DaSiWa MiniMax H3 Workflows v1.4
This is a customized version of the original DaSiWa MiniMax H3 workflow.
It preserves the original T2VA, I2VA, FL2VA, and REF2VA modes while adding quality-of-life tools for attention selection, clip continuation, seed management, automatic aspect-ratio handling, color matching, previews, and optional latent refinement.
What is new in v1.4
New unified Attention selector in the Settings panel.
Improved NativeAddGuide and Masked AV continuation routing.
Fixed the continuation selector so it appears correctly as a Settings widget.
Fixed multiple audio/video synchronization and exact-duration issues.
Masked AV now conforms source audio to the exact video timeline.
Improved automatic resolution and aspect-ratio handling for continuation clips.
Improved latent-upscale routing and high-resolution conditioning alignment.
Removed the standalone external prompt input box.
Prompt creation is now handled directly through the MiniMax H3 Director prompt builder.
Attention Selector
The Settings panel includes one Attention selector:
ValueBackendDescription0NativeMaximum compatibility and reference quality. Usually the slowest option.1SageAttentionFaster attention with generally similar quality to Native.2Comfy Kitchen AttentionRecommended balance between speed, quality, and compatibility.3Sol-AttnExperimental sparse attention. May provide additional acceleration depending on the GPU.
The selected attention backend is applied to both the FL2VA and REF2VA model paths. Only one backend is active at a time.
Attention requirements
Native: included with ComfyUI.
SageAttention: requires a compatible SageAttention and KJNodes installation.
Comfy Kitchen Attention: requires a recent ComfyUI version.
Sol-Attn: requires ComfyUI-SolAttn_triton.
Spectrum Acceleration
Spectrum is an optional denoising acceleration for MiniMax H3. It can be used together with the selected Attention backend.
For final-quality comparisons, disable Spectrum if you notice:
Weaker motion
Reduced face detail
Ghosting or temporal artifacts
Audio/video inconsistencies
Repository: ComfyUI-Spectrum-MiniMax-H3
Clip Continuation
The workflow supports two continuation modes:
NativeAddGuide
Uses a previous video as visual and audio context.
Recommended AddGuide Context Frames:
1: fastest, minimal context
6: light context
12: balanced short context
22: recommended balance
39: stronger continuity, but slower
Masked AV
Preserves an exact visual and audio prefix from a previous clip while generating the remaining section. It is useful when a more precise AV boundary is required.
Use a source video with synchronized audio and video. NativeAddGuide and Masked AV should not be enabled at the same time.
Repository: ComfyUI-H3-Motion-Context-MultiRef
Automatic Aspect Ratio and Color Match
When continuation is enabled, the workflow automatically derives an output resolution close to the source clip’s aspect ratio while respecting the selected megapixel preset and MiniMax H3 size constraints.
Color Match can reduce visible changes in:
Temperature
Saturation
Brightness
Contrast
Overall color balance
Recommended Color Match Strength:
0.10–0.15: subtle correction
0.20: recommended balance
0.25–0.35: stronger correction
Color Match is used only when a continuation mode is active. Disable it if you experience VRAM issues or unwanted color changes.
Optional Latent Upscale Refinement
The optional LBH branch generates the video at a lower resolution, upscales the latent in latent space, and performs a final high-resolution refinement pass.
Example:
16 total steps = 12 base-resolution steps + latent upscale + 4 high-resolution steps
Recommended scales:
1.25×: lighter and safer
1.50×: recommended starting point
2.00×: heavier and more demanding
The workflow uses:
MinimaxH3LatentUpscaler3DBF16 precision
CUDA processing
Alignment 32
Optional temporal chunking
Automatic model unloading
Repository: Comfyui_Minimax_h3_latent_Upscaler
Model download: Minimax H3 Latent Upscaler
Latent refinement is optional and disabled by default. Results may vary depending on resolution, scale, frame count, GPU, and sampling settings.
Previews and Seed Control
The workflow uses KJNodes ModelPreviewOverride for faster previews.
Repository: ComfyUI-KJNodes
An optional MiniMax H3 TAE preview model can be placed in:
ComfyUI/models/vae_approx/taeh3.safetensorsThe workflow also uses rgthree Comfy Seed for easier seed comparison, randomization, locking, copying, and reuse.
Repository: rgthree-comfy
Required Components
A recent ComfyUI build
FFmpeg
SageAttention, if using Attention 1
ComfyUI-SolAttn_triton, if using Attention 3
ComfyUI-Spectrum-MiniMax-H3, if using Spectrum
Comfyui_Minimax_h3_latent_Upscaler, if using latent upscale
H3 Latent Upscaler – ComfyUI Custom Nodes if using latent upscale
Recommended Starting Settings
Attention: 2 — Comfy Kitchen Attention
Spectrum: enabled for testing; disable for final comparisons if artifacts appear
AddGuide Context Frames: 22
Color Match Strength: 0.20 for continuation
Latent Upscale: disabled initially; test from 1.25× or 1.50×
NativeAddGuide or Masked AV: use only one at a time
For maximum compatibility, use Native Attention, disable Spectrum, and use conservative resolution and refinement settings.
This workflow is intended for experimentation and benchmarking. Results may vary depending on GPU model, VRAM, CUDA/PyTorch versions, ComfyUI version, resolution, frame count, and enabled optimizations.
Description
Multiples bug fixes for I2V, T2V
New Continue from video unified selector
External prompt box deleted
Clip video now is totally optional
FAQ
Comments (9)
The v1.4 workflow keeps saying I don't have the "MinMaxH3ConditioningUpscale" nodes from DaSiWa-nodes despite me updating everything.
did you git pull ComfyUI-DaSiWa-Nodes and
Comfyui_Minimax_h3_latent_Upscaler?,maybe something did not update well
@NegativeMeta I've tried all that, and it didn't fix it. I even uninstalled and reinstalled both node packs clean. Looking at the workflow it's specifically the nodes labelled "🧬 LBH · FL2VA high-res conditioning" and "🧬 LBH · Ref2VA high-res conditioning". It seems the nodes for those literally don't exist.
@guiltyai69 ok I think maybe this node is missing! i use it to fix a bug from dasiwa original workflow please try to install it https://github.com/rockerBOO/h3-latent-upscaler
@NegativeMeta Yep, that seemed to work!
@NegativeMeta I regret to inform you that i'm still getting tensor mismatch errors when trying to use LBH in I2VA. "RuntimeError: shape mismatch: value tensor of shape [1230, 96] cannot be broadcast to indexing result of shape [1200, 96]".
REF2VA works perfectly fine with LBH.
EDIT: Just realised I should mention i'm using DaSiWa's hybrid turbo checkpoint for both REV2VA and FL2VA, as it's a hybrid that can be used in both.
@guiltyai69 I have updated it. Now, I2VA should work with latent upscaled. Please try it!
@NegativeMeta Well, I tried it out. It no longer errors, but the actual results with I2VA LBH are unpredictable. Either the first few frames will be a complete blurry mess and the rest of the video is fine, or the entire video has double-vision/drunk-vision, and it seems to be affected by whatever loras i'm using (it was worst when I was using Mystic XXX). Again, none of this seems to happen when using REF2VA.
Fortunately it seems you can still use I2VA style prompting within REF2VA, so that seems to be a workaround.
@guiltyai69 What exactly parameters are you using to see if I can reproduce that?