(Down)Load SHARP Model

This is node one of every SHARP graph, and the parenthetical in its name is the whole point: it's not a normal checkpoint loader pointing at a file you already have, it's a "download this if you don't, then load it" node. Wire it up, hit run, and it fetches the weights for you the first time.

SHARP itself is worth knowing what you're loading. It's a model Apple open-sourced (arXiv 2512.10685) that turns a single ordinary photo into a set of 3D Gaussians - a point cloud you can view from other angles - in well under a second of actual inference. This pack (ComfyUI-Sharp, by PozzettiAndrea, who posts as u/ant_drinker) wraps it for ComfyUI. If you're used to SD/Flux nodes, recalibrate: this isn't image generation, it's monocular 3D reconstruction. Same "one photo in" simplicity, completely different output.

How it works

There's no model-selection dropdown here because there's only one model to load. On first run the node downloads sharp_2572gikvuh.pt straight into ComfyUI/models/sharp/ and loads it from there; on every run after that it just loads the cached file. If you're setting up an offline box, grab that file ahead of time and drop it in that folder yourself - the node will find it and skip the download.

The only real decision is precision. Leave it on auto unless you have a specific reason not to - it already picks bf16 on Ampere-and-newer, fp16 on Volta/Turing, and fp32 on anything older, which is exactly the choice you'd make by hand anyway.

The inputs and output that matter

There are no required inputs at all. The one optional field:

• precision (default auto) - model dtype. auto matches precision to your GPU generation; only override it if you're deliberately forcing fp32 for a compatibility test or similar.

The single output, model_config (SHARP_MODEL_CONFIG), plugs into the model input of every Predict node in the pack - SharpPredict, SharpPredictForeground, SharpPredictDepth, SharpPredictMetricDepth, SharpPredictGaussianAttrs, SharpPredictGaussiansFromMetricDepth. One loader, every downstream node shares it.

Installing it

Three ways, README's own ranking, fastest to most reliable:

1. ComfyUI Manager - search "Sharp", install the highest version shown; if that build misbehaves, try nightly.
2. Manager → Install via Git URL - https://github.com/PozzettiAndrea/ComfyUI-Sharp.git.
3. Manual: cd ComfyUI/custom_nodes && git clone https://github.com/PozzettiAndrea/ComfyUI-Sharp.git, then inside that folder pip install -r requirements.txt --upgrade and python install.py, then restart.

One heads-up straight from the README: install optionally uses an experimental package called comfy-env, which pulls in the pixi package manager to attempt a one-click isolated install. If your install hangs or behaves oddly, that's the moving part to suspect first.

Common issues

The clearest documented failure mode, straight from the pack's release thread: people on 8GB VRAM cards reported the app either OOMing outright or, in one case, just hanging at startup with no error message at all - which is consistent with the download-and-load step choking on a card that's genuinely too small for it. If your ComfyUI server seems to freeze right around when this node should be doing its thing, that's the first thing to rule out, not a broken install.

If the model download itself fails (corporate firewall, flaky connection, whatever), don't fight it through the node - just download sharp_2572gikvuh.pt separately and place it in ComfyUI/models/sharp/ by hand, then re-run.

And if you hit something genuinely weird, the author is unusually responsive: he asks people to open a GitHub Discussion or Issue and offers to dig through install/inference logs directly. Worth taking him up on it rather than guessing - this is a young pack (first released December 2025) and edge cases are still being found.