This node re-samples (enhances / upscales) an already-denoised MiniMax H3 AV latent through the full auto pipeline under tight VRAM constraints: it processes the clip with temporal chunking (so arbitrarily long videos fit in memory) + spatial tiling (so arbitrarily high resolutions fit in memory), keeping peak VRAM bounded to a single tile, while preserving the audio track intact.

MiniMax H3 generates video as a nested latent that bundles 24-channel video and 32-channel audio in one tensor. Standard ComfyUI upscale nodes do not understand this structure. MMH3 Ultimate Upscale wraps the entire temporal split -> latent upscale -> spatial split -> per-tile sampling -> spatial stitch -> temporal stitch loop into one node, so you can upscale a finished H3 clip the same way you would upscale a normal latent — without breaking audio and without running out of VRAM even on small cards.

Features

Upscale long + high-res video on limited VRAM. The core design goal: temporal chunking keeps arbitrarily long clips in memory, spatial tiling keeps arbitrarily high resolutions in memory, and only one tile is sampled at a time — so peak VRAM stays at a single tile regardless of video length or output resolution.
One node, full pipeline. Temporal chunking (outer loop), optional latent upscale, spatial tiling (inner loop), per-tile diffusion sampling, then spatial + temporal stitching — all driven by a single MMH3 Ultimate Upscale node.
Temporal chunking for long videos. A long clip is cut into overlapping time chunks; each chunk is processed independently and stitched back together.
Two upscale modes per chunk:
- H3 3D model-based upscaler (MMH3 Latent Upscale with Model Params) — uses the minimax_h3_latent_upscaler_3d_*.safetensors checkpoints from the latent_upscale_models folder.
- Model-free interpolation (MMH3 Latent Upscale Params) — resizes the video latent spatially (nearest / bilinear / area / bicubic) with no extra model, audio untouched. Mirrors ComfyUI's Upscale Latent but keeps the nested AV structure.
Spatial tiling for bounded VRAM. Each chunk is split into tiles and only one tile is sampled at a time, so peak VRAM stays at one tile instead of the whole frame.
Audio preserved. The audio portion of the latent is carried through unchanged on every chunk and stitch — it is never re-sampled.
Optional stages. latent_upscale_param, temporal_split_param, and spatial_split_param are all optional. Leave any of them unconnected to skip that stage (no upscale / single chunk / whole-chunk sampling).
VRAM-friendly model management. The 3D upscaler is offloaded back to CPU after each use, and the diffusion model is unloaded while the upscaler runs, so H3 + upscaler are never resident at the same time (the next sample reloads H3 automatically).
Per-piece conditioning. Conditioning is re-anchored in time per chunk and spatially cropped per tile; keyframe video latents are resized to the (possibly upscaled) chunk grid.

Advantages

Temporal consistency & smooth time transitions

Frame-0 anchor. At the start of each chunk (except the first), the chunk's frame-0 keyframe is replaced by the previous chunk's re-sampled boundary frame (anchor_conditioning, controlled by anchor_strength, default 0.999 — mirroring the Anchor MiniMax H3 Latent node). This removes detail mismatch at the chunk seam.
Cross-fade stitching. Overlapping chunks are blended with a linear cross-fade (temporal_append / _crossfade) over the overlap region, so transitions between chunks are smooth rather than hard-cut.

Pixel-space consistency & smooth spatial transitions

Frozen overlap mask. Each tile is sampled at its true extent, but the overlap strips it shares with already-stitched neighbors are pre-filled from the accumulated result and locked with a noise_mask (spatial_fade_mask). The re-sample is therefore only allowed to change the free interior; the shared seam content is preserved exactly.
Masked write-back. After sampling, the frozen seam region is written back with torch.where(band, stitched, tile), guaranteeing the already-consistent seam is never overwritten.
Configurable seam blending. The overlap band between tiles is blended with overlap_blend (linear / smoothstep / overwrite / midpoint) under overlap_mode (earlier wins / later wins), giving full control over how adjacent tiles transition into each other — smooth, not blocky.

Other

Peak VRAM bounded to a single tile thanks to spatial tiling + model offloading.
Audio never re-sampled — no audio artifacts, no extra cost.
No forced model download — pick the model-based 3D upscaler or the model-free interpolation path.

Nodes

| Node | Role | |------|------| | MMH3 Ultimate Upscale | Main node. Runs the whole loop. Inputs: latent, conditioning, model, noise, sampler, sigmas, optional negative + cfg, and the three optional param inputs. | | MMH3 Temporal Split Params | chunk_length (px frames, multiple of 17), temporal_overlap (multiple of 17), anchor_strength. | | MMH3 Spatial Split Params | tile_width / tile_height (px, multiple of 32), spatial_w_overlap / spatial_h_overlap (px, multiple of 32), fade_width / fade_height (seam mask fade), min_tile_size, overlap_mode, overlap_blend. | | MMH3 Latent Upscale with Model Params | H3 3D model upscaler: model_name, width, height (snapped to a multiple of 32), device, precision. | | MMH3 Latent Upscale Params | Model-free interpolation: method, width, height (snapped to a multiple of 32). |

Typical workflow

Generate an H3 AV latent with MiniMax H3 (video + audio in one latent).
(Optional) MMH3 Temporal Split Params → connect to temporal_split_param.
(Optional) MMH3 Latent Upscale with Model Params or MMH3 Latent Upscale Params → connect to latent_upscale_param.
(Optional) MMH3 Spatial Split Params → connect to spatial_split_param.
Feed latent, conditioning, model, noise, sampler, sigmas into MMH3 Ultimate Upscale.
Decode the output latent with the H3 VAE.

The width/height you set for upscaling must match the conditioning's generation size (the size the video was conditioned at, after upscale).

Reference Projects

This node is built on top of two existing community projects:

Latent split (temporal / spatial / anchor / append mechanics):
https://github.com/bbaudio-2025/Comfyui-MiniMax-H3-LatentSplit
Latent model-based upscaling (H3 3D upscaler checkpoints & inference):
https://github.com/LBH-123-AI/Comfyui_Minimax_h3_latent_Upscaler

The H3 3D upscaler network code and normalization statistics are adapted from the second project; the temporal/spatial split, anchor and append logic follow the first.

Extra

This project was vibe-coded by AI, If you run into any problems, it's best to search with AI.😂