From d5562f0602544b3a6dda205fe7687e9169436f37 Mon Sep 17 00:00:00 2001 From: Rattus Date: Thu, 4 Dec 2025 13:58:10 +1000 Subject: [PATCH] mp: use look-ahead actuals for stream offload VRAM calculation 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. --- comfy/model_patcher.py | 12 +++++++++--- 1 file changed, 9 insertions(+), 3 deletions(-) diff --git a/comfy/model_patcher.py b/comfy/model_patcher.py index df2d8e827..3dcac3eef 100644 --- a/comfy/model_patcher.py +++ b/comfy/model_patcher.py @@ -699,12 +699,12 @@ class ModelPatcher: offloaded = [] offload_buffer = 0 loading.sort(reverse=True) - for x in loading: + for i, x in enumerate(loading): module_offload_mem, module_mem, n, m, params = x lowvram_weight = False - potential_offload = max(offload_buffer, module_offload_mem + (comfy.model_management.NUM_STREAMS * module_mem)) + potential_offload = max(offload_buffer, module_offload_mem + sum([ x1[1] for x1 in loading[i+1:i+1+comfy.model_management.NUM_STREAMS]])) lowvram_fits = mem_counter + module_mem + potential_offload < lowvram_model_memory weight_key = "{}.weight".format(n) @@ -876,14 +876,18 @@ class ModelPatcher: patch_counter = 0 unload_list = self._load_list() unload_list.sort() + offload_buffer = self.model.model_offload_buffer_memory + if len(unload_list) > 0: + NS = comfy.model_management.NUM_STREAMS + offload_weight_factor = [ min(offload_buffer / (NS + 1), unload_list[0][1]) ] * NS for unload in unload_list: if memory_to_free + offload_buffer - self.model.model_offload_buffer_memory < memory_freed: break module_offload_mem, module_mem, n, m, params = unload - potential_offload = module_offload_mem + (comfy.model_management.NUM_STREAMS * module_mem) + potential_offload = module_offload_mem + sum(offload_weight_factor) lowvram_possible = hasattr(m, "comfy_cast_weights") if hasattr(m, "comfy_patched_weights") and m.comfy_patched_weights == True: @@ -935,6 +939,8 @@ class ModelPatcher: m.comfy_patched_weights = False memory_freed += module_mem offload_buffer = max(offload_buffer, potential_offload) + offload_weight_factor.append(module_mem) + offload_weight_factor.pop(0) logging.debug("freed {}".format(n)) for param in params: