awesome-minimax-h3-integration README

The project's README from github.com/MiniMax-AI/awesome-minimax-h3-integration. As one markdown file: README.md.

MiniMax H3

MiniMax H3 Integrations

A community-maintained index of checkpoints, tools, and workflows for MiniMax H3, ordered by developer interest.

Official resources

Start here

This navigation guide is not a complete compatibility list.

Goal Start with
Run on your GPU Run locally — pick a stack from the VRAM table
Work with audio comfyui-minimax-h3-audio-T8 and audio VAE
Build in ComfyUI Official tutorial · Workflows & nodes
Write better prompts Prompting
Make it faster Speed
Fine-tune it Training & LoRAs
Serve it as an API Serving H3
Run on Apple Silicon antirez/h3.c

Run it locally

MiniMax-H3 generates video with native stereo audio from text, images, video, and audio inputs. It supports clips up to 2K and 15 seconds. Two base variants exist:

Checkpoints are the same size. FL2VA, trained only with keyframes, typically yields better raw output. Ref2VA accepts more reference material but has lower base quality; the Ref Patch can partially bridge this gap.

By VRAM and hardware

Find your GPU in the table, then use the notes to inform your configuration.

Situation Stack Why this combination
24 GB, first run pruned_int8_convrot DiT (19.53 GiB) + TE nvfp4_awq (14.61 GiB) + ComfyUI-MiniMaxH3-Easy Easy routes T2V, I2V, first/last-frame, and reference input through a single Media port. Sampling, LoRAs, and decoding remain outside the node for later modification.
24 GB, want speed The above + TE-Speed-MiniMaxH3 + Turbo v4_step600_ema at 6–8 steps Block-cache acceleration; v3.2 adapts to current ComfyUI's block prefetch and no longer patches core files. 6–8 steps reduce Turbo motion smear.
22 GB, Turing (sm_75) minimax-h3-turing — W4A8 mixed + Turbo 4-step field handbook 5.7 min/clip baseline; T8 BlockCache drafts −43%; PDD 8-step + T8 combo 210 s/clip. sm_75 has no FP8/BF16 tensor cores — quantization, launch flags and kernel support all differ from Ampere+
12–16 GB Pruned Q4_K_M GGUF (10.64 GiB) or pruned nvfp4 (11.67 GiB) + TE Q2_K (7.91 GiB) + fp8mix VAE pair GGUF offers the most size options, beneficial for tight memory. IQ1_S is smaller at 3.78 GiB, but quality noticeably drops.
8 GB DiffSynth-Studio NF4 path The project states 8 GB as its minimum for this path. Offloading performs most work here; expect slow performance, not just small memory footprint.
RTX 50-series / Blackwell NVIDIA Sol-Attn 1.14–1.44× faster than SageAttention with −37 % MLP peak VRAM, measured on a 5090. SM89–SM121, Triton 3.6.0. Also unlocks Blackwell-only hybrid-NVFP4 checkpoints.
Multi-shot / long video ComfyUI-H3-Motion-Context H3 generates in blocks up to 15 s. Motion-Context feeds the previous block's final frame and audio forward, preserving motion direction and speed.
Storyboard / timeline ComfyUI_MiniMaxH3_Director Five importable templates: t2v, fl2v, r2v, v2v, and rv2v.
Inpaint / local edit scraed/LanPaint v2.1.0 fixed H3 support. Training-free video and audio inpainting.
Apple Silicon antirez/h3.c (MIT, Metal-native) h3.c supports T2V/A, first-last-frame, and ordered Ref2VA references end-to-end, with M3 Max / M5 Max performance optimization ongoing.
One-command local open-video-ai/open-video "Ollama for video models" — install · pull · run.

Checkpoints

Source What it is Files Total
MiniMaxAI/MiniMax-H3 Original diffusers weights — transformer/ (FL2VA) and transformer_ref/ (Ref2VA) at 14 shards / 61.73 GiB each, plus text encoder, video VAE, audio VAE, and self-contained FL2VA/ and Ref2VA/ pipeline folders 280 464.2 GiB
Comfy-Org/MiniMax-H3 ComfyUI-repackaged single-file weights — 10 diffusion models, 3 text encoders, video + audio VAE 17 433.2 GiB
Variant Name Precision Size Download
FL2VA minimax_h3_fl2va ![bf16][badge-bf16] 61.73 GiB ![][gh-Comfy--Org]
FL2VA minimax_h3_fl2va ![int8][badge-int8] 31.70 GiB ![][gh-Comfy--Org]
FL2VA minimax_h3_fl2va_pruned ![bf16][badge-bf16] 37.46 GiB ![][gh-Comfy--Org]
FL2VA minimax_h3_fl2va_pruned ![fp8][badge-fp8] 19.52 GiB ![][gh-Comfy--Org]
FL2VA minimax_h3_fl2va_pruned ![int8][badge-int8] 19.53 GiB ![][gh-Comfy--Org]
Ref2VA minimax_h3_ref2va ![bf16][badge-bf16] 61.73 GiB ![][gh-Comfy--Org]
Ref2VA minimax_h3_ref2va ![int8][badge-int8] 31.70 GiB ![][gh-Comfy--Org]
Ref2VA minimax_h3_ref2va_pruned ![bf16][badge-bf16] 37.46 GiB ![][gh-Comfy--Org]
Ref2VA minimax_h3_ref2va_pruned ![fp8][badge-fp8] 19.52 GiB ![][gh-Comfy--Org]
Ref2VA minimax_h3_ref2va_pruned ![int8][badge-int8] 19.53 GiB ![][gh-Comfy--Org]

"Pruned" means AdaLN-pruned. These models are roughly 40% smaller, work only in ComfyUI, and underpin most of the consumer-GPU quants below. For a 24 GB card, pruned_int8_convrot (19.53 GiB) is the usual starting point.

Quantized Models

MiniMax provides original BF16 checkpoints. The files below are community conversions and repackaged variants, not official MiniMax releases. Confirm compatibility with your runtime's documentation before downloading.

Community FL2VA conversions
Pruned Precision Method Size Download
![bf16][badge-bf16] BF16 61.73 GiB ![][gh-Comfy--Org]
![bf16][badge-bf16] Hybrid (fl2va base + ref2va adaln b15-49) 20.97 GiB ![][gh-smhfacct]
![bf16][badge-bf16] Hybrid (fl2va base + ref2va adaln b20-49) 20.97 GiB ![][gh-smhfacct]
![bf16][badge-bf16] Hybrid (fl2va base + ref2va adaln b25-49) 20.97 GiB ![][gh-smhfacct]
![bf16][badge-bf16] Hybrid (fl2va base + ref2va adaln b30-49) 20.97 GiB ![][gh-smhfacct]
![int8][badge-int8] ConvRot 31.70 GiB ![][gh-Comfy--Org]
![int8][badge-int8] ConvRot Lean (HQ) 21.91 GiB ![][gh-DmitryDB]
![int8][badge-int8] ConvRot 20.94 GiB ![][gh-DmitryDB]
![int8][badge-int8] ConvRot Lite 20.33 GiB ![][gh-DmitryDB]
![fp8][badge-fp8] FP8 E4M3FN 43.78 GiB ![][gh-rzgar]
![mxfp8][badge-mxfp8] MXFP8 44.34 GiB ![][gh-rzgar]
![fp8][badge-fp8] FP8 + FP16 attention 26.70 GiB ![][gh-rzgar]
![nvfp4][badge-nvfp4] NVFP4 (HQ) 13.60 GiB ![][gh-DmitryDB]
![nvfp4][badge-nvfp4] NVFP4 10.86 GiB ![][gh-DmitryDB]
![nvfp4][badge-nvfp4] NVFP4 32.05 GiB ![][gh-rockerBOO]
![int4][badge-int4] NF4 (DiffSynth) 15.98 GiB ![][gh-DiffSynth-Studio]
OrbitQuant W4A4 17.03 GiB ![][gh-WaveCut]
![int8][badge-int8] ⚠️ DT-sQKV ConvRot 21.00 GiB ![][gh-DmitryDB]
![int8][badge-int8] ⚠️ DT-sQKV ConvRot Lean 27.99 GiB ![][gh-DmitryDB]
✓ ![bf16][badge-bf16] BF16 37.46 GiB ![][gh-Comfy--Org]
✓ ![fp8][badge-fp8] FP8 scaled 19.52 GiB ![][gh-Comfy--Org]
✓ ![int8][badge-int8] ConvRot 19.53 GiB ![][gh-Comfy--Org] ┊ ![][gh-Abiray]
✓ ![nvfp4][badge-nvfp4] NVFP4 18.69 GiB ![][gh-rockerBOO]
✓ ![nvfp4][badge-nvfp4] NVFP4 + ConvRot INT8 18.69 GiB ![][gh-rockerBOO]
✓ ![nvfp4][badge-nvfp4] NVFP4 11.67 GiB ![][gh-Abiray]
✓ ![int4][badge-int4] Mixed INT4/INT8 ConvRot 14.81 GiB ![][gh-Abiray] ┊ ![][gh-tsolful]
✓ ![int4][badge-int4] Mixed INT4/INT8 ConvRot Lean 17.27 GiB ![][gh-tsolful]
✓ ![int4][badge-int4] INT4 ConvRot 15.67 GiB ![][gh-rockerBOO]
✓ ![int4][badge-int4] Mixed INT4/INT8 ConvRot 18.92 GiB ![][gh-rockerBOO]
✓ ![int4][badge-int4] INT4 ConvRot 16.67 GiB ![][gh-Merserk]
✓ ![int4][badge-int4] INT4 ConvRot (pruned) 10.56 GiB ![][gh-Merserk]
✓ ![int4][badge-int4] W4A8 ConvRot 11.68 GiB ![][gh-AX1Y2JP] ┊ ![][gh-Kijai] ┊ ![][gh-Winnougan]

GGUF quants — see the GGUF section.

Community Ref2VA conversions
Pruned Precision Method Size Download
![bf16][badge-bf16] BF16 61.73 GiB ![][gh-Comfy--Org]
![int8][badge-int8] ConvRot ┊ (patchin HF 1.02) 31.70 GiB ![][gh-Comfy--Org] ┊ ![][gh-t8star]
![int8][badge-int8] ConvRot Lean (HQ) 21.91 GiB ![][gh-DmitryDB]
![int8][badge-int8] ConvRot 20.94 GiB ![][gh-DmitryDB]
![int8][badge-int8] ConvRot Lite 20.33 GiB ![][gh-DmitryDB]
![nvfp4][badge-nvfp4] NVFP4 (HQ) 13.60 GiB ![][gh-DmitryDB]
![nvfp4][badge-nvfp4] NVFP4 10.86 GiB ![][gh-DmitryDB]
![nvfp4][badge-nvfp4] NVFP4 32.05 GiB ![][gh-rockerBOO]
![nvfp4][badge-nvfp4] NVFP4 mixed 22.76 GiB ![][gh-Abiray]
![int4][badge-int4] NF4 (DiffSynth) 15.98 GiB ![][gh-DiffSynth-Studio]
OrbitQuant W4A4 17.03 GiB ![][gh-WaveCut]
![nvfp4][badge-nvfp4] Hybrid NVFP4, FFN-only (Blackwell) 16.38 GiB ![][gh-abakanai]
![nvfp4][badge-nvfp4] Hybrid NVFP4, QKV+FFN (Blackwell) 14.03 GiB ![][gh-abakanai]
![int8][badge-int8] ⚠️ DT-sQKV ConvRot 21.00 GiB ![][gh-DmitryDB]
![int8][badge-int8] ⚠️ DT-sQKV ConvRot Lean 27.99 GiB ![][gh-DmitryDB]
✓ ![bf16][badge-bf16] BF16 37.46 GiB ![][gh-Comfy--Org]
✓ ![fp8][badge-fp8] FP8 scaled 19.52 GiB ![][gh-Comfy--Org]
✓ ![int8][badge-int8] ConvRot 19.53 GiB ![][gh-Comfy--Org] ┊ ![][gh-Abiray]
✓ ![nvfp4][badge-nvfp4]

awesome-minimax-h3-integration (MiniMax-AI/awesome-minimax-h3-integration)

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What is this?A community-maintained index of checkpoints, tools, and workflows for MiniMax H3, a video generation model that produces clips with native stereo audio from text, image, video, and audio inputs.
Is this a tool, or just a list of links?It is a curated reference list (an awesome-list) that points to official and community checkpoints, quantizations, ComfyUI nodes, and workflows for MiniMax H3 — it does not run anything itself.
How is the list organized?It opens with a goal-based table (run locally, use audio, build in ComfyUI, write prompts, speed up, fine-tune, serve via API, run on Apple Silicon), then a VRAM table that maps GPU memory to a recommended checkpoint and text-encoder stack.
How much VRAM do I need to run MiniMax H3?Anywhere from 8 GB (DiffSynth-Studio NF4 path with heavy offloading) up to 24 GB+ for the standard pruned int8 ConvRot checkpoint; the README's VRAM table matches specific GPU tiers to checkpoint/text-encoder combinations.
Are the quantized checkpoints official MiniMax releases?No. Only the original BF16 diffusers weights from MiniMaxAI are official; all the INT8/FP8/NVFP4/GGUF conversions in the list are community repackagings, so you should confirm compatibility with your runtime before downloading.
Does this only work with NVIDIA GPUs, or can I use it on a Mac?Most stacks target NVIDIA GPUs from Turing (sm75) through Blackwell/RTX 50-series, but there is also a native Metal path for Apple Silicon via antirez/h3.c, with M3/M5 Max optimization still ongoing.
What's the difference between FL2VA and Ref2VA?FL2VA (first-and-last-frame mode) takes zero, one, or two input images and typically yields better raw quality; Ref2VA (omni-reference mode) accepts up to 9 images, 3 video clips, and 3 audio clips for richer conditioning but with slightly lower base quality that the Ref Patch partially offsets.
Can MiniMax H3 generate audio along with video?Yes, it generates video with native stereo audio directly from text, image, video, and audio inputs, and there is a dedicated comfyui-minimax-h3-audio-T8 node plus an audio VAE for this.
How long and high-resolution are the generated clips?Clips can run up to 2K resolution and 15 seconds, and tools like ComfyUI-H3-Motion-Context can chain multiple blocks together for longer, multi-shot videos.
Is there a one-command way to run MiniMax H3 locally?Yes, open-video-ai/open-video is described as 'Ollama for video models' — you install it, pull the model, and run it with a single command.
Creator
MiniMax-AI
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0.2 MB
Stars
442
Updated
CommitOct 17
Age
2mo
Commits · 90 Days