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    [MiniMax H3] NSFW I2VA / T2VA / FL2VA / R2VA Workflows 👾 Qwen3.5 Auto Prompt | ⚡ MiniMax-H3 Turbo LoRA | 🔈 Native Audio | TensorRT Upscale | RIFE Interpolation - 🔁 OneClick - FL2VA Loop
    NSFW

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    ComfyUI-QwenVL-Mod — Enhanced Vision-Language with MiniMax H3 Version 2.8.0 (2026/09/02) — 🎬 MiniMax H3 Native Video+Audio + NVFP4 Blackwell + SOL-ATTN + Spectrum (native only) + lightx2v Turbo LoRA + Wildcards + 10Eros-Max Support + Camera Tag Dropdown + Unified FL2VA Loop

    ⬆️ 2026/09/04 UPDATE ⬆️

    🔧 Turbo LoRA Switch — larryvrh → lightx2v 8-step 768p

    All Turbo workflows now use lightx2v Turbo LoRA 8-step 768p (Apache-2.0) instead of larryvrh v4-600:

    • FL2VA: minimax_h3_fl2v_turbo_8step_v1.0_768p_comfyui_bf16.safetensors (~1.96 GB)

    • Ref2VA: minimax_h3_ref2v_turbo_8step_v1.0_768p_comfyui_bf16.safetensors (~1.96 GB)

    • No custom node required — standard ComfyUI LoRA loader works

    • Removed Larryvrh/ComfyUI-MiniMax-H3-Turbo custom node

    • Trained at 1344×768 — matches our native resolution exactly

    🚫 Spectrum + Sol-Attn Bypass with Turbo — Verified

    Community testing confirmed that Spectrum and Sol-Attn cause fallbacks and slowdown when used with Turbo LoRA at 8 steps:

    • Spectrum: forecasts steps that don't have enough context at 8-step — fallbacks double the work. "Near-useless at 10 steps" (community)

    • Sol-Attn (tau 1.3→0.8): aggressive sparse approximation on 8-step trajectory causes reconstruction fallbacks

    • Rule: bypass both Spectrum and Sol-Attn when Turbo LoRA is active. They are for 20-step native only

    Turbo pure: Turbo LoRA ON · Spectrum OFF · Sol-Attn OFF · euler + simple · 8 steps Native + Spectrum: Turbo LoRA OFF · Spectrum ON · Sol-Attn ON (tau 1.0) · res_multistep + simple · 20 steps

    🔄 10Eros-Max Switch — DmitryDB → cicalooo TURBO Hybrid Beta3

    The 10Eros-Max model has been switched to cicalooo's ComfyUI-native INT8 ConvRot Turbo Hybrid Beta3:

    • Model: 10Eros_Max_h3_TURBO-hybrid_beta3_int8_convrot_skip_edges.safetensors (~22.5 GB)

    • TURBO fused in checkpoint — no separate t8star LoRA needed

    • Boundary blocks 0, 1, 48, 49 left in BF16 for stability

    • Removed DmitryDB 10Eros model + t8star compatibility LoRA

    ⚡ Comfy Kitchen Attention — Replaces SageAttention

    All MMH3 Docker/provisioning now uses --use-ck-attention (Comfy Kitchen Attention) instead of --use-sage-attention:

    • Faster on Blackwell (RTX 5090 / PRO 6000)

    • Better detail preservation

    • No separate SageAttention package needed

    ⬆️ 2026/09/02 UPDATE ⬆️

    🎥 Camera Tag Dropdown (19 movements)

    The QwenVL node now has a camera_tag dropdown — no more typing [ORBIT] manually in the prompt. Select from 19 camera movements directly in the node UI:

    CategoryTagsStatic[STATIC_CAMERA], [LOCKED_OFF]Slow zoom[SLOW_ZOOM_IN], [SLOW_ZOOM_OUT]Fast zoom[FAST_ZOOM_IN], [FAST_ZOOM_OUT]Pan[PAN_LEFT], [PAN_RIGHT]Tilt[TILT_UP], [TILT_DOWN]Dolly[DOLLY_IN], [DOLLY_OUT]Tracking[TRACKING_LEFT], [TRACKING_RIGHT]Crane[CRANE_UP], [CRANE_DOWN]Other[ORBIT], [HANDHELD], [ROLL]

    How it works: when you select a tag, it's injected both at the start of the prompt and as a FINAL CAMERA DIRECTIVE at the end — so Qwen 9B actually respects it despite recency bias on long prompts. The tag also gets a short description so Qwen knows exactly what to write.

    Subject stays alive: the directive explicitly tells Qwen that the camera tag controls ONLY the camera — the subject must still have natural, lively action (breathing, gestures, expression, body motion) throughout the clip. No more "statue during orbit" problem.

    Manual tags still work: if you leave the dropdown on None and type [ORBIT] in your prompt, it's detected and injected automatically as a fallback.

    Available on all three QwenVL nodes: AILab_QwenVL, AILab_QwenVL_Advanced, and AILab_QwenVL_PromptEnhancer.

    🔄 FL2VA Loop Merged into FL2VA — One Workflow, Bypass Group

    The separate MiniMaxH3-Turbo-FL2VA-Loop-Qwen3.5 workflow is removed. The loop trim logic now lives inside the main FL2VA workflow, wrapped in a "Loop Trim" group that can be toggled via the rgthree Fast Groups Bypasser node:

    • Loop mode (trim active): the ImageFromBatch + ComfyMathExpression nodes trim the frozen tail (~5 frames) for seamless looping

    • Non-loop mode (trim bypassed): toggle the group off in the Bypasser → VAEDecode passes directly to RIFE/upscale, full frames preserved

    No more switching between two workflows — just toggle the group.

    🧹 PromptEnhancer Cleanup

    • Removed the redundant custom_system_prompt input — enhancement_style (presets) + prompt_text (user input) cover all use cases

    • Removed CUSTOM_ONLY_STYLE ("✍️ Custom Only (no preset)") — no longer needed

    • Added camera_tag dropdown (same as main QwenVL nodes)

    ⬆️ 2026/08/31 UPDATE ⬆️

    🎲 Wildcards (T2VA Workflow)

    The T2VA Turbo workflow includes a WildcardProcessor node that injects randomized prompt fragments from the MadBe's Prompt Engine (__mbe/prmpt/*) wildcard library. Each generation picks a random entry from each wildcard file, so the same seed produces different results across runs unless you pin the seed.

    Wildcards Used in the T2VA Workflow

    WildcardCategoryWhat it randomizes__mbe/prmpt/vidstyle__Video styleCinematic / anime / vintage film / 3D CG / claymation / watercolor / fantasy etc.__mbe/prmpt/imgcmp/shots__Camera shotClose-up / wide / medium / dolly / crane / orbit / handheld etc.__mbe/prmpt/lctns/rndmlctns__LocationRandom setting (bedroom / beach / studio / alley / forest / rooftop etc.)__mbe/prmpt/light/rndmlight__LightingKey light direction, color temperature, soft/hard, ambient mood__mbe/prmpt/char/favchar__CharacterRandom character archetype (age, body type, hair, ethnicity)__mbe/prmpt/clths/rndmclth__ClothingRandom outfit / garment description__mbe/prmpt/clths/nudty_brsts__NSFWBreast / nudity descriptors (NSFW preset)__mbe/actsolo/brstplng__NSFW actionSolo breast-play action verbs (NSFW preset)

    How It Works

    1. The WildcardProcessor node sits before the Qwen3-VL prompt enhancer

    2. At queue time, each __wildcard__ token is replaced with a random line from the corresponding .txt file inside ComfyUI/custom_nodes/ComfyUI-Wildcards/wildcards/mbe/prmpt/

    3. The expanded text is passed to Qwen3-VL, which converts it into the official MiniMax H3 prompt format

    4. Different seed = different wildcard picks — use a fixed seed if you want reproducible results

    Customizing Wildcards

    • Edit existing: open the .txt files under ComfyUI/custom_nodes/ComfyUI-Wildcards/wildcards/mbe/prmpt/ and add/remove lines (one entry per line)

    • Add your own: create a new .txt file, e.g. mbe/prmpt/mytags.txt, then reference it as __mbe/prmpt/mytags__

    • Remove a wildcard: delete the __...__ token from the WildcardProcessor text field in the workflow

    • Disable randomization: replace the __wildcard__ token with a fixed string

    Required Custom Node

    The wildcard files ship with the custom node. If a wildcard resolves to empty, the custom node is missing or the wildcard folder is not installed.

    🔄 Sampler Change — MiniMaxH3TurboSampler → KSamplerSelect + MiniMaxH3SigmaShift

    All 4 Turbo workflows (T2VA, I2VA, FL2VA, R2VA) have been updated to use ComfyUI core nodes instead of the custom MiniMaxH3TurboSampler:

    • Removed: MiniMaxH3TurboSampler (custom node from Larryvrh/ComfyUI-MiniMax-H3-Turbo)

    • Added: KSamplerSelect (sampler: euler) + MiniMaxH3SigmaShift (shift_video=12, shift_audio=3) — both ComfyUI core nodes, no custom node required

    • Scheduler: simple (unchanged)

    Why?

    • On ComfyUI v0.34.2+ with native ModelSamplingAV, the custom MiniMaxH3TurboSampler internally delegates to stock euler anyway — the custom node is redundant

    • Using core nodes means the same workflow works with both:

      • Standard model (minimax_h3_fl2va_pruned_nvfp4_convrot_int8) + Turbo LoRA minimax_h3_turbo_v4_step600_ema

      • 10Eros-Max (10Eros_Max_H3_FL2VA-INT8-ConvRot-HQ) + T8 compatibility LoRA minimax_h3_fl2v_turbo_8step_v1.0_10ErosMax_beta1_pruned_compat_v001_T8

    • Just swap LoadDiffusionModel and LoraLoaderBypassModelOnly — the sampler path stays the same

    10Eros-Max (Optional — Experimental)

    • Model: 10Eros_Max_H3_FL2VA-INT8-ConvRot-HQ.safetensors (~23.5 GB) — DmitryDB/MiniMax-H3-10Eros-Max-Quants

    • LoRA: minimax_h3_fl2v_turbo_8step_v1.0_10ErosMax_beta1_pruned_compat_v001_T8.safetensors (~1.96 GB) — t8star/minimax_h3_turbo_4step_10ErosMax_test4_pruned_curveproj1025_T8

    • Sampler: euler + MiniMaxH3SigmaShift (shift 12/3) + simple scheduler — same as standard model

    • ⚠️ NVFP4 degrades quality and audio on the 10Eros fine-tune — use INT8 ConvRot HQ only

    • ⚠️ The T8 LoRA is checkpoint-specific — only works with the exact 10Eros pruned model (SHA-256: f82cc3f723b080e7ae94a7c98f95aa989e387618d0bdc940133dfbd9f432c062)

    ⬆️ 2026/08/27 UPDATE ⬆️

    NVFP4+INT8 ConvRot Hybrid — New Default

    • Default diffusion models: NVFP4+INT8 ConvRot hybrid (minimax_h3_fl2va_pruned_nvfp4_convrot_int8 / minimax_h3_ref2va_pruned_nvfp4_convrot_int8) from lilcheaty/MiniMax-H3-NVFP4 — NVFP4 on MLP, INT8 ConvRot on attention, BF16 on sensitive layers. Best speed/quality on Blackwell, ~2.5x faster than pure INT8 with identical visual quality

    • Uncensored text encoder: NVFP4 (qwen3vl_32b_heretic_minimax_h3_nvfp4) from Momoking/Qwen3-VL-32B-Heretic-MiniMax-H3-NVFP4 — fast on Blackwell, no quality impact on text encoding

    • ⚠️ Non-Blackwell GPUs: Use pure INT8 ConvRot models from Comfy-Org/MiniMax-H3 instead. NVFP4 requires sm_120+ (RTX 5090 / PRO 6000).

    SOL-ATTN + Spectrum Integration

    • All 4 Turbo workflows now include SOL-ATTN (Scheduled Sol Attention) for sharper output

    • All 4 Turbo workflows now include Spectrum adaptive smoothing (offline replay disabled for speed)

    • Turbo LoRA linked from preset to subgraph in all workflows

    Turbo Step Standardization

    • All Turbo workflows standardized to 8 steps (was 6 for T2VA/R2VA)

    • Consistent minimax_h3_turbo_v4_step600_ema LoRA across all workflows

    TensorRT Batch Size

    • RIFE and Upscaler TRT expose separate loader and runner batch_size parameters

    • Verified stable configuration:

      • RIFE: loader 1, runner 1

      • Upscaler: loader 2, runner 2

    • The loader compiles the TensorRT engine profile; the runner controls frames sent per infer() call (runner ≤ loader)

    • RIFE batch values above 1 can build but currently fail during interpolation; keep RIFE at 1/1

    • Upscaler 2/2 is verified on RTX PRO 6000 Blackwell; batch 4 fails to build with TensorRT 10.15 on sm_120

    • Changing the loader batch size requires a different engine; delete incompatible cached TRT engines before rebuilding

    Upscaler: Auto-detect Scale Factor

    • Removed the scale dropdown (2x/4x) from the Upscaler runner node — it was redundant and error-prone

    • The loader now auto-detects the upscale factor from the model name (2x* → 2, 4x* → 4, x2plus → 2, x4plus → 4)

    • The factor is passed to the runner via the engine object — no more mismatch between model and scale setting

    • Requires ComfyUI-Upscaler-TensorRT-Auto updated to latest version

    ⚠️ Requirements — Read First!

    GPU & VRAM

    • 🟢 Recommended template configuration — RTX 5090 (32 GB) / RTX PRO 6000 (48 GB) → NVFP4 diffusion + NVFP4 text encoder

    • 🟡 Non-Blackwell alternative — RTX 4090 / 3090 (24 GB) → INT8 ConvRot + offload

    • 🟠 Lower-VRAM alternative — 12–16 GB → INT4 + aggressive offload; slow and not recommended for production

    • ⚠️ NVFP4 requires Blackwell (sm_120+) and does not run on RTX 4090/3090/4080

    12 GB GPUs (e.g. RTX 3060 12GB): Technically possible with INT4 models + aggressive offloading, but very slow. You need 32 GB+ system RAM and a fast NVMe SSD. Not recommended for production use.

    Model Quantization Options

    Software

    • ComfyUI: v0.31.0+ (required for MiniMax H3 native support)

    • Python: 3.10+

    • CUDA: 12.8+ (13.0 recommended)

    • Storage: allow at least 90 GB for the complete provisioned package (~81 GB of models plus engines, workflows and outputs)

    Qwen3-VL Prompt Enhancer

    • GGUF: Q4_K_S (~4.8 GB) or Q5_K_S (~5.5 GB) for 8B model

    • HF: Qwen3-VL-8B-Heretic-Stable (~16 GB) or Qwen3-VL-4B (~8 GB)

    ⚡ MiniMax-H3 Turbo LoRA (Optional — Faster & Sharper)

    A distilled 8-step LoRA for MiniMax-H3 that replaces the default ~20-step sampling, with a dedicated ComfyUI node. All Turbo workflows now include SOL-ATTN (Scheduled Sol Attention) and Spectrum adaptive smoothing for sharper, smoother output.

    Works with all tasks: T2VA, I2VA, FL2VA and R2VA.

    🌟 What is ComfyUI-QwenVL-Mod?

    A powerful enhanced vision-language node for ComfyUI that combines Qwen3-VL models with MiniMax H3 video generation workflows. Features multilingual support, visual style detection, native stereo audio, and NSFW capabilities for professional AI content creation.

    Think: "Your all-in-one solution for intelligent prompt enhancement and video+audio generation with MiniMax H3!"

    🎬 Key Features

    🚀 MiniMax H3 Video+Audio Generation

    • T2VA (Text-to-Video+Audio): Generate video with native stereo audio from text

    • I2VA (Image-to-Video+Audio): Animate a first-frame image with audio

    • FL2VA (First-Last-Frame): Generate the transition between two keyframes — Qwen3-VL sees both frames

    • R2VA (Reference-to-Video): Lock character identity, style, motion, or voice using reference images

    🧠 Qwen3-VL Auto-Prompting

    • Multilingual: Write your prompt in any language — Qwen3-VL translates and converts it

    • Auto-format: Generates the official MiniMax H3 prompt format (3-field for base, 6-field for R2VA)

    • Multi-reference: Qwen3-VL sees all connected images via image + image2 inputs

    • Visual style detection: 12+ artistic styles (photorealistic, cinematic, anime, 3D CG, claymation, vintage film, watercolor, fantasy, etc.)

    • Smart caching: Performance optimization with Fixed Seed Mode

    • GGUF backend: Efficient local model inference with quantization support

    • Qwen3.5 support: Thinking mode disabled via /no_think for fast prompt generation

    🔊 Native Stereo Audio

    • No separate audio node needed — MiniMax H3 generates video and audio jointly in a single forward pass

    • Voice, sound effects, and music modeled together, not layered on afterward

    • Describe sounds in your prompt and the model generates them natively

    🎨 NSFW Support

    • Comprehensive content generation without restrictions

    • 9 dedicated NSFW presets (3 base 🎬 + 3 R2VA 🎞️ + 3 FL2VA 🔄) with explicit diegetic soundscape

    • Natural progression, style adaptation, consistent characters

    📦 What's Included — 4 Turbo Workflows

    All workflows are pre-wired with MiniMax-H3 Turbo LoRA + MiniMax-H3 Turbo Sampler at 8 steps + SOL-ATTN + Spectrum.

    1. ⚡ T2VA Turbo — MiniMaxH3-Turbo-T2VA-Qwen3.5.json — text only — Text-to-video+audio. Simplest workflow.

    2. ⚡ I2VA Turbo — MiniMaxH3-Turbo-I2VA-Qwen3.5.json — text + first-frame image (image) — Image-to-video. First-frame animation with audio.

    3. ⚡ FL2VA Turbo — MiniMaxH3-Turbo-FL2VA-Qwen3.5.json — text + first-frame (image) + last-frame (image2) — First-Last-Frame to video. Includes TensorRT upscale + RIFE frame interpolation for 48 fps output.

    4. ⚡ R2VA Turbo — MiniMaxH3-Turbo-R2VA-Qwen3.5.json — text + reference images (image + image2) — Reference-to-video. Lock identity, style, motion, camera, or voice using up to 9 ref images.

    Workflows 3 and 4 include TensorRT upscaling and RIFE frame interpolation for 48 fps high-resolution output.

    🖼️ Multi-Reference Input (image2)

    The QwenVL-Mod node has two image inputs:

    • T2VA: no images needed

    • I2VA: image = first frame

    • FL2VA: image = first frame, image2 = last frame, frame_count = 1

    • R2VA: image = primary reference, image2 = additional references (batch, up to 9), frame_count = 1–9

    Qwen3-VL sees all connected images as individual images (not as a video sequence), enabling proper multi-reference analysis for FL2VA and R2VA.

    🎯 QwenVL-Mod NSFW Presets (9 total)

    The workflows include built-in NSFW presets for the Qwen3-VL prompt enhancer:

    🎬 Base Presets (T2VA / I2VA)

    • 🎬 MiniMax H3 NSFW (5s) — 5 seconds — 3 fields: integrated_multimodal_description + overall_soundscape + non_diegetic_music

    • 🎬 MiniMax H3 NSFW (10s) — 10 seconds — Same format

    • 🎬 MiniMax H3 NSFW (15s) — 15 seconds — Same format

    🔄 FL2VA Presets (First-Last-Frame)

    • 🔄 MiniMax H3 NSFW FL2VA (5s) — 5 seconds — 3 fields, transition-focused (describes the path between frames)

    • 🔄 MiniMax H3 NSFW FL2VA (10s) — 10 seconds — Same format

    • 🔄 MiniMax H3 NSFW FL2VA (15s) — 15 seconds — Same format

    🎞️ R2VA Presets (Reference)

    • 🎞️ MiniMax H3 NSFW R2VA (5s) — 5 seconds — 6 fields: subject_definitions + summary + retention_analysis + detailed_description + overall_soundscape + non_diegetic_music

    • 🎞️ MiniMax H3 NSFW R2VA (10s) — 10 seconds — Same format

    • 🎞️ MiniMax H3 NSFW R2VA (15s) — 15 seconds — Same format

    What the presets produce

    • 🎬 Base: [Shot 1] with style + initial composition, camera vocabulary, speaker IDs, diegetic soundscape

    • 🔄 FL2VA: Describes the transition path between first and last frames (not the scene — images fix the scene). Favors single continuous shot.

    • 🎞️ R2VA: 6-section format with <Subject N>, <Picture N>, <Video N>, <Audio N> labels, retention markers (fully_preserved, partially_preserved, etc.), task-type summary

    • All presets: smooth, continuous camera motion (no abrupt or stepped changes), explicit diegetic soundscape, optional non-diegetic music (defaults to N/A)

    SFW presets are also available. Edit the preset dropdown in the QwenVL node to switch.

    🎮 Usage Examples

    Basic Text-to-Video (T2VA)

    1. Load MiniMaxH3-Turbo-T2VA-Qwen3.5.json

    2. Write your prompt in any language

    3. Select preset 🎬 MiniMax H3 NSFW (5s/10s/15s)

    4. Generate video with native audio

    Image-to-Video (I2VA)

    1. Load MiniMaxH3-Turbo-I2VA-Qwen3.5.json

    2. Upload your first-frame image to image

    3. Select preset 🎬 MiniMax H3 NSFW (5s/10s/15s)

    4. Write what happens next (in any language)

    5. Generate animated video with audio

    First-Last-Frame (FL2VA)

    1. Load MiniMaxH3-Turbo-FL2VA-Qwen3.5.json

    2. Upload first-frame to image, last-frame to image2, set frame_count=1

    3. Select preset 🔄 MiniMax H3 NSFW FL2VA (5s/10s/15s)

    4. Describe the transition between the two frames

    5. Generate the interpolated video at 48 fps with TensorRT upscale + RIFE

    Reference-to-Video (R2VA)

    1. Load MiniMaxH3-Turbo-R2VA-Qwen3.5.json

    2. Upload primary reference to image, additional references to image2 (batch), set frame_count to match

    3. Select preset 🎞️ MiniMax H3 NSFW R2VA (5s/10s/15s)

    4. Reference them by tag in your prompt: <Picture 1>, <Picture 2>, etc.

    5. Generate video with locked identity/style

    🔧 Technical Specifications

    ⚡ Performance

    • Output: 768p, 24 fps (native), up to ~15 seconds

    • Audio: Native stereo, generated jointly with video

    • Upscale: TensorRT RealESRGAN x4 (FL2VA + R2VA workflows)

    • Frame interpolation: RIFE v4.25 → 48 fps (FL2VA + R2VA workflows)

    • Sage Attention: FP16 accumulation, async offload

    • Smart caching: Reuse prompts with same inputs, Fixed Seed Mode for text-only caching

    🎨 Model Support

    • Qwen3-VL 4B: 7 GGUF variants (2.38 GB – 4.28 GB)

    • Qwen3-VL 8B: 7 GGUF variants (4.8 GB – 8.71 GB)

    • Qwen3.5: 4B / 9B / 27B (uncensored, heretic, unsloth) — thinking mode disabled

    • HF Models: Josiefed, official, Heretic-Stable variants

    • Quantization: Q4_K_S, Q5_K_S, FP16, INT8

    🌐 Multilingual Capabilities

    • Input languages: Any language supported

    • Auto-translation: Automatic translation to optimized English

    • Style detection: Works with multilingual prompts

    • Cultural adaptation: Context-aware prompt enhancement

    📦 Installation

    Quick Install

    1. Download: ComfyUI-QwenVL-Mod (latest version)

    2. Extract to ComfyUI/custom_nodes/ComfyUI-QwenVL-Mod

    3. Install requirements: pip install -r requirements.txt

    4. Restart ComfyUI

    5. Load included workflows from minimax/ folder

    Custom Nodes Required

    Note: ComfyMathExpression is built into ComfyUI core (v0.24.1+) — no custom node needed.

    Models Required

    T2VA / I2VA / FL2VA use the NVFP4 FL2VA model (Blackwell GPUs):

    • models/vae/ → minimax_h3_video_vae_fp16.safetensors (~5 GB)

    • models/vae/ → minimax_h3_audio_vae_fp32.safetensors (~0.6 GB)

    • models/diffusion_models/ → minimax_h3_fl2va_pruned_nvfp4_convrot_int8.safetensors (~20 GB) — lilcheaty/MiniMax-H3-NVFP4

    • models/text_encoders/ → qwen3vl_32b_heretic_minimax_h3_nvfp4.safetensors (~15.7 GB) — Momoking/Qwen3-VL-32B-Heretic-MiniMax-H3-NVFP4

    R2VA (ref2va) uses the NVFP4 Ref2VA model:

    Non-Blackwell GPUs: Use INT8 ConvRot models from Comfy-Org/MiniMax-H3 instead. NVFP4 requires sm_120+ (RTX 5090 / PRO 6000).

    10Eros-Max NVFP4 (optional/experimental)

    • models/diffusion_models/ → 10Eros_Max_H3_FL2VA-INT8-ConvRot-HQ.safetensors (~23.5 GB)

    • Pair it only with minimax_h3_fl2v_turbo_8step_v1.0_10ErosMax_beta1_pruned_compat_v001_T8.safetensors (~1.96 GB)

    • Switch both diffusion model and matching LoRA together; do not mix the standard and 10Eros LoRAs

    • The standard MiniMax H3 NVFP4+INT8 hybrid is the verified default. 10Eros-Max remains experimental; NVFP4 HQ degrades quality and audio on the 10Eros fine-tune, so INT8 ConvRot HQ is used instead

    Turbo LoRA (standard — all tasks)

    INT4 alternative (for 12-16 GB GPUs): Merserk/MiniMax-H3-INT4-ConvRot

    Qwen3-VL Prompt Enhancer

    • models/LLM/ → Qwen3-VL-8B-Heretic-Stable (GGUF or HF)

    TensorRT Engines (FL2VA + R2VA only)

    • models/upscale_models/ → RealESRGAN_x4 (TensorRT engine)

    • models/rife/ → rife425_ensemble_False_scale_1_sim (TensorRT engine, ONNX auto-downloaded from HF)

    TensorRT engines must be built for your specific GPU. See ComfyUI-RIFE-TensorRT-Auto and ComfyUI-Upscaler-TensorRT-Auto for build instructions.

    🎬 MiniMax H3 Prompting Notes

    How to Write Your Prompt

    Describe the scene naturally. Be clear about the concepts below — Qwen3-VL handles the rest:

    • 🎨 Visual style (put it first): photorealistic, cinematic, anime, 3D CG, claymation, vintage film, watercolor, fantasy

    • 👥 Subjects: number, gender, appearance, clothing, position, expression

    • 🏃 Action / motion: what happens, speed, interaction

    • 🎥 Camera: dolly, pan, zoom, static, handheld, crane, orbit — smooth and continuous (no abrupt changes)

    • 🌍 Environment: setting, lighting, atmosphere, time of day

    • 🔊 Audio (important!): dialogue, breaths, moans, skin contact, ambient sounds, music

    🔄 FL2VA: Describe the transition between frames, not the scene (images fix the scene) 🎞️ R2VA: Reference inputs by tag: <Picture 1>, <Picture 2>, <Video 1>, <Audio 1>

    Resolution Guidance

    MiniMax H3 native canvas: 768 px short edge, long edge capped at 1344 px, multiples of 32.

    • 📱 Portrait: 768×1344 · 896×1152 · 960×1280

    • ⬛ Square: 1024×1024

    • 🖥️ Landscape: 1344×768 · 1152×896 · 1280×960

    ⚠️ Match the aspect ratio to your input image! Forcing 16:9 on a portrait image will squash it.

    ⚠️ Avoid direct 1080p. Generate at native resolution, then upscale with TensorRT nodes (FL2VA + R2VA workflows).

    Duration

    Choose a preset: 5s / 10s / 15s. The Math Expression node snaps the frame count to the model's 17-frame-per-block grid (17k+5 at 24 fps).

    🐳 Docker / Cloud Ready

    OneClick RunPod Template

    Prefer a ready-to-go environment? Use the OneClick - ComfyUI - MiniMax H3 Turbo - Qwen3VL RunPod template:

    • Docker image: huchukato/comfyui-qwenvl-runpod:cu13-mmh3

    • Base: huchukato/comfyui-base:cu130

    • All custom nodes pre-installed

    • All 4 Turbo workflows auto-downloaded at boot

    • Models auto-downloaded at first boot (~81 GB including INT8 diffusion, NVFP4 text encoder, 10Eros INT8 HQ and Turbo LoRAs; persistent)

    • ComfyUI v0.34.2 baked into base image

    • Sage Attention, FP16 accumulation, async offload

    • TensorRT upscaling + RIFE interpolation (stable defaults: Upscaler 2/2, RIFE 1/1)

    • SOL-ATTN + Spectrum for Turbo workflows

    Access: ComfyUI :8188 · JupyterLab :8888 · FileBrowser :8080 (user admin / password adminadmin12) · SSH ssh root@pod-ip

    📖 README & instructions

    ComfyUI Args (pre-configured)

    --disable-auto-launch
--fast fp16_accumulation
--use-sage-attention
--reserve-vram 2
--cuda-malloc
--async-offload

    🚀 Why Choose ComfyUI-QwenVL-Mod + MiniMax H3?

    🎬 For Content Creators

    • Native audio: Video and audio in one pass — no separate MMAudio needed

    • Multilingual: Write in any language, Qwen3-VL handles translation

    • Professional: Official MiniMax H3 prompt format with camera vocabulary and speaker tags

    • Quality: 768p native, TensorRT upscale to higher resolution

    🔥 For NSFW Content

    • Explicit: Uncensored generation with dedicated NSFW presets

    • 9 presets: 3 base 🎬 + 3 FL2VA 🔄 + 3 R2VA 🎞️ — each tuned for its mode

    • Detailed: Rich scene descriptions with explicit diegetic soundscape

    • Natural: Realistic progression, consistent characters

    • Audio: Native moans, breaths, skin contact, ambient sounds

    ⚡ For Power Users

    • Customizable: Easy to modify presets and system prompts

    • Extendable: Add your own Qwen3-VL models (GGUF or HF)

    • Integrable: Works with existing ComfyUI setups

    • Optimized: Sage Attention, FP16, async offload, smart caching

    • Multi-reference: image2 input for FL2VA and R2VA workflows

    🌟 What Makes This Special?

    • First: Complete MiniMax H3 workflow pack with Qwen3-VL auto-prompting

    • Native audio: No separate audio node — MiniMax H3 does it all

    • 4 Turbo workflows: T2VA, I2VA, FL2VA, R2VA — covers all MiniMax H3 modes

    • Multi-reference: Qwen3-VL sees all connected images (not just the first)

    • TensorRT: Built-in upscaling and frame interpolation

    • 9 NSFW presets: Dedicated presets for each mode with correct prompt structure

    • Multilingual: Any input language, auto-translated and formatted

    • Ready: Works out-of-the-box with included workflows

    🎯 What's New in v2.6.0

    ⚡ NVFP4+INT8 ConvRot Hybrid — New Default

    • ✅ Default diffusion models: NVFP4+INT8 ConvRot hybrid (minimax_h3_fl2va_pruned_nvfp4_convrot_int8 / minimax_h3_ref2va_pruned_nvfp4_convrot_int8)

    • ✅ ~2.5x faster than pure INT8 ConvRot with identical visual quality on Blackwell

    • ✅ NVFP4 on MLP, INT8 ConvRot on attention, BF16 on sensitive layers (by rockerBOO/lilcheaty)

    • ✅ NVFP4 requires Blackwell GPUs (RTX 5090 / PRO 6000, sm_120+)

    • ✅ Pure INT8 ConvRot models still available for non-Blackwell GPUs

    🔧 SOL-ATTN + Spectrum Integration

    • ✅ All 4 Turbo workflows now include SOL-ATTN (Scheduled Sol Attention) for sharper output

    • ✅ All 4 Turbo workflows now include Spectrum adaptive smoothing (offline replay disabled for speed)

    • ✅ Turbo LoRA linked from preset to subgraph in all workflows

    ⚡ Turbo Step Standardization

    • ✅ All Turbo workflows standardized to 8 steps (was 6 for T2VA/R2VA)

    • ✅ Consistent minimax_h3_turbo_v4_step600_ema LoRA across all workflows

    📦 TensorRT Batch Size

    • ✅ Stable defaults: RIFE loader/runner 1/1, Upscaler loader/runner 2/2

    • ✅ Upscaler 2/2 verified on RTX PRO 6000 Blackwell

    • ⚠️ RIFE batch >1 currently fails during interpolation even when the engine builds; keep it at 1/1

    • ⚠️ Upscaler batch 4 fails to build with TensorRT 10.15 on Blackwell sm_120

    🧹 Cleanup

    • ✅ Removed was-node-suite from MiniMax Dockerfile (not used by MiniMax workflows)

    • ✅ Removed ComfyUI-Frame-Interpolation from MiniMax (uses RIFE TensorRT instead)

    • ✅ Removed KJNodes from provisioning (baked into RunPod base image)

    • ✅ ComfyMathExpression is built into ComfyUI core — no custom node needed

    🧠 Qwen3.5 Thinking Fix

    • ✅ /no_think prefix for Qwen3.5 models (enable_thinking deprecated in recent llama.cpp)

    • ✅ Broadened architecture detection (qwen35, qwen35moe, qwen35_vl)

    • ✅ Works across both HF and GGUF nodes

    📦 Workflow Organization

    • ✅ Moved workflows to minimax/ folder

    • ✅ Renamed FLF to FL2VA (clearer naming)

    • ✅ Added Civitai documentation

    📋 Credits

    📄 License

    Workflows are released under the same license as the underlying models and custom nodes. See each repository for details.

    MiniMax H3 model weights: Comfy-Org/MiniMax-H3 — MiniMax H3 Community License.

    Built with ❤️ for the ComfyUI community

    Description

    FAQ

    ComfyWorkflows
    MiniMax H3
    by huchukato
    Download (Beta) View on CivitAI
    minimax
    nsfw
    autoprompt
    t2va
    i2va
    character

    Details

    Downloads
    36
    Platform
    CivitAI
    Platform Status
    Available
    Created
    9/8/2026
    Updated
    9/11/2026
    Deleted
    -

    Files

    MinimaxH3NSFWI2VAT2VAFL2VAR2VAWorkflowsQwen35_OneclickFL2VALoop.zip

    Size:
    25.96 KB
    SHA256:
    9a6dc0c1f8a20ce2f51b58f0756937dc7bf2f78fd0643b772d6cce9afa2d0557

    Mirrors

    CivitAI (1 mirrors)