Conditioning (Combine) and (Concat) node in ComfyUI
Conditioning (Combine) merges two conditionings so the sampler is guided by both at once; Conditioning (Concat) joins the token sequences into one longer prompt. Related nodes set area, mask and timestep ranges.
Node pack: ComfyUI core
Category: Conditioning and prompts
What Conditioning (Combine) and (Concat) does
ComfyUI treats prompts as data, so they can be mixed after encoding. Conditioning (Combine) takes two CONDITIONING inputs and outputs a list containing both; the sampler evaluates each and averages the guidance, which blends two ideas (for example two styles) more evenly than writing them in one prompt. Conditioning (Concat) appends the second prompt tokens to the first, which behaves like a long single prompt.
The same family includes Conditioning (Average) with a weight slider, Conditioning (Set Area) and (Set Mask) to apply a prompt only to a region, and ConditioningSetTimestepRange to apply a prompt only during part of the sampling. Together they make regional prompting and prompt scheduling possible without custom nodes.
Inputs
Name | Type | What it is |
|---|---|---|
conditioning_1 | CONDITIONING | First encoded prompt. |
conditioning_2 | CONDITIONING | Second encoded prompt (Concat: appended; Combine: evaluated alongside). |
Outputs
Name | Type | What it is |
|---|---|---|
CONDITIONING | CONDITIONING | The merged conditioning for the sampler positive or negative input. |
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How to use Conditioning (Combine) and (Concat)
- Encode two prompts with two CLIP Text Encode nodes.
- Feed both into Conditioning (Combine) or (Concat).
- Connect the output to the KSampler positive input.
- For a region, pass one prompt through Conditioning (Set Mask) with a MASK first, then combine with the full-image prompt.
Settings and tips
- Combine doubles the sampler work per step for the positive side; Concat does not.
- Set Area with strength 1.0 and set_cond_area "default" is the classic two-subjects-left-and-right technique.
- Use ConditioningSetTimestepRange 0.0-0.3 for a composition prompt and 0.3-1.0 for a detail prompt.
- Conditioning (Average) with conditioning_to_strength 0.5 gives a true midpoint between two prompts.
Troubleshooting Conditioning (Combine) and (Concat)
Subjects bleed into each other with Set Area or Set Mask
Why it happens
The regional prompts overlap or there is no general prompt covering the whole canvas, so the model fills gaps from either region.
How to fix it
Add a third, general prompt for the whole image, combine all three, and keep the regions from overlapping. Lower the regional strength to 0.8.
Error: cond shapes do not match when using Concat
Why it happens
The two prompts come from different text encoders (for example SD 1.5 CLIP and SDXL CLIP) or one includes pooled output the other lacks.
How to fix it
Encode both prompts with the same CLIP object from the same loader.
Nothing changes when combining
Why it happens
Both inputs are the same conditioning, or the combined output is not the one wired into the sampler.
How to fix it
Check the wire into KSampler positive comes from the combine node and that the two inputs differ.
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Questions about Conditioning (Combine) and (Concat)
Combine or Concat for two styles?
Combine blends two separately evaluated guidances; Concat is like a longer prompt. Try Combine first for styles, Concat for added detail words.
Can I do this on the negative side?
Yes, all conditioning nodes work for negative prompts too.
Related nodes
CLIP Text Encode (Prompt)
ComfyUI core
CLIP Text Encode turns a text prompt into CONDITIONING using the model text encoder. One node holds the positive prompt, a second one the negative prompt.
KSampler
ComfyUI core
KSampler runs the denoising loop: it takes the model, prompts and a latent and produces the finished latent image, controlled by seed, steps, cfg, sampler, scheduler and denoise.
Load Image (as Mask)
ComfyUI core
Load Image (as Mask) turns one channel of a picture (alpha, red, green or blue) into a MASK, so black-and-white mask files or painted layers can drive inpainting and compositing.
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Load Checkpoint
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Load Checkpoint (CheckpointLoaderSimple) opens a .safetensors or .ckpt model file and hands out the three parts every workflow needs: the diffusion MODEL, the CLIP text encoder and the VAE.
Save Image
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Save Image writes the IMAGE tensor to ComfyUI/output as a PNG, with the whole workflow embedded in the file metadata so the picture can be dragged back into ComfyUI to restore the graph.
VAE Decode
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VAE Decode converts the sampled LATENT into a pixel IMAGE with the VAE; VAE Decode (Tiled) does the same in tiles for very large images.
Empty Latent Image
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Empty Latent Image creates the blank latent canvas (width, height, batch_size) that text-to-image sampling starts from; dimensions must be multiples of 8 and match the model family.
Load Image
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Load Image reads a picture from the ComfyUI input folder (or an upload) and outputs an IMAGE tensor plus a MASK taken from the alpha channel, the starting point for img2img, inpainting, ControlNet and IP-Adapter graphs.
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