Home Lab Infrastructure

Local Compute Node

I prioritize data sovereignty and low-latency workflows. Instead of relying solely on cloud APIs, I maintain a dedicated on-premise environment optimized for generative AI workloads and high-throughput media rendering.

Resource Allocation

Compute Accelerator

CUDA-Based Inference

Equipped with a 24GB VRAM buffer to load large parameter LLMs (Qwen3-Coder-Next-80b (3b active) via quantization) partly into memory for rapid token generation.

Processing

Hybrid Core Architecture

24-core / 32-thread config leveraging high-frequency P-cores for compilation and E-cores for background container orchestration.

Memory

DDR5 Pool

High-bandwidth memory tier ensures stability when running multiple Docker containers alongside memory-intensive video rendering tasks.

Storage IO

All-NVMe Array

Gen4 storage fabric providing massive IOPS to eliminate bottlenecks during 4K footage scrubbing and dataset loading.

Creative & Generative Ecosystem

LM Studio

My primary interface for testing quantized GGUF models. Allows for rapid swapping of model architectures to benchmark inference speeds and logical reasoning.

ComfyUI

Advanced node-based pipeline extending beyond static images. I engineer custom workflows for generative video, audio-reactive visuals, and neural lip-syncing to produce full-motion media locally.

DaVinci Resolve

The command center for assembly. I utilize the full GPU stack for color grading, Fusion VFX compositing, and final mastering, ensuring seamless integration of AI-generated assets into linear timelines.