(Experimental) A high-throughput and memory-efficient inference and serving engine for LLMs optimized for GB10 homelabs

Optimized vLLM deployment for NVIDIA Blackwell (RTX 5090) on Linux Kernel 6.14. Resolves SM_120 kernel incompatibilities, P2P deadlocks, and memory fragmentation for high-performance LLM inference.

Rust-native MoE inference runtime with custom CUDA kernels for Blackwell GPUs. Includes DFlash speculative decoding, multi-tier Engram memory, and entropy-adaptive routing. Targets Qwen3.5-35B-A3B on a single RTX 5060 Ti 16GB.

VPN-free Prebuilt PyTorch 2.9.0 for CUDA 12.8 + sm_120 (RTX 5080)

Pre-built onnxruntime-gpu 1.24.1 with Blackwell sm_120 CUDA kernels (RTX 5090/5080/5070)

llama.cpp fork with additional SOTA quants and improved performance

Complete installation guide for ComfyUI-Hunyuan3DWrapper on NVIDIA Blackwell GPUs (RTX 5070 Ti, 5080, 5090) Covers custom_rasterizer manual compilation for sm_120 / compute_120 architecture.