UNI-1 Max

UNI-1 Max is the answer to the question everyone asks after a good-but-not-great UNI-1 render: "can it do better?" It's the higher tier of Luma's image model, same interface, same web-search trick, more of whatever the base model was holding back. In the hosted-model world "more" usually means resolution headroom and detail budget, and "Max" is where you spend it when the composition finally works.

Like its base sibling, it's a closed Luma model rented per generation through Runware's cloud in the ComfyUI-Runware pack. The local community's verdict on closed hosted image models is short and unflattering - "not local, not open source" - but if you're already in this pack, that ship has sailed. The question is which tier to queue, and Max is the tier for the keeper shot, not the first draft.

How it works

Same mechanism as every node here: model AIR luma:uni@1-max, imageInference task, REST request through the runware-sdk, native IMAGE output. Inputs mirror UNI-1 exactly:

• positivePrompt - required.
• seedImage / referenceImages - IMAGE conditioning sockets.
• settings.search - web search for visual references before generating; use it for real-world subjects, landmarks, products.
• settings.style - preset, default auto.
• width / height - 1024; numberResults 1–4; watermark socket optional.

The output

One image socket, type IMAGE, into Preview Image or Save Image.

Installing it

The pack install covers every node, once:

cd ComfyUI/custom_nodes
git clone https://github.com/Runware/ComfyUI-Runware
pip install -r ComfyUI-Runware/requirements.txt

Restart, set your key via ComfyUI Settings → Runware API key, RUNWARE_API_KEY, or runware auth login.

Where people get burned

The tier's entire value proposition is "pay more for more," so the honest advice is: don't start here. Run the idea through Runware_luma_uni_1 to lock the composition, then re-queue the winner on Max - otherwise you're paying Max prices for prompt roulette. And remember the meter is the real user interface for hosted models: the node prints cost per run, and numberResults is the quiet way to triple that bill. If the extra spend isn't visibly buying detail, drop back to base and save the credits.