1863 Commits

Author	SHA1	Message	Date
comfyanonymous	5ac3b26a7d	Update warning for old pytorch version. (#11319) ... Versions below 2.4 are no longer supported. We will not break support on purpose but will not fix it if we do.	2025-12-14 04:02:50 -05:00
chaObserv	6592bffc60	seeds_2: add phi_2 variant and sampler node (#11309) ... * Add phi_2 solver type to seeds_2 * Add sampler node of seeds_2	2025-12-14 00:03:29 -05:00
comfyanonymous	971cefe7d4	Fix pytorch warnings. (#11314)	2025-12-13 18:45:23 -05:00
comfyanonymous	da2bfb5b0a	Basic implementation of z image fun control union 2.0 (#11304) ... The inpaint part is currently missing and will be implemented later. I think they messed up this model pretty bad. They added some control_noise_refiner blocks but don't actually use them. There is a typo in their code so instead of doing control_noise_refiner -> control_layers it runs the whole control_layers twice. Unfortunately they trained with this typo so the model works but is kind of slow and would probably perform a lot better if they corrected their code and trained it again.	2025-12-13 01:39:11 -05:00
comfyanonymous	c5a47a1692	Fix bias dtype issue in mixed ops. (#11293)	2025-12-12 11:49:35 -05:00
comfyanonymous	5495589db3	Respect the dtype the op was initialized in for non quant mixed op. (#11282)	2025-12-11 23:32:27 -05:00
comfyanonymous	eeb020b9b7	Better chroma radiance and other models vram estimation. (#11278)	2025-12-11 17:33:09 -05:00
comfyanonymous	ae65433a60	This only works on radiance. (#11277)	2025-12-11 17:15:00 -05:00
comfyanonymous	fdebe18296	Fix regular chroma radiance (#11276)	2025-12-11 17:09:35 -05:00
comfyanonymous	f8321eb57b	Adjust memory usage factor. (#11257)	2025-12-11 01:30:31 -05:00
Farshore	e711aaf1a7	Lower VAE loading requirements：Create a new branch for GPU memory calculations in qwen-image vae (#11199)	2025-12-10 22:02:26 -05:00
comfyanonymous	17c92a9f28	Tweak Z Image memory estimation. (#11254)	2025-12-10 19:59:48 -05:00
comfyanonymous	791e30ff50	Fix nan issue when quantizing fp16 tensor. (#11213)	2025-12-09 17:03:21 -05:00
Jukka Seppänen	e2a800e7ef	Fix for HunyuanVideo1.5 meanflow distil (#11212)	2025-12-09 16:59:16 -05:00
rattus	9d252f3b70	ops: delete dead code (#11204) ... This became dead code in https://github.com/comfyanonymous/ComfyUI/pull/11069	2025-12-09 00:55:13 -05:00
Lodestone	b9fb542703	add chroma-radiance-x0 mode (#11197)	2025-12-08 23:33:29 -05:00
rattus	e136b6dbb0	dequantization offload accounting (fixes Flux2 OOMs - incl TEs) (#11171) ... * make setattr safe for non existent attributes Handle the case where the attribute doesnt exist by returning a static sentinel (distinct from None). If the sentinel is passed in as the set value, del the attr. * Account for dequantization and type-casts in offload costs When measuring the cost of offload, identify weights that need a type change or dequantization and add the size of the conversion result to the offload cost. This is mutually exclusive with lowvram patches which already has a large conservative estimate and wont overlap the dequant cost so\ dont double count. * Set the compute type on CLIP MPs So that the loader can know the size of weights for dequant accounting.	2025-12-08 23:21:31 -05:00
comfyanonymous	d50f342c90	Fix potential issue. (#11201)	2025-12-08 23:20:04 -05:00
comfyanonymous	3b0368aa34	Fix regression. (#11194)	2025-12-08 17:38:36 -05:00
rattus	60ee574748	retune lowVramPatch VRAM accounting (#11173) ... In the lowvram case, this now does its math in the model dtype in the post de-quantization domain. Account for that. The patching was also put back on the compute stream getting it off-peak so relax the MATH_FACTOR to only x2 so get out of the worst-case assumption of everything peaking at once.	2025-12-08 15:18:06 -05:00
dxqb	8e889c535d	Support "transformer." LoRA prefix for Z-Image (#11135)	2025-12-08 15:17:26 -05:00
comfyanonymous	56fa7dbe38	Properly load the newbie diffusion model. (#11172) ... There is still one of the text encoders missing and I didn't actually test it.	2025-12-07 07:44:55 -05:00
comfyanonymous	329480da5a	Fix qwen scaled fp8 not working with kandinsky. Make basic t2i wf work. (#11162)	2025-12-06 17:50:10 -08:00
rattus	4086acf3c2	Fix on-load VRAM OOM (#11144) ... slow down the CPU on model load to not run ahead. This fixes a VRAM on flux 2 load. I went to try and debug this with the memory trace pickles, which needs --disable-cuda-malloc which made the bug go away. So I tried this synchronize and it worked. The has some very complex interactions with the cuda malloc async and I dont have solid theory on this one yet. Still debugging but this gets us over the OOM for the moment.	2025-12-06 18:42:09 -05:00
comfyanonymous	50ca97e776	Speed up lora compute and lower memory usage by doing it in fp16. (#11161)	2025-12-06 18:36:20 -05:00
comfyanonymous	ae676ed105	Fix regression. (#11137)	2025-12-05 23:01:19 -05:00
Jukka Seppänen	fd109325db	Kandinsky5 model support (#10988) ... * Add Kandinsky5 model support lite and pro T2V tested to work * Update kandinsky5.py * Fix fp8 * Fix fp8_scaled text encoder * Add transformer_options for attention * Code cleanup, optimizations, use fp32 for all layers originally at fp32 * ImageToVideo -node * Fix I2V, add necessary latent post process nodes * Support text to image model * Support block replace patches (SLG mostly) * Support official LoRAs * Don't scale RoPE for lite model as that just doesn't work... * Update supported_models.py * Rever RoPE scaling to simpler one * Fix typo * Handle latent dim difference for image model in the VAE instead * Add node to use different prompts for clip_l and qwen25_7b * Reduce peak VRAM usage a bit * Further reduce peak VRAM consumption by chunking ffn * Update chunking * Update memory_usage_factor * Code cleanup, don't force the fp32 layers as it has minimal effect * Allow for stronger changes with first frames normalization Default values are too weak for any meaningful changes, these should probably be exposed as advanced node options when that's available. * Add image model's own chat template, remove unused image2video template * Remove hard error in ReplaceVideoLatentFrames -node * Update kandinsky5.py * Update supported_models.py * Fix typos in prompt template They were now fixed in the original repository as well * Update ReplaceVideoLatentFrames Add tooltips Make source optional Better handle negative index * Rename NormalizeVideoLatentFrames -node For bit better clarity what it does * Fix NormalizeVideoLatentStart node out on non-op	2025-12-05 22:20:22 -05:00
comfyanonymous	092ee8a500	Fix some custom nodes. (#11134)	2025-12-05 18:25:31 -05:00
Jukka Seppänen	79d17ba233	Context windows fixes and features (#10975) ... * Apply cond slice fix * Add FreeNoise * Update context_windows.py * Add option to retain condition by indexes for each window This allows for example Wan/HunyuanVideo image to video to "work" by using the initial start frame for each window, otherwise windows beyond first will be pure T2V generations. * Update context_windows.py * Allow splitting multiple conds into different windows * Add handling for audio_embed * whitespace * Allow freenoise to work on other dims, handle 4D batch timestep Refactor Freenoise function. And fix batch handling as timesteps seem to be expanded to batch size now. * Disable experimental options for now So that the Freenoise and bugfixes can be merged first --------- Co-authored-by: Jedrzej Kosinski <kosinkadink1@gmail.com> Co-authored-by: ozbayb <17261091+ozbayb@users.noreply.github.com>	2025-12-05 12:42:46 -08:00
comfyanonymous	6fd463aec9	Fix regression when text encoder loaded directly on GPU. (#11129)	2025-12-05 15:33:16 -05:00
comfyanonymous	43071e3de3	Make old scaled fp8 format use the new mixed quant ops system. (#11000)	2025-12-05 14:35:42 -05:00
Jedrzej Kosinski	0ec05b1481	Remove line made unnecessary (and wrong) after transformer_options was added to NextDiT's _forward definition (#11118)	2025-12-05 14:05:38 -05:00
rattus	9bc893c5bb	sd: bump HY1.5 VAE estimate (#11107) ... Im able to push vram above estimate on partial unload. Bump the estimate. This is experimentally determined with a 720P and 480P datapoint calibrating for 24GB VRAM total.	2025-12-04 09:50:36 -08:00
rattus	f4bdf5f830	sd: revise hy VAE VRAM (#11105) ... This was recently collapsed down to rolling VAE through temporal. Clamp The time dimension.	2025-12-04 09:50:04 -08:00
rattus	6be85c7920	mp: use look-ahead actuals for stream offload VRAM calculation (#11096) ... TIL that the WAN TE has a 2GB weight followed by 16MB as the next size down. This means that team 8GB VRAM would fully offload the TE in async offload mode as it just multiplied this giant size my the num streams. Do the more complex logic of summing up the upcoming to-load weight sizes to avoid triple counting this massive weight. partial unload does the converse of recording the NS most recent unloads as they go.	2025-12-03 23:28:44 -05:00
comfyanonymous	ea17add3c6	Fix case where text encoders where running on the CPU instead of GPU. (#11095)	2025-12-03 23:15:15 -05:00
rattus	519c941165	Prs/lora reservations (reduce massive Lora reservations especially on Flux2) (#11069) ... * mp: only count the offload cost of math once This was previously bundling the combined weight storage and computation cost * ops: put all post async transfer compute on the main stream Some models have massive weights that need either complex dequantization or lora patching. Don't do these patchings on the offload stream, instead do them on the main stream to syncrhonize the potentially large vram spikes for these compute processes. This avoids having to assume a worst case scenario of multiple offload streams all spiking VRAM is parallel with whatever the main stream is doing.	2025-12-03 02:28:45 -05:00
rattus	73f5649196	Implement temporal rolling VAE (Major VRAM reductions in Hunyuan and Kandinsky) (#10995) ... * hunyuan upsampler: rework imports Remove the transitive import of VideoConv3d and Resnet and takes these from actual implementation source. * model: remove unused give_pre_end According to git grep, this is not used now, and was not used in the initial commit that introduced it (see below). This semantic is difficult to implement temporal roll VAE for (and would defeat the purpose). Rather than implement the complex if, just delete the unused feature. (venv) rattus@rattus-box2:~/ComfyUI$ git log --oneline 220afe33 (HEAD) Initial commit. (venv) rattus@rattus-box2:~/ComfyUI$ git grep give_pre comfy/ldm/modules/diffusionmodules/model.py: resolution, z_channels, give_pre_end=False, tanh_out=False, use_linear_attn=False, comfy/ldm/modules/diffusionmodules/model.py: self.give_pre_end = give_pre_end comfy/ldm/modules/diffusionmodules/model.py: if self.give_pre_end: (venv) rattus@rattus-box2:~/ComfyUI$ git co origin/master Previous HEAD position was 220afe33 Initial commit. HEAD is now at 9d8a8179 Enable async offloading by default on Nvidia. (#10953) (venv) rattus@rattus-box2:~/ComfyUI$ git grep give_pre comfy/ldm/modules/diffusionmodules/model.py: resolution, z_channels, give_pre_end=False, tanh_out=False, use_linear_attn=False, comfy/ldm/modules/diffusionmodules/model.py: self.give_pre_end = give_pre_end comfy/ldm/modules/diffusionmodules/model.py: if self.give_pre_end: * move refiner VAE temporal roller to core Move the carrying conv op to the common VAE code and give it a better name. Roll the carry implementation logic for Resnet into the base class and scrap the Hunyuan specific subclass. * model: Add temporal roll to main VAE decoder If there are no attention layers, its a standard resnet and VideoConv3d is asked for, substitute in the temporal rolloing VAE algorithm. This reduces VAE usage by the temporal dimension (can be huge VRAM savings). * model: Add temporal roll to main VAE encoder If there are no attention layers, its a standard resnet and VideoConv3d is asked for, substitute in the temporal rolling VAE algorithm. This reduces VAE usage by the temporal dimension (can be huge VRAM savings).	2025-12-02 22:49:29 -05:00
comfyanonymous	b94d394a64	Support Z Image alibaba pai fun controlnets. (#11062) ... These are not actual controlnets so put it in the models/model_patches folder and use the ModelPatchLoader + QwenImageDiffsynthControlnet node to use it.	2025-12-02 21:38:31 -05:00
rattus	277237ccc1	attention: use flag based OOM fallback (#11038) ... Exception ref all local variables for the lifetime of exception context. Just set a flag and then if to dump the exception before falling back.	2025-12-02 17:24:19 -05:00
comfyanonymous	daaceac769	Hack to make zimage work in fp16. (#11057)	2025-12-02 17:11:58 -05:00
Dr.Lt.Data	b4a20acc54	feat: Support ComfyUI-Manager for pip version (#7555)	2025-12-01 22:32:52 -05:00
comfyanonymous	878db3a727	Implement the Ovis image model. (#11030)	2025-12-01 20:56:17 -05:00
comfyanonymous	2640acb31c	Update qwen tokenizer to add qwen 3 tokens. (#11029) ... Doesn't actually change anything for current workflows because none of the current models have a template with the think tokens.	2025-12-01 17:13:48 -05:00
comfyanonymous	0a6746898d	Make the ScaleRope node work on Z Image and Lumina. (#10994)	2025-11-29 18:00:55 -05:00
comfyanonymous	5151cff293	Add some missing z image lora layers. (#10980)	2025-11-28 23:55:00 -05:00
comfyanonymous	52a32e2b32	Support some z image lora formats. (#10978)	2025-11-28 21:12:42 -05:00
Jukka Seppänen	b907085709	Support video tiny VAEs (#10884) ... * Support video tiny VAEs * lighttaew scaling fix * Also support video taes in previews Only first frame for now as live preview playback is currently only available through VHS custom nodes. * Support Wan 2.1 lightVAE * Relocate elif block and set Wan VAE dim directly without using pruning rate for lightvae	2025-11-28 19:40:19 -05:00
rattus	0ff0457892	mm: wrap the raw stream in context manager (#10958) ... The documentation of torch.foo.Stream being usable with with: suggests it starts at version 2.7. Use the old API for backwards compatibility.	2025-11-28 16:38:12 -05:00
Urle Sistiana	6484ac89dc	fix QuantizedTensor.is_contiguous (#10956) (#10959)	2025-11-28 16:33:07 -05:00