BennyDaBall/HyperFlow-H3-Flash-INT8-ComfyUI

HyperFlow H3 Flash INT8 for ComfyUI

HyperFlow H3 Flash running in ComfyUI on ComfyUI's own INT8 kernels: text, image and reference to video with synchronized stereo audio, in 6 steps.

46 s for a 5 s clip with audio on one RTX 5090, or about 38 s with ComfyUI's sparse attention node. The official Q4_K_M GGUF takes 66 s on the same machine.

Speed

One RTX 5090 (32 GB) with 64 GB of system RAM, ComfyUI with CK attention. Text to video at 1344×768, 124 frames (5.2 s at 24 fps) with audio, CFG 1, the same prompt for every run. Each time is the wall clock from queueing the prompt to the saved MP4, averaged over 5 seeds run back to back with the models loaded. A cold first run is not counted.

Setup	Steps	s/it	Mean per clip
This repo (fl2va), patcher: legacy	6	5.4	46.1 s
This repo + ComfyUI Model Sparse Attention (sol-attn, tau 1.25)	6	4.2	about 38 s
Official Q4_K_M GGUF + official HyperFlow nodes	6	8.6	66.0 s
Official Q8_0 GGUF + official HyperFlow nodes	6	8.4	64.4 s
Stock MiniMax H3	20	6.3	139.1 s

With the legacy patcher a 5.2 s clip takes 46.1 s. That is about 30% less time than the official Q4_K_M GGUF on the same machine (66.0 s; Video Rebirth's own figure for that setup on a 5090 is 99 s), and about 3x faster than stock MiniMax H3 at 20 steps (139.1 s). Q8_0 takes 64.4 s.

Adding ComfyUI core's Model Sparse Attention brings the INT8 run to about 38 s. Sparse attention is an approximation, so its output is not identical to dense attention.

Peak VRAM in the legacy run was 23.6 GiB (24,209 MiB, nvidia-smi, whole GPU including the desktop).

What you get

• Both HyperFlow INT8 checkpoints, converted for ComfyUI: fl2va (text, first frame, first + last frame) and ref2va (reference images). No GGUF, no dequantizing to bf16.
• The loader node: comfyui_hyperflow_int8_nodes (HyperFlow INT8 Loader), also on the Comfy Registry as comfyui-hyperflow-int8-nodes.
• Ready-to-run workflows in workflows/: text to video, text to video with sparse attention, first frame, first + last frame, and reference to video. The node pack ships the same files under Workflow > Browse Templates.

Quick start

1. Install two node packs and restart ComfyUI: the official ComfyUI-HyperFlow-Flash and comfyui_hyperflow_int8_nodes. Both are on the Comfy Registry (comfyui-hyperflow-flash, comfyui-hyperflow-int8-nodes) for ComfyUI-Manager, or clone them into ComfyUI/custom_nodes/.
2. Put a checkpoint from this repo in ComfyUI/models/diffusion_models/, plus the text encoder and VAEs from Comfy-Org/MiniMax-H3 (details below).
3. Drag a workflow from workflows/ onto the canvas and queue it.

Examples

All clips are AI-generated with the files in this repo, one run each, seed 42, audio level-matched.

Text to video (fl2va)

A 10 s, 243-frame text-to-video run at 1344x768: the same prompt the bundled text-to-video workflows start with.

Full prompt

Photoreal 35mm action film, one continuous 10-second shot. A sunny Mediterranean hill town of whitewashed houses with blue shutters and potted red geraniums, bright morning light. A daring 25-year-old woman bike courier in a bright yellow jersey, black cycling shorts, a black helmet and a gray messenger bag slung across her back rides a mountain bike flat out down a long, steep outdoor stone staircase that winds between the houses toward the sea. The camera chases her from directly behind at her shoulder height the whole time, racing down the stairs a few meters behind her rear wheel: a fast, bouncing handheld follow shot that keeps her in the center of the frame. Timed action: 0.0-2.0s: she bounces down the stone steps standing on the pedals, the bike rattling, the bag swinging on her back. 2.0-4.0s: a flock of gray pigeons resting on the steps bursts into the air all around her and flutters past the camera. 4.0-6.0s: the stairs end at a small landing with a fruit stall; she pulls up the front wheel and jumps the bike clean over a wooden crate of oranges, landing hard on both wheels as a few oranges tumble and roll down the steps. 6.0-8.0s: she swerves around a startled old baker in a white apron carrying a basket of bread, who throws his free hand up in surprise. 8.0-10.0s: she bursts out of the alley onto a bright harbor road with the deep blue sea and white fishing boats ahead, skids sideways to a stop in a spray of dust, looks back over her shoulder at the camera and grins. Audio: the clatter of tires on stone steps, rattling chain and gears, wings flapping, oranges thudding on the stone, the baker's startled shout, the hiss of the skid, seagulls and the sea at the end. No music.

First frame to video (fl2va)

One generated still in as the first frame, 10 s out: a 243-frame run at 1344x768 with the bundled hyperflow_int8_i2v workflow, only the image, prompt and length changed.

First frame

Prompt summary: on a night train full of passengers from different eras, the woman by the window looks into the camera and says "You're not supposed to be on this train.", then turns back to the moon she drew on the glass.

Full prompt

For the target video, at 0.00 seconds into the target video, <Picture 1> (from [Shot 1]) is fully referenced.
integrated_multimodal_description: [Shot 1] Photoreal 35mm live-action at night inside a vintage train carriage rolling fast through the rain, warm wall lamps and streaks of passing amber and teal light from the rain-streaked window, the clickety-clack of the wheels over the rail joints loud and steady the whole time. The woman (S1) with the black bob and burgundy scarf sits by the window in the foreground; behind her, softly out of focus, passengers from different eras ride quietly: a Victorian gentleman with a newspaper, a 1920s woman in a feathered headband, a 1940s soldier, a 1970s man in a leather jacket and a present-day teenager with earbuds. Locked-off camera, medium close-up on her. 0.0-2.0s: bands of passing light sweep across her face in time with the rhythmic clatter of the wheels as she looks from the crescent moon she drew on the glass toward the camera. 2.0-4.5s: she holds the camera's gaze with a faint, knowing smile, and in a low, calm voice (S1) says: <d>[English] You're not supposed to be on this train.</d> Rain drums on the window. 4.5-6.5s: behind her the Victorian gentleman turns a page of his newspaper with a crisp rustle, the 1920s woman opens her eyes and glances toward the window, and the soldier lifts his head. 6.5-8.5s: she turns back to the window and slowly traces the crescent moon on the glass again with her fingertip, the carriage creaking as it sways. 8.5-10.0s: the train speeds up, the wheel clatter quickens, a distant train horn sounds, and the passing lights flicker faster across the whole carriage. Her face stays the same woman throughout; the passengers behind her stay soft and out of focus.
overall_soundscape: Loud and clear train sound throughout: the steady rhythmic clickety-clack of steel wheels over the rail joints, the deep rumble and rattle of the moving carriage, heavy rain drumming on the window glass, wooden panels creaking as the carriage sways, a crisp newspaper page turn, a distant train horn near the end.
non_diegetic_music: N/A

Reference to video (ref2va)

Three generated references in, one shot out, rendered with the ref2va INT8 file in ComfyUI (our loader, legacy patcher), 1344x768, 124 frames, 6 steps, seed 42. Audio level-matched. AI-generated.

Character	Prop	Location

Prompt summary: the woman from Picture 1 rides the scooter from Picture 2 into the square from Picture 3 while the camera makes one slow push-in to a close-up; she stops and says "Wanna go for a ride?".

Full prompt

<Picture 1> is the woman: keep her face, long blonde waves, yellow sundress and white sneakers exactly as in <Picture 1>. <Picture 2> is the scooter: keep its mint-turquoise paint, chrome trim, round chrome headlight, cream seat and whitewall tires exactly as in <Picture 2>. <Picture 3> is the location: the whitewashed harbor square with blue doors and shutters, magenta bougainvillea, stone paving and the deep blue sea with white boats, exactly as in <Picture 3>. Photoreal 35mm live-action on a bright late morning. The camera starts wide at eye level at the far end of the stone square of <Picture 3>, the harbor wall, the sea and the boats behind her, and makes one slow, steady dolly push-in straight toward her for the whole shot, ending on a medium close-up of her face and shoulders. Timed action: 0.0-1.8s: the woman from <Picture 1> rides the scooter from <Picture 2> into the square from the left, both wheels rolling over the stones, and glides to a stop in the center facing the camera. 1.8-2.6s: she plants both white sneakers on the stones to hold the scooter upright, the scooter's stand stays folded up under the floorboard, her hands stay on the handlebars and she smiles at the approaching camera. 2.6-4.2s: looking straight into the lens, she says playfully, "Wanna go for a ride?" 4.2-5.1s: she tips her head toward the empty cream seat behind her and grins as the camera arrives close on her face. Natural sunlight with soft shadows, shallow depth of field as the camera closes in. Audio: the scooter's small engine puttering, then idling, her clear spoken line, seagulls, gentle waves against the harbor wall. No music.

Use in ComfyUI

Custom nodes

Both packs are required. Clone them into ComfyUI/custom_nodes/ and restart ComfyUI:

1. ComfyUI-HyperFlow-Flash, the official pack: HyperFlow Sigmas and the two-time patch.
2. comfyui_hyperflow_int8_nodes: HyperFlow INT8 Loader for these files, plus the five workflows as templates. Registry id comfyui-hyperflow-int8-nodes.

ComfyUI itself needs native MiniMax-H3 and INT8 convrot support.

Model files

Folder in ComfyUI/models/	File	From
diffusion_models/	minimax_h3_fl2va_hyperflow_flash_int8_convrot.safetensors, minimax_h3_ref2va_hyperflow_flash_int8_convrot.safetensors	this repo
text_encoders/	qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors	Comfy-Org/MiniMax-H3
vae/	minimax_h3_video_vae_fp16.safetensors, minimax_h3_audio_vae_fp32.safetensors	Comfy-Org/MiniMax-H3

fl2va covers text, first frame and first + last frame; ref2va covers reference images. Download only the one you need:

hf download BennyDaBall/HyperFlow-H3-Flash-INT8-ComfyUI minimax_h3_fl2va_hyperflow_flash_int8_convrot.safetensors --local-dir ComfyUI/models/diffusion_models
hf download BennyDaBall/HyperFlow-H3-Flash-INT8-ComfyUI minimax_h3_ref2va_hyperflow_flash_int8_convrot.safetensors --local-dir ComfyUI/models/diffusion_models

Plan on 15.9 to 16.3 GB of VRAM for the weights.

Workflows

Drag a .json from workflows/ onto the ComfyUI canvas, or open it from Workflow > Browse Templates in the node pack's section; the pack ships the same files.

Workflow	Task	File
hyperflow_int8_t2v.json	text to video	fl2va
hyperflow_int8_t2v_sparse.json	text to video with ComfyUI's Model Sparse Attention (sol-attn, tau 1.25)	fl2va
hyperflow_int8_i2v.json	first frame to video	fl2va
hyperflow_int8_flf2v.json	first and last frame to video	fl2va
hyperflow_int8_ref2v.json	reference images to video	ref2va

They are the official HyperFlow templates with the GGUF loader swapped for HyperFlow INT8 Loader. The two text to video workflows start on a 10 s action prompt at 243 frames; the others use 124 frames (5.2 s). t2v_sparse adds the sparse attention node; bypass it (Ctrl+B) to run dense.

workflows/api/ has the API-format versions. To queue one on a running ComfyUI:

import json, urllib.request

wf = json.load(open("workflows/api/hyperflow_int8_t2v_api.json", encoding="utf-8"))
wf["5"]["inputs"]["prompt"] = "your prompt"
wf["5"]["inputs"]["length"] = 124  # 17n + 5 frames at 24 fps
req = urllib.request.Request("http://127.0.0.1:8188/prompt", data=json.dumps({"prompt": wf}).encode(),
                             headers={"Content-Type": "application/json"})
print(urllib.request.urlopen(req).read().decode())

Settings

• Patcher: use patcher: legacy on HyperFlow INT8 Loader. Every bundled workflow does, and the speed numbers above use it. auto (ComfyUI DynamicVRAM) is experimental.
• Steps: HyperFlow Sigmas with 4 (speed), 6 (default) or 8 (quality) steps.
• Sampler: euler, CFG 1, no negative prompt.
• Length: 17n + 5 frames at 24 fps: 124 is 5.2 s, 243 is 10.1 s.

How the conversion works

These are modified files. They are converted versions of fl2va_int8_convrot/ and ref2va_int8_convrot/ from VideoRebirthAI/hyperflow-h3-flash at revision 9e9ed14b8be4b751d7517b8ca58dd199d509720c. The INT8 codes and scales are copied bit for bit. Only the layout changes:

• tensors are renamed to ComfyUI's MiniMax-H3 names;
• the dropped blocks are left out and the kept blocks renumbered;
• INT8 q/k/v are concatenated into one projection;
• the two halves of the first feed-forward projection swap to ComfyUI's gate | value order;
• the low-rank factors stay bf16, zero-padded to a rank multiple of 8;
• the step-endpoint gate and the 6-step sigmas are stored as tensors.

Each file's metadata carries the MiniMax notice and this modification notice. NOTICE lists the changes.

Files

File	Partition	Tasks (official ComfyUI template)	Blocks	Size
minimax_h3_fl2va_hyperflow_flash_int8_convrot.safetensors	fl2va	text, first frame, first + last frame (hyperflow_t2v, hyperflow_i2v, hyperflow_flf2v)	47	15.9 GB
minimax_h3_ref2va_hyperflow_flash_int8_convrot.safetensors	ref2va	reference images (hyperflow_ref2v)	49	16.3 GB

Receipts

Every check was run on CPU against the upstream files:

Check	fl2va	ref2va
INT8 codes + scales bit-identical to upstream	120 / 120 modules	120 / 120 modules
Dequantized weights vs HyperFlow's int8.py	max error 0	max error 0
Linear output vs HyperFlow Int8RotLinear (same activation arithmetic)	bit-identical	bit-identical
Low-rank pairs bit-identical	102 / 102	114 / 114
Unquantized tensors vs the official Q8_0 GGUF	315 / 315 bit-exact	234 / 234 bit-exact
Lowest linear correlation vs Q8_0 GGUF	0.99991	0.99993

License and notices

Unofficial, third-party conversion. These files were converted, and so modified, by a third party: the owner of this repo. MiniMax, Video Rebirth and Comfy Org did not make, review or endorse them. This is not an official MiniMax, Video Rebirth or Comfy Org release.

These files are a Model Derivative of MiniMax-H3, modified from Video Rebirth's HyperFlow H3 Flash. They are distributed under the MiniMax H3 Community License Agreement with no additional or different terms. By downloading or using them, you accept that Agreement:

• Territory: licensed worldwide excluding the European Union, the United Kingdom, the Republic of Korea and the United States of America. Individuals and organizations in those jurisdictions must get MiniMax's prior authorization before downloading (application form; License Q&A).
• Redistribution: any copy of these files must ship with LICENSE (the Agreement) and NOTICE. Modified files must be clearly marked as modified, and no additional or different terms may be imposed (Section III).
• AI-generated content disclosure: publicly distributed content generated with these weights must be clearly and prominently disclosed as AI-generated (Acceptable Use Policy, item 12).
• Commercial use: products or services above $20 million USD in annual revenue need prior written authorization from MiniMax (api@minimax.io). Products and services built with the weights must prominently display "MiniMax H3" on their user interface (Section IV.2).
• Hosted services and use restrictions: hosted services must implement the safeguards in Section V.5 and bind end users to Section V and the Acceptable Use Policy (Exhibit A). Outputs may not be used to train or improve other AI models.
• Upstream text: LICENSE reproduces the August 2, 2026 Agreement text. The version in the upstream repository governs.

The node pack is licensed separately under GPL-3.0.

Thanks to MiniMax for MiniMax-H3, to Video Rebirth for HyperFlow H3 Flash and its ComfyUI pack, and to Comfy Org for ComfyUI's INT8 convrot kernels.

Not an official MiniMax product. Powered by MiniMax H3.