Silicon-Implants
MPS-native augmentation nodes for ComfyUI optimized for Apple Silicon with high-performance alternatives for loaders, encoders, and samplers. (Description by CC)
TLDR: git clone https://github.com/Blackest/Silicon-Implants comfyui-silicon-implants
Silicon-Implants: MPS-native augmentation nodes for ComfyUI. It's Not PC :) Tired of sagging? Not getting the performance you expect? Introducing Silicon-Implants for ComfyUI.
Many nodes are PC-first; if you haven't got CUDA, they fall back to the CPU. On Apple Silicon, we have Unified Memory and Metal Performance Shaders (MPS). We aren't built the same. If you want the freedom of not being PC in 2026, these nodes are for you.
The Strategy: Surgical Augmentation Silicon-Implants is not a "catch-all" node pack. It is a lean repository of high-performance alternatives designed to "augment" your setup, not replace it. PC-centric nodes shuffle GBs of data over the PCI Bus. On Apple Silicon, it's all the same memory—it’s not a swap, it's deciding who does the job.
Targeted: Only alternatives for bottleneck nodes (Loaders, Encoders, Samplers) currently crippled by CPU fallback.
Efficiency-First: If it isn't slow, we don't touch it.
Plug & Play: Keep your favorite "pig" repos; just swap in these [MPS] native versions where it counts.
Real-World Silicon Tips Avoid FP8: It’s not Apple-native and usually crashes.
RAM Management: Monitor Activity Monitor. Orange is okay; Red is bad. If you're hitting 150GB use with 75GB swap, you're killing your internal SSD.
Browser Choice: Use Safari or run ComfyUI remotely to keep Chrome from eating your Unified RAM.
Open Build: The "50 Nodes" Vision The Goal: If 50 developers fix just one bottleneck node, we have a world-class, native Mac ecosystem in a week.
Contributor Rules:
Author Attribution: Every node file includes a mandatory AUTHOR attribute. If you fix the node, you get the credit.
MPS-Native: Code must check for MPS and default to BF16/Unified Memory logic. No lazy CPU fallbacks.
Lean: No unnecessary dependencies. Keep the implants surgical.
Licensing Since this code is often derivative of other code, licensing derives with it. Gemma_api_conditioning_MPS.py inherits the LTX-2 licensing (see LICENSE_LTX2 in this repo).
Note: If you actually meet the requirement for commercial licensing (>$10M revenue), can I be your friend? :)
Stop the fallbacks. Start using your GPU.