Multi Images Input

Most ComfyUI nodes that touch images are built around exactly one IMAGE tensor at a time. That's fine until you want a vision model to look at several pictures together - a before/after pair, a stack of scanned pages, a photo set you want compared side by side. MultiImagesInput exists for exactly that gap: it's the adapter that turns a handful of separate image inputs into one batch, so the Pixtral Large node (which only exposes a single images slot) can actually use them.

It ships in ShmuelRonen's ComfyUI Pixtral Large Extension, a small three-node pack that wraps Mistral AI's Pixtral Large vision model. Worth knowing up front: ShmuelRonen isn't a random one-off repo author - he's better known for ComfyUI-LatentSyncWrapper, a lip-sync wrapper that shows up in workflow-share threads with real traction (one post walking through it pulled 238 upvotes on r/comfyui). This Pixtral pack doesn't see anywhere near that volume, but it's the same "wrap an external model in clean nodes" habit from someone who's done it before.

Why it exists, mechanically

Pixtral Large is a 124B-parameter model (123B decoder, 1B vision encoder) with a 128K context window, and it can reason across up to 30 high-resolution images in a single request - compare two product photos, read a multi-page document, walk a sequence of frames in order. ComfyUI's Load Image node hands you one image per node instance, though, and there's no built-in way to bundle several into one input. MultiImagesInput is that bundler: connect as many image sources as you need into its slots, and it concatenates them into a single batch tensor for the main node to send upstream.

How it works

It's a dynamic-input node - the same pattern you've probably seen on other "combine N things" nodes. It starts with two slots, image_1 and image_2, controlled by a required inputcount widget (default 2, range 2–30). Raise inputcount and hit the node's update control, and it grows more image_N slots to match. Wire a Load Image (or anything that outputs IMAGE) into each slot, and the single images output is the whole set stacked into a batch.

Inputs and outputs that matter

• inputcount (2–30, default 2) - the only widget you set directly. Everything past this is just plugging images into the slots it creates.
• image_1, image_2, … - one IMAGE input per slot.
• Output: images (IMAGE) - the batched result. Wire it straight into Pixtral Large's images input.

How to install it

Search "ComfyUI Pixtral Large Extension" in ComfyUI Manager and install from there, or do it by hand:

cd ComfyUI/custom_nodes
git clone https://github.com/ShmuelRonen/ComfyUI_pixtral_large.git

Restart ComfyUI afterward. There's nothing to download for this node specifically - the vision model itself lives on Mistral's servers, not on your disk, so the only setup that actually matters happens on the Pixtral Large node (the API key).

Common issues & troubleshooting

The pack's own README lists three failure modes for this node, and they line up cleanly with how it's meant to be used:

• "At least 2 images are required" - inputcount bottoms out at 2 on purpose. If you genuinely have one image, skip this node and connect Load Image straight into Pixtral Large.
• "Exceeded maximum image count" - you've gone past 30. That's Pixtral Large's actual context ceiling, not an arbitrary limit here, so trim the set instead of trying to raise inputcount further.
• "Invalid image format" - one of the connected slots isn't a normal ComfyUI IMAGE tensor. This usually traces back to something odd upstream (a mask output, an unconventional loader) rather than the batching node itself.

Beyond those three, the practical thing to know before you build a big document-analysis graph around this: every image you add is another thing that has to decode correctly, and a bigger batch means a heavier, slower call once it hits Pixtral Large. If you're testing a new multi-page workflow, start with two or three images and confirm the round trip works before wiring up thirty.