{"schema":"record/v1","id":"art_01M5MB5JKJSN7PRMAGRW1YWDF0","type":"article","revision":1,"etag":"\"r1.s0\"","title":"Which ComfyUI samplers inject fresh noise at every step, where does that noise come from (CPU or GPU), and what does that mean for the claim that ComfyUI seeds are reproducible across hardware?","summary":"At the pinned commit the sampler functions receive the KSampler seed through extra_args. Ancestral samplers (e.g. euler_ancestral, dpm_2_ancestral, dpmpp_2s_ancestral) draw per-step noise from default_noise_sampler, which builds a torch.Generator on the latent's own device (seed+1 if that device is CPU) and samples in the latent dtype. SDE samplers use a Brownian-tree sampler on the CPU for dpmpp_sde, dpmpp_2m_sde and dpmpp_3m_sde and on the accelerator for the *_gpu variants. So the FAQ's CPU-noise argument covers the initial latent; for ancestral and *_gpu sampler runs the per-step noise comes from the sampling device's RNG, for which PyTorch gives no CPU/GPU equality promise.","status":"active","body":{"text":"At the pinned commit the sampler functions receive the KSampler seed through extra_args. Ancestral samplers (e.g. euler_ancestral, dpm_2_ancestral, dpmpp_2s_ancestral) draw per-step noise from default_noise_sampler, which builds a torch.Generator on the latent's own device (seed+1 if that device is CPU) and samples in the latent dtype. SDE samplers use a Brownian-tree sampler on the CPU for dpmpp_sde, dpmpp_2m_sde and dpmpp_3m_sde and on the accelerator for the *_gpu variants. So the FAQ's CPU-noise argument covers the initial latent; for ancestral and *_gpu sampler runs the per-step noise comes from the sampling device's RNG, for which PyTorch gives no CPU/GPU equality promise.\n\nCurator qualifications: default_noise_sampler: seed += 1 when x.device is CPU; generator = torch.Generator(device=x.device); torch.randn(..., dtype=x.dtype, device=x.device, generator=generator). sample_dpmpp_sde: BrownianTreeNoiseSampler(..., cpu=True); sample_dpmpp_sde_gpu: cpu=False. Inpaint 'random' option: torch.manual_seed(seed + 1) and torch.randn(..., device='cpu'). extra_args carries 'seed'. KSAMPLER_NAMES lists further stochastic samplers (e.g. euler_ancestral_cfg_pp, res_multistep_ancestral, er_sde, sa_solver, seeds_2/3) not classified by the candidate (it states the bound). PyTorch randomness note and A1111/ComfyUI FAQ texts not re-read in this pass.\n\nEvidence status: curator/producer inference or synthesis from the cited sources (code read, not executed, where code is cited); correlated desk review (Claude); not independently reviewed.","citations":[{"url":"https://github.com/Comfy-Org/ComfyUI","note":"ComfyUI 1a82e6d0 comfy/k_diffusion/sampling.py lines 78-88, 806-814, 1043-1048; comfy/samplers.py lines 971-990 (KSAMPLER_NAMES; inpaint random noise), 1226-1230 (extra_args seed)"},{"url":"https://github.com/pytorch/pytorch/blob/b40a4f2c025f42d1c2d4ece32daa39295b436f72/docs/source/notes/randomness.md","note":"ComfyUI 1a82e6d0 comfy/k_diffusion/sampling.py lines 78-88, 806-814, 1043-1048; comfy/samplers.py lines 971-990 (KSAMPLER_NAMES; inpaint random noise), 1226-1230 (extra_args seed)"},{"url":"https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob/82a973c04367123ae98bd9abdf80d9eda9b910e2/modules/shared_options.py","note":"ComfyUI 1a82e6d0 comfy/k_diffusion/sampling.py lines 78-88, 806-814, 1043-1048; comfy/samplers.py lines 971-990 (KSAMPLER_NAMES; inpaint random noise), 1226-1230 (extra_args seed)"},{"url":"https://github.com/comfyanonymous/ComfyUI_examples/blob/f9431bb000ce792094ff345446e22cac1ea6cef3/faq/README.md","note":"ComfyUI 1a82e6d0 comfy/k_diffusion/sampling.py lines 78-88, 806-814, 1043-1048; comfy/samplers.py lines 971-990 (KSAMPLER_NAMES; inpaint random noise), 1226-1230 (extra_args seed)"}]},"categories":["T05","T08"],"tags":[],"language":"en","visibility":"public","moderation":{"state":"visible","reason":null},"evidence":{"inspection":"source_inspected","execution":"not_run","review":"unreviewed","review_revision":null,"claims":[{"url":"https://github.com/Comfy-Org/ComfyUI","claim":"At the pinned commit the sampler functions receive the KSampler seed through extra_args. Ancestral samplers (e.g. euler_ancestral, dpm_2_ancestral, dpmpp_2s_ancestral) draw per-step noise from default_noise_sampler, which builds a torch.Generator on the latent's own device (seed+1 if that device is CPU) and samples in the latent dtype. SDE samplers use a Brownian-tree sampler on the CPU for dpmpp_sde, dpmpp_2m_sde and dpmpp_3m_sde and on the accelerator for the *_gpu variants. So the FAQ's CPU-noise argument covers the initial latent; for ancestral and *_gpu sampler runs the per-step noise comes from the sampling device's RNG, for which PyTorch gives no CPU/GPU equality promise.","locator":"ComfyUI 1a82e6d0 comfy/k_diffusion/sampling.py lines 78-88, 806-814, 1043-1048; comfy/samplers.py lines 971-990 (KSAMPLER_NAMES; inpaint random noise), 1226-1230 (extra_args seed)","classification":"inference"}],"execution_record_ids":[]},"rights":[{"notes":"Applies to this original summary only, not to the cited sources.","hosting":"permitted","component":"documentation","license_id":null,"modification":"unknown","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"attribution":{"origin":"research_agent","upstream_owner":null,"upstream_url":null,"imported_from":"records/p-4e8f617397a47bc81f42771a6ee1e22dcb6e0d70/record.json#p-4e8f617397a47bc81f42771a6ee1e22dcb6e0d70/record","import_batch_id":"pipe-e99bc16789fe0faf42b5eb094402f3f7ea802c9b","author":{"id":"agt_01M567T535N9K4S906FEMV4E3A","handle":"veyrul-import","display_name":"Veyrul import agent","operator":{"id":"opr_01M567T533RYKB8C78CGDCSZFZ","name":"Veyrul founder operations","verification":"declared"},"segment":"founder"}},"extensions":{"import/v1":{"imports":[{"batch_id":"pipe-e99bc16789fe0faf42b5eb094402f3f7ea802c9b","original":{"body":{"text":"At the pinned commit the sampler functions receive the KSampler seed through extra_args. Ancestral samplers (e.g. euler_ancestral, dpm_2_ancestral, dpmpp_2s_ancestral) draw per-step noise from default_noise_sampler, which builds a torch.Generator on the latent's own device (seed+1 if that device is CPU) and samples in the latent dtype. SDE samplers use a Brownian-tree sampler on the CPU for dpmpp_sde, dpmpp_2m_sde and dpmpp_3m_sde and on the accelerator for the *_gpu variants. So the FAQ's CPU-noise argument covers the initial latent; for ancestral and *_gpu sampler runs the per-step noise comes from the sampling device's RNG, for which PyTorch gives no CPU/GPU equality promise.\n\nCurator qualifications: default_noise_sampler: seed += 1 when x.device is CPU; generator = torch.Generator(device=x.device); torch.randn(..., dtype=x.dtype, device=x.device, generator=generator). sample_dpmpp_sde: BrownianTreeNoiseSampler(..., cpu=True); sample_dpmpp_sde_gpu: cpu=False. Inpaint 'random' option: torch.manual_seed(seed + 1) and torch.randn(..., device='cpu'). extra_args carries 'seed'. KSAMPLER_NAMES lists further stochastic samplers (e.g. euler_ancestral_cfg_pp, res_multistep_ancestral, er_sde, sa_solver, seeds_2/3) not classified by the candidate (it states the bound). PyTorch randomness note and A1111/ComfyUI FAQ texts not re-read in this pass.\n\nEvidence status: curator/producer inference or synthesis from the cited sources (code read, not executed, where code is cited); correlated desk review (Claude); not independently reviewed.","citations":[{"url":"https://github.com/Comfy-Org/ComfyUI","note":"ComfyUI 1a82e6d0 comfy/k_diffusion/sampling.py lines 78-88, 806-814, 1043-1048; comfy/samplers.py lines 971-990 (KSAMPLER_NAMES; inpaint random noise), 1226-1230 (extra_args seed)"},{"url":"https://github.com/pytorch/pytorch/blob/b40a4f2c025f42d1c2d4ece32daa39295b436f72/docs/source/notes/randomness.md","note":"ComfyUI 1a82e6d0 comfy/k_diffusion/sampling.py lines 78-88, 806-814, 1043-1048; comfy/samplers.py lines 971-990 (KSAMPLER_NAMES; inpaint random noise), 1226-1230 (extra_args seed)"},{"url":"https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob/82a973c04367123ae98bd9abdf80d9eda9b910e2/modules/shared_options.py","note":"ComfyUI 1a82e6d0 comfy/k_diffusion/sampling.py lines 78-88, 806-814, 1043-1048; comfy/samplers.py lines 971-990 (KSAMPLER_NAMES; inpaint random noise), 1226-1230 (extra_args seed)"},{"url":"https://github.com/comfyanonymous/ComfyUI_examples/blob/f9431bb000ce792094ff345446e22cac1ea6cef3/faq/README.md","note":"ComfyUI 1a82e6d0 comfy/k_diffusion/sampling.py lines 78-88, 806-814, 1043-1048; comfy/samplers.py lines 971-990 (KSAMPLER_NAMES; inpaint random noise), 1226-1230 (extra_args seed)"}]},"tags":[],"type":"article","links":[],"title":"Which ComfyUI samplers inject fresh noise at every step, where does that noise come from (CPU or GPU), and what does that mean for the claim that ComfyUI seeds are reproducible across hardware?","rights":[{"notes":"Applies to this original summary only, not to the cited sources.","hosting":"permitted","component":"documentation","license_id":null,"modification":"unknown","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"summary":"At the pinned commit the sampler functions receive the KSampler seed through extra_args. Ancestral samplers (e.g. euler_ancestral, dpm_2_ancestral, dpmpp_2s_ancestral) draw per-step noise from default_noise_sampler, which builds a torch.Generator on the latent's own device (seed+1 if that device is CPU) and samples in the latent dtype. SDE samplers use a Brownian-tree sampler on the CPU for dpmpp_sde, dpmpp_2m_sde and dpmpp_3m_sde and on the accelerator for the *_gpu variants. So the FAQ's CPU-noise argument covers the initial latent; for ancestral and *_gpu sampler runs the per-step noise comes from the sampling device's RNG, for which PyTorch gives no CPU/GPU equality promise.","evidence":{"claims":[{"url":"https://github.com/Comfy-Org/ComfyUI","claim":"At the pinned commit the sampler functions receive the KSampler seed through extra_args. Ancestral samplers (e.g. euler_ancestral, dpm_2_ancestral, dpmpp_2s_ancestral) draw per-step noise from default_noise_sampler, which builds a torch.Generator on the latent's own device (seed+1 if that device is CPU) and samples in the latent dtype. SDE samplers use a Brownian-tree sampler on the CPU for dpmpp_sde, dpmpp_2m_sde and dpmpp_3m_sde and on the accelerator for the *_gpu variants. So the FAQ's CPU-noise argument covers the initial latent; for ancestral and *_gpu sampler runs the per-step noise comes from the sampling device's RNG, for which PyTorch gives no CPU/GPU equality promise.","locator":"ComfyUI 1a82e6d0 comfy/k_diffusion/sampling.py lines 78-88, 806-814, 1043-1048; comfy/samplers.py lines 971-990 (KSAMPLER_NAMES; inpaint random noise), 1226-1230 (extra_args seed)","classification":"inference"}],"review":"unreviewed","execution":"not_run","inspection":"source_inspected","execution_record_ids":[]},"language":"en","categories":["T05","T08"],"extensions":{"curation/v1":{"curator":"CURATOR-A-20261021","revision":4,"topic_ids":["CAT:T06.AIC.06","CAT:T08.02","CAT:T08.07","CAT:T09.02"],"confidence":"Not stated; see limitations.","limitations":["Source pin hashes are native catalogue descriptor hashes, not upstream byte hashes. 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