--- title: MiniMax-H3-Turbo-Lora canonical_url: "https://www.modelscope.cn/models/larryvrh/MiniMax-H3-Turbo-Lora" md_url: "https://www.modelscope.cn/models/larryvrh/MiniMax-H3-Turbo-Lora.md" repository: larryvrh/MiniMax-H3-Turbo-Lora last_updated: 2026-08-09 license: apache-2.0 pipeline_tag: text-to-video-synthesis tasks: - text-to-video-synthesis base_model: - Comfy-Org/MiniMax-H3 base_model_relation: adapter parameters: 3.1B tensor_type: - BF16 library_name: - lora - safetensors - pytorch frameworks: - pytorch downloads: 10289 stars: 57 tags: - text-to-video - text-to-audio - audio-video - lora - minimax-h3 - comfyui --- # MiniMax-H3-Turbo-Lora > MiniMax-H3-Turbo-Lora - larryvrh 在 ModelScope 开源的模型。MiniMax-H3 Turbo LoRA — few-step audio-video generation larryvrh/MiniMax-H3-Turbo-Lora 是 ModelScope 魔搭社区上的 3.1B 参数text-to-video-synthesis模型，采用 apache-2.0 许可，基于 Comfy-Org/MiniMax-H3 构建。 - **Repository**: larryvrh/MiniMax-H3-Turbo-Lora - **License**: apache-2.0 - **Tasks**: text-to-video-synthesis - **Parameters**: 3.1B - **Base model**: Comfy-Org/MiniMax-H3 - **Tags**: text-to-video, text-to-audio, audio-video, lora, minimax-h3, comfyui - **Downloads**: 10289 - **Stars**: 57 - **Last updated**: 2026-08-09 Source: https://www.modelscope.cn/models/larryvrh/MiniMax-H3-Turbo-Lora --- # 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.)