Kling v3 Omni (BudgetPixel)
Nine-reference composition that goes to 4K
- reference_images
- images
Kling v3 Omni is the Kling image family's answer to "what if we could hold a whole character sheet at once?" It's a unified text-to-image and image-editing node with multi-reference composition from up to nine reference images and output that goes up to 4K. In the BudgetPixel image lineup that puts it in the same heavy-lifting company as GPT-Image-2 and FLUX 2 Dev - the nodes you reach for when a single reference isn't enough to pin down who, what, and where.
The pricing is where Omni gets interesting: 35 credits per image at 1K/2K, and 60 at 4K. The 4K step-up is only 25 credits over the 2K price - proportionally tiny compared to the video shelf - which makes the 4K tier genuinely tempting. "Omni" is the pitch: one node that does generation and editing with serious reference capacity, without the billing matrix complexity of the OpenAI or Grok 2.0 nodes.
How it works
Standard BudgetPixel image flow: POST your prompt and reference batch into the Kling image pipeline, poll /images/{id}, download the IMAGE batch. The reference handling is the star - batches you wire into the reference_images input map onto the model's reference slots automatically, so a batch of nine images becomes nine composition anchors with zero extra wiring. That's the same pattern as FLUX 2 Dev but with more than double the reference capacity.
The inputs that matter
- prompt - required, multiline. With references attached, this is the composition instruction: "image 1 is the subject, image 2 the outfit, image 3 the location…"
- reference_images - up to 9. The node's whole reason to exist.
- size - 1K / 2K / 4K. The 4K tier is only 60 credits - the cheapest high-res path in the pack's image lineup.
- aspect_ratio - framing.
- num_images - 1–4, default 1 (each billed at the tier's rate).
- seed - default -1 (random).
Output is images (IMAGE batch).
Install
Manager (search "BudgetPixel") or:
cd ComfyUI/custom_nodes
git clone https://github.com/budgetpixel-ai/comfyui-budgetpixel.git
pip install -r comfyui-budgetpixel/requirements.txt
Restart, set BUDGETPIXEL_API_KEY or budgetpixel.json ({"api_key": "bpx_live_..."}) in the pack folder. No model files; requests is the only dependency.
Where people get burned
Reference hygiene is everything at nine slots. Feeding it nine images that conflict - different people, different lighting, contradictory styles - produces a muddle, and the 35-60 credits you spent aren't coming back. Curate the batch like it's a casting call. Second, remember this is Kling's image model despite the Kling video brand - if you came here expecting video, the video Kling nodes are in the BudgetPixel/Video category. Third, the 4K tier's cheap price can lead to overshooting: a 4K Omni render is slower server-side and heavier downstream, so use 4K when you'll actually use the resolution, not because it's only 25 credits more. And when you re-test, flip force_rerun so the cache doesn't hand you yesterday's image.
Inputs (6)
| Name | Type | Default | Description |
|---|---|---|---|
| prompt | STRING | Text description of the image to generate. | |
| aspect_ratioopt | COMBO | 1:1 | Output aspect ratio. |
| num_imagesopt | INT | 11–4 | Number of images to generate. |
| reference_imagesopt | IMAGE | Optional reference images (up to 9) for image editing and multi-reference composition. Each item is a public image URL, a data URI, raw base64, or an uploaded-file URL from POST /v1/uploads. Omit for text-to-image. | |
| sizeopt | COMBO | 2K | Output resolution tier. 1K/2K bill 35 credits per image; 4K bills 60. |
| force_rerunopt | BOOLEAN | false | — |
Outputs (1)
| Name | Type | Description |
|---|---|---|
| images | IMAGE | — |