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Frosty40/h3-spark
h3-spark is a machine learning model from Frosty40. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for comfyui. The card lists the license as other.
Complete serving package for running MiniMax H3 video generation on a single NVIDIA DGX Spark, at serving speed. Two parts:
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Updated Aug 16, 2026
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From the Hugging Face model README
Complete serving package for running MiniMax H3 video generation on a single NVIDIA DGX Spark, at serving speed. Two parts:
Repository hub: the canonical source tree, install script, demo footage, and issue tracker live on GitHub: https://github.com/newjordan/h3-spark — start there to actually run the system. This HF repo mirrors the same source and hosts the serving configuration alongside the weights.
weights/ — pruned + NVFP4-quantized checkpoints (modified
derivatives of the MiniMax H3 weights; see weights/MODEL_CARD.md
and weights/LICENSE-MiniMax-H3-Community.txt).config/h3_spark_serving.env).Four-shot segment generated and served from one DGX Spark (drone orbit on the wizard -> knight riding solo -> riding together -> wide shot with a dragon silhouette), with narration voice-over and score mix. Watch it in the GitHub README (it embeds the video):
https://github.com/newjordan/h3-spark
H3_ATTENTION=sage2-quality).H3_MODULATION_FUSION=exact).H3_SWIGLU_NVFP4_FUSION=auto, H3_RMS_ADALN_NVFP4_FUSION=auto) —
200 NVFP4 linears per evaluation.H3_Q_RMS_ROPE_INT8_FUSION=auto), byte-exact on default and
non-default streams.silu(gate)*up native kernel, GPU fp16 host transfer, persistent host
decode buffer, NHWC staging (COMFY_MINIMAX_H3_VAE_*).labs/nvfp4_static/).Warm fixed-reference workload 20-step render — 864×480, 124 frames at 24 fps, six
references, S=20,423, boosting GB10, SM clock recorded in the same
sentence as the time:
| Config | Sampler | % faster | s/step | Executor | % faster | Wall | SM |
|---|---|---|---|---|---|---|---|
| Stock Comfy (BF16 ops) | 243 s | — | 12.1 | ~278 s | — | — | boosting |
| This config, dynamic NVFP4 (2026-08-15) | 153.6 s | 36.8% | 7.68 | 171.7 s | 38.2% | 180.2 s | 2300–2330 MHz |
| This config, promoted static NVFP4 scales (2026-08-15, 200/200 layers) | 148.4–149.4 s | 38.5–38.9% | 7.42–7.47 | 166.4–167.6 s | 39.7–40.1% | 170.0–170.1 s | 2242–2255 MHz |
The 2026-08-15 static artifact passed the fail-closed promotion gate
(verify_promotion.py exit 0): 200/200 static layers, zero excluded
layers, held-out max ratio 0.9873. Static scales are shape-bound and
workload-bound — dynamic NVFP4 is the always-valid default.
Prereqs: ComfyUI (GPL-3.0), comfy-kitchen ≥ 0.2.27 (Apache-2.0), SageAttention ≥ 2.2.0 (Apache-2.0), PyTorch 2.13.0+cu130, Triton 3.7.x, NVIDIA driver ≥ 580, CUDA 13.0. Target: NVIDIA DGX Spark (sm120) or other Blackwell parts (B200 validation in progress).
# 1. get the source (canonical clone — GitHub)
git clone https://github.com/newjordan/h3-spark
cd h3-spark
# 2. weights: official upstream MiniMax H3 checkpoints
hf download MiniMaxAI/MiniMax-H3 --local-dir models --include "Ref2VA/*" "FL2VA/*"
mkdir -p models/ComfyUI/models
cp -r models/Ref2VA models/ComfyUI/models/
cp -r models/FL2VA models/ComfyUI/models/
# 3. overlay: install the serving source overlay into ComfyUI
bash scripts/install_comfyui_overlay.sh /path/to/ComfyUI
# 4. env: export the validated serving defaults
set -a; source config/h3_spark_serving.env; set +a
Our pruned + NVFP4-quantized derivatives (the numbers in the table below) ship as a companion weights package — status and download in the GitHub README.
Start ComfyUI with:
python main.py --listen 127.0.0.1 --port 18188 \
--models-directory /path/to/models/ComfyUI/models \
--disable-pinned-memory --fp16-intermediates --highvram \
--disable-dynamic-vram --fast fp16_accumulation cublas_ops autotune
weights/ are modified derivatives of MiniMax H3
and are licensed under the MiniMax H3 Community License Agreement
(full text in weights/LICENSE-MiniMax-H3-Community.txt, required
NOTICE file alongside). Read it, including the Applicable Territory
definition and Sections III and V, before use or redistribution.third_party_licenses/.docs/PROVENANCE.md.