| --- |
| license: apache-2.0 |
| base_model: Comfy-Org/MiniMax-H3 |
| tags: |
| - text-to-video |
| - text-to-audio |
| - audio-video |
| - lora |
| - minimax-h3 |
| - comfyui |
| pipeline_tag: text-to-video |
| --- |
| |
| # MiniMax-H3 Turbo LoRA — few-step audio-video generation |
|
|
| A LoRA for [MiniMax-H3](https://huggingface.co/Comfy-Org/MiniMax-H3) that renders |
| joint **video + synchronized stereo audio** in as few as **4 sampling steps** |
| instead of the usual ~20 — a ~5× sampling speedup — and keeps getting better as |
| you add steps. |
|
|
| ## Which checkpoint — `v4` (step 600) or `v1` (850)? |
|
|
| For **most** work, use **`minimax_h3_turbo_v4_step600_ema.safetensors`**. It's the |
| strongest checkpoint we've released: much better static and small-motion shots, |
| markedly better micro-detail (faces, fingers, fine texture), and the |
| over-sharpening / plastic look of the earlier `v1` (~850) line is **fully |
| resolved**. |
| |
| v4 introduced a **static-frame enhancement** — a big win for static and |
| small-motion content. The one trade-off shows up **only at 4 steps with large, |
| fast motion**, where v4 can produce **motion-smear / trailing ghosting** (we're |
| actively fixing this). Two things address it: |
| |
| - **Use 6–8 steps.** This **largely removes the smear** and is where v4 looks its |
| best. v4 also tolerates higher step counts better than v1, which tends to |
| over-sharpen at high steps + strength 1.0. |
| - For the specific case of **4 steps *and* heavy motion**, the older **`v1` ~850** |
| checkpoint can still be the friendlier pick. |
| |
| ``` |
| Using 6–8 steps? ── yes ──► v4-600 (recommended) |
| │ no (4 steps) |
| ▼ |
| Heavy / fast motion? ── no ──► v4-600 (recommended) |
| │ yes |
| ▼ |
| v1-850 (friendlier at 4-step heavy motion) |
| ``` |
| |
| Still a preview — training continues; the two areas still being improved are |
| **audio** and **behaviour under fast, intense motion**. |
| |
| ## Steps and strength — read this |
| |
| - **4 steps is the recommended *minimum*; 4–8 is the useful range.** 6–8 steps |
| look noticeably better than 4, so add steps if you can afford them. Past **8 |
| steps** it stops helping and can start to introduce **over-sharp artifacts** — |
| there's no benefit to going higher, so stay in **4–8**. |
| - **Keep strength at `1.0`.** It's tuned for 1.0 and holds up well across the 4–8 |
| step range. Only reach for the strength dial if a *specific* clip misbehaves — |
| then **blurry ghosting / smear → nudge up** (`~1.05–1.2`), **over-sharp grain → |
| nudge down** (`~0.8–0.95`). |
| - Keep the scheduler on `simple`. |
| |
| ## Use it in ComfyUI (recommended) |
| |
| Custom nodes: **[Larryvrh/ComfyUI-MiniMax-H3-Turbo](https://github.com/Larryvrh/ComfyUI-MiniMax-H3-Turbo)** |
| — or search **"MiniMax-H3 Turbo"** in ComfyUI-Manager. (Keep the node updated; it |
| evolves alongside these weights.) |
| |
| 1. Install the nodes (Manager, or `git clone` into `ComfyUI/custom_nodes`) and put |
| a `.safetensors` from this repo into `ComfyUI/models/loras/`. You also need the |
| base MiniMax-H3 model, VAEs and text encoder — see the |
| [MiniMax-H3 tutorial](https://docs.comfy.org/tutorials/video/minimax/minimax-h3). |
| 2. Start from the official MiniMax-H3 workflow (t2v or i2v) and make two changes: |
| - insert **MiniMax-H3 Turbo LoRA** between the model loader and the sampler; |
| - feed `SamplerCustomAdvanced` from **MiniMax-H3 Turbo Sampler**, and set the |
| scheduler to `simple` at **≥ 4 steps**. |
| |
| Everything else stays as in the official graph, so both text-to-video and |
| image-to-video work. A ready-made t2v workflow ships in the |
| [node repo](https://github.com/Larryvrh/ComfyUI-MiniMax-H3-Turbo/tree/main/example_workflows) |
| (and here as `minimax_h3_t2v_turbo.json`) — drag it in. |
|
|
| - **Base model**: any MiniMax-H3 base — full (`bf16`, `int8_convrot`) **and the |
| pruned/curve variants** (`pruned_int8`, `pruned_fp8`). The node auto-detects a |
| pruned base and re-injects the time-conditioning at run time, so **one LoRA file |
| covers every base**. |
| - **`low_vram`** switch: **off** applies the LoRA at run time (sharpest, |
| recommended); **on** merges it into the weights for the lowest peak VRAM (a bit |
| softer on quantized bases). Turn it on only if you run out of memory. |
| - The custom sampler **auto-adapts to your ComfyUI version**: MiniMax-H3 runs |
| video and audio on two different flow schedules; recent ComfyUI handles that |
| natively (`ModelSamplingAV`) and older ComfyUI doesn't — the Turbo Sampler |
| detects which and does the right thing either way, so nothing to change when you |
| update ComfyUI. |
| |
| ## Weights |
| |
| All bf16, ~744 MB, applied as a plain low-rank update |
| (`W_eff = W + lora_B @ lora_A`, alpha = rank, so no extra scaling). **Prefer the |
| EMA files**; the non-EMA ones are for comparison. |
| |
| | file | notes | |
| |---|---| |
| | **`minimax_h3_turbo_v4_step600_ema.safetensors`** | **recommended — current best.** Strong static/small-motion, good micro-detail, no over-sharpening. | |
| | `minimax_h3_turbo_v4_step600.safetensors` | v4-600 non-EMA (comparison). | |
| | `minimax_h3_turbo_v4_step150_ema.safetensors` | earlier v4 checkpoint. | |
| | `minimax_h3_turbo_4step_ema_ckpt850.safetensors` | `v1` line (~850) — over-sharpened / plastic in general, but the friendlier pick for **4-step heavy motion** (see above). | |
| | `minimax_h3_turbo_4step_ema_ckpt500.safetensors` | older `v1` (~500), softer. | |
| | `minimax_h3_turbo_4step_ema.safetensors` | initial release (~200). | |
|
|
| *Naming:* `v4` is the current training recipe and `stepN` is the training step. |
| Older files carry the previous `4step_ckptN` naming, where `4step` referred to the |
| sampler-step count. |
|
|
| ## Standalone (no ComfyUI graph) |
|
|
| `generate.py` is a single self-contained file — it loads the base DiT + a LoRA, |
| encodes the prompt, runs the few-step dual-schedule sampler, decodes and muxes an |
| mp4. It still needs a ComfyUI checkout for the H3 model / VAE / text-encoder |
| definitions: |
|
|
| ```bash |
| git clone https://github.com/comfyanonymous/ComfyUI |
| cd ComfyUI && pip install -r requirements.txt && cd .. |
| pip install -r requirements.txt # this repo: torch, safetensors, imageio-ffmpeg |
| |
| # base weights from Comfy-Org/MiniMax-H3 into a models/ tree, then: |
| python generate.py \ |
| --comfyui ./ComfyUI \ |
| --base models/diffusion_models/minimax_h3_fl2va_bf16.safetensors \ |
| --lora minimax_h3_turbo_v4_step600_ema.safetensors \ |
| --te models/text_encoders/qwen3vl_32b_minimax_h3_int8_convrot.safetensors \ |
| --video-vae models/vae/minimax_h3_video_vae_fp16.safetensors \ |
| --audio-vae models/vae/minimax_h3_audio_vae_fp32.safetensors \ |
| --prompt "A corgi in a chef hat flipping a pancake, sizzling sounds and a cheerful bark." \ |
| --width 1344 --height 768 --frames 124 --steps 6 --out corgi.mp4 |
| ``` |
|
|
| ## Notes |
|
|
| - **Resolution / duration**: width and height are multiples of 32 (short edge |
| typically 768). Frame count is at 24 fps and snaps to the model's 17·k+5 grid |
| (124 ≈ 5 s). Validated range ~124–362 frames (~5–15 s). |
| - **VRAM**: the base model is large (~33 B); an 80 GB GPU is comfortable at the |
| largest resolutions. The ComfyUI node streams the base and adds the `low_vram` |
| switch, so it runs on much smaller GPUs. In the standalone script, |
| `--offload-adaln` trades ~13 GB of VRAM for CPU RAM. |
| - **Audio**: 32 kHz stereo, aligned to the video; the two streams ride different |
| flow schedules and are integrated each on its own clock. (Audio is one of the |
| two areas still being improved — see the top.) |
|
|
