Local LLMs

Why it matters

Run security audits, reverse engineering, and proprietary codebase queries through confidential computing enclaves without vendor surveillance or session policy blocks.

Why it matters

You can experiment with massive Mixture-of-Experts (MoE) models on affordable consumer hardware using disk streaming and clever prefetching without renting expensive cloud clusters.

Why it matters

A zero-dependency HTML calculator estimates VRAM requirements for GGUF models before downloading. It computes model weights, context length, and architecture-specific KV cache footprint to avoid CUDA allocation crashes, with the caveat that MoE and mixed-quant files land a few percent off the table.

Why it matters

You can inspect the reasoning degradation and raw latency of client-side local language models directly in your browser without spinning up backend GPU infrastructure.

Why it matters

Accelerate local multimodal inference up to 2.62x end-to-end on Apple Silicon and server GPUs using official builds of llama.cpp, MLX, and SGLang.

Why it matters

You can protect your local AI and fine-tuning pipelines from broken builds caused by deleted or censored model repositories on centralized hubs.