ComfyUI Node
Hunyuan Instruct Multi-Image Fusion
A ComfyUI node in Hunyuan/Instruct with 16 inputs and 3 outputs.
Hunyuan Instruct Multi-Image Fusion
- model
- image_1
- image_2
- image_3
- image_4
- image_5
- image
- cot_reasoning
- status
◄instructionCombine the style of image 1 with elements from image 2►
◄seed-1►
◄bot_taskimage►
◄system_promptdynamic►
◄resolution1024x1024 (1:1 Square)►
◄steps-1►
◄guidance_scale-1.0►
◄flow_shift2.80►
◄max_new_tokens2048►
◄verbose0►
CategoryHunyuan/Instruct
Inputs (16)
| Name | Type | Default | Description |
|---|---|---|---|
| model | HUNYUAN_INSTRUCT_MODEL | — | |
| image_1 | IMAGE | — | |
| instruction | STRING | Combine the style of image 1 with elements from image 2 | Instruction describing how to combine the images. Reference images as 'image 1', 'image 2', 'image 3', etc. Examples: 'Based on image 1 logo, create a fridge magnet with image 2 material', 'Let the cat from image 1 take a selfie with the cat from image 2, with image 3 as background'. Works with both English and Chinese prompts. |
| seed | INT | -1-1–2147483647 | -1 for random seed |
| image_2opt | IMAGE | — | |
| image_3opt | IMAGE | — | |
| image_4opt | IMAGE | Experimental — model officially supports up to 3, but the pipeline accepts more. Increases VRAM usage significantly. | |
| image_5opt | IMAGE | Experimental — model officially supports up to 3, but the pipeline accepts more. Increases VRAM usage significantly. | |
| bot_taskopt | COMBO | image | Controls how the model processes your fusion instruction.\n• image: Direct fusion — instruction applied as-is.\n• recaption: Rewrites instruction into detailed fusion description then generates.\n• think_recaption: (BEST) CoT reasoning about how to combine elements, rewrites instruction, then generates. Recommended for complex multi-image fusion. |
| system_promptopt | COMBO | dynamic | System prompt guiding multi-image fusion. dynamic (recommended) auto-selects the best prompt for your bot_task. en_unified includes reference editing guidelines for extracting and combining elements across images. The model understands both English and Chinese instructions. |
| resolutionopt | COMBO | 1024x1024 (1:1 Square) | Output image resolution. Auto lets the model predict aspect ratio (often unpredictable with multiple input images of different sizes). Selecting a specific resolution gives deterministic output dimensions. |
| stepsopt | INT | -1-1–100 | -1 for auto (8 for Distil, 50 for full Instruct). Higher step counts (60–80) reduce flow-matching artifacts at 2K+ resolutions but generation time scales linearly. |
| guidance_scaleopt | FLOAT | -1.0-1–20 | CFG scale. -1 = auto (model's recommended value, typically 2.5) |
| flow_shiftopt | FLOAT | 2.800–10 | Flow shift for the diffusion scheduler. Controls denoising schedule shape. Default 2.8 is balanced. Presets: Portraits / faces: 2.0–2.5 (sharper detail). Landscapes / illustrations: 3.5–5.0 (cleaner gradients). |
| max_new_tokensopt | INT | 2048256–8192 | Maximum tokens for CoT reasoning and instruction rewriting. Only used with recaption or think_recaption modes. Multi-image fusion may benefit from higher values (e.g. 3072) for complex instructions. |
| verboseopt | INT | 00–2 | Verbosity level. 0=silent (recommended), 1=info (shows full system prompt), 2=debug |
Outputs (3)
| Name | Type | Description |
|---|---|---|
| image | IMAGE | — |
| cot_reasoning | STRING | — |
| status | STRING | — |