fix: Calculate 25% more VRAM for base models with weights/LoRAs

Instead of adding a fixed 2GB overhead, now calculates 25% more
VRAM for base models that will have fine-tuned weights/tensors
or LoRA adapters loaded on top.
parent 1162d3c0
...@@ -3909,8 +3909,9 @@ def select_best_model(gen_type, models, vram_gb=24, prefer_quality=True, return_ ...@@ -3909,8 +3909,9 @@ def select_best_model(gen_type, models, vram_gb=24, prefer_quality=True, return_
} }
# Check VRAM compatibility using base model requirements # Check VRAM compatibility using base model requirements
# LoRAs add a small overhead (~1-2GB) # LoRAs and fine-tuned weights add significant overhead (25% more)
vram_est = parse_vram_estimate(base_model_info.get("vram", "~10 GB")) + 2 base_vram = parse_vram_estimate(base_model_info.get("vram", "~10 GB"))
vram_est = base_vram * 1.25 # 25% more for weights/tensors/loras
if allow_bigger_models: if allow_bigger_models:
# If allowing bigger models, check if VRAM + 75% of available RAM is sufficient # If allowing bigger models, check if VRAM + 75% of available RAM is sufficient
available_ram = get_available_ram_gb() available_ram = get_available_ram_gb()
......
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