Merge master into worksplit-multigpu#13546
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Kosinkadink merged 30 commits intoworksplit-multigpufrom Apr 24, 2026
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…model (#13330) * feat(api nodes): added 4K resolution for Veo models; added Veo 3 Lite model Signed-off-by: bigcat88 <bigcat88@icloud.com> * increase poll_interval from 5 to 9 --------- Signed-off-by: bigcat88 <bigcat88@icloud.com> Co-authored-by: Jedrzej Kosinski <kosinkadink1@gmail.com>
…ionNode (#13504) The tooltip on the resolution input states that 4K is not available for veo-3.1-lite or veo-3.0 models, but the execute guard only rejected the lite combination. Selecting 4K with veo-3.0-generate-001 or veo-3.0-fast-generate-001 would fall through and hit the upstream API with an invalid request. Broaden the guard to match the documented behavior and update the error message accordingly. Co-authored-by: Jedrzej Kosinski <kosinkadink1@gmail.com>
* initial RIFE support * Also support FILM * Better RAM usage, reduce FILM VRAM peak * Add model folder placeholder * Fix oom fallback frame loss * Remove torch.compile for now * Rename model input * Shorter input type name ---------
fixes #13492) (#13518) On Windows with aimdo enabled, disable_weight_init.Linear uses lazy initialization that sets weight and bias to None to avoid unnecessary memory allocation. This caused a crash when copy_() was called on the None weight attribute in Stable_Zero123.__init__. Replace copy_() with direct torch.nn.Parameter assignment, which works correctly on both Windows (aimdo enabled) and other platforms.
the mixed_precision ops can have input_scale parameters that are used in tensor math but arent a weight or bias so dont get proper VRAM management. Treat these as force-castable parameters like the non comfy weight, random params are buffers already are.
* feat(api-nodes): add SD2 real human support Signed-off-by: bigcat88 <bigcat88@icloud.com> * fix: add validation before uploading Assets Signed-off-by: bigcat88 <bigcat88@icloud.com> * Add asset_id and group_id displaying on the node Signed-off-by: bigcat88 <bigcat88@icloud.com> * extend poll_op to use instead of custom async cycle Signed-off-by: bigcat88 <bigcat88@icloud.com> * added the polling for the "Active" status after asset creation Signed-off-by: bigcat88 <bigcat88@icloud.com> * updated tooltip for group_id * allow usage of real human in the ByteDance2FirstLastFrame node * add reference count limits * corrected price in status when input assets contain video Signed-off-by: bigcat88 <bigcat88@icloud.com> --------- Signed-off-by: bigcat88 <bigcat88@icloud.com>
* fix(api-nodes): fixed price badges, add new resolutions Signed-off-by: bigcat88 <bigcat88@icloud.com> * proper calculate the total run cost when "n > 1" Signed-off-by: bigcat88 <bigcat88@icloud.com> --------- Signed-off-by: bigcat88 <bigcat88@icloud.com>
Signed-off-by: bigcat88 <bigcat88@icloud.com>
This was doing an over-estimate of VRAM used by the async allocator when lots of little small tensors were in play. Also change the versioning scheme to == so we can roll forward aimdo without worrying about stable regressions downstream in comfyUI core.
Causes Nans
Currently if the graph contains a cycle, the just inifitiate recursions, hits a catch all then throws a generic error against the output node that seeded the validation. Instead, fail the offending cycling mode chain and handlng it as an error in its own right. Co-authored-by: guill <jacob.e.segal@gmail.com>
…orksplit-multigpu Amp-Thread-ID: https://ampcode.com/threads/T-019dbce6-507d-700f-a488-68919459c9ca Co-authored-by: Amp <amp@ampcode.com> # Conflicts: # requirements.txt
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Merge latest master changes into worksplit-multigpu. Conflict in requirements.txt resolved keeping ours (comfy-aimdo==0.0.214).
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If Need pricing update:
QA
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