alissonerdx/LTX-Best-Face-ID/resolve/main/Best_FaceID_v1.0_LoRA.safetensors</a>)### Optional LoRA[LTX-2.3-OmniNFT-RL-Lora_bf16.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/Kijai/LTX2.3_comfy/resolve/main/loras/LTX-2.3-OmniNFT-RL-Lora_bf16.safetensors?download=true">https://huggingface.co/Kijai/LTX2.3_comfy/resolve/main/loras/LTX-2.3-OmniNFT-RL-Lora_bf16.safetensors?download=true</a>)[LTX_SulphurEXP_LoRA_fro99-avgrank105.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/maximsobolev275/LTX-SulphurExperimental-LoRA-Optimized/resolve/main/LTX_SulphurEXP_LoRA_fro99-avgrank105.safetensors">https://huggingface.co/maximsobolev275/LTX-SulphurExperimental-LoRA-Optimized/resolve/main/LTX_SulphurEXP_LoRA_fro99-avgrank105.safetensors</a>)[JoyAI-Echo-content_r256.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/TenStrip/LTX2.3_JoyAI_Lora_Extracted/resolve/main/JoyAI-Echo-content_r256.safetensors">https://huggingface.co/TenStrip/LTX2.3_JoyAI_Lora_Extracted/resolve/main/JoyAI-Echo-content_r256.safetensors</a>)[LTX_10Eros-v15_LoRA_fro99-avgrank103.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/maximsobolev275/LTX-10Eros-LoRA-r768/resolve/main/LTX_10Eros-v15_LoRA_fro99-avgrank103.safetensors">https://huggingface.co/maximsobolev275/LTX-10Eros-LoRA-r768/resolve/main/LTX_10Eros-v15_LoRA_fro99-avgrank103.safetensors</a>)### Optional Model converted by me[10Eros_v1_experimental_nvfp4.safetensors](<a target="_blank" rel="ugc" href="https://huggingface.co/Plaguekind/10Eros_v1_experimental_nvfp4/resolve/main/10Eros_v1_experimental_nvfp4.safetensors?download=true">https://huggingface.co/Plaguekind/10Eros_v1_experimental_nvfp4/resolve/main/10Eros_v1_experimental_nvfp4.safetensors?download=true</a>)

PlagueKind - Minimax H3 Sparse  Attention - LTX Workflow  - Eros | Sulphur Compatible | FaceID

## V1 Notes- FFLF is unreliable at res above 640, don't know why, it's like this on default WF as well.- First frame resize node controls the generation size. - Don't touch the other resize nodes as they only control ref size and are set to max.- Euler + Linear Quadratic seems to be the best combo with between 15-20 steps.- I didn't add easy cache because it ruins the quality noticeably,

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