Mac Studio Clusters Now Run Trillion-Parameter Models for $40K
macOS RDMA over Thunderbolt 5 has turned four Mac Studios into a 1.5TB unified memory cluster that runs Kimi K2 at 25 tokens per second - a setup that would cost $780K with NVIDIA H100s.
Articles Tagged "Local AI"
Apple M4 Max - Unified Memory for Large Models
Full specs and benchmarks for the Apple M4 Max SoC - up to 128GB unified memory at 546 GB/s, 3nm process, and why it has become the quiet favorite for running 70B+ models locally.
NVIDIA RTX 3090 - The Budget 24GB Value King
Full specs and benchmarks for the NVIDIA GeForce RTX 3090 - 24GB GDDR6X at 936 GB/s, Ampere architecture, and why used 3090s remain the best value option for local AI inference in 2026.
NVIDIA RTX 4090 - The Home Lab AI Standard
Full specs and benchmarks for the NVIDIA GeForce RTX 4090 - 24GB GDDR6X, 1,008 GB/s bandwidth, Ada Lovelace architecture, and why it remains the default home lab GPU for local AI inference.
NVIDIA RTX 5090 - Blackwell for the Home Lab
Full specs and benchmarks for the NVIDIA GeForce RTX 5090 - 32GB GDDR7, 1,792 GB/s bandwidth, Blackwell architecture, and what it means for local AI inference.
AORUS RTX 5090 AI BOX vs NVIDIA DGX Spark for Local AI
Two very different approaches to desktop AI hardware - a 32 GB eGPU with 1,792 GB/s bandwidth versus a 128 GB unified memory mini PC with full CUDA. Which one should you buy?
AORUS RTX 5090 AI BOX Review: Desktop GPU Power via Thunderbolt 5
A review of the Gigabyte AORUS RTX 5090 AI BOX - a liquid-cooled eGPU packing a full desktop RTX 5090 with 32 GB GDDR7, connecting to any laptop over Thunderbolt 5 for $2,999.
DGX Spark Review: NVIDIA's $4,699 Desktop AI Box
A hands-on review of the NVIDIA DGX Spark - a 128 GB Grace Blackwell mini PC that promises 1 petaflop of AI performance on your desk for $4,699.
NVIDIA DGX Spark Setup and Usage Guide for 2026
A complete guide to setting up the NVIDIA DGX Spark - from unboxing and first boot to running LLM inference, fine-tuning models, and optimizing performance.
The Creator of MLX Just Left Apple - And He's Not the First
Awni Hannun, the Stanford-trained researcher who co-created Apple's MLX machine learning framework, announced his departure from Apple. His exit is the latest in a devastating exodus of AI talent that has hollowed out Apple's ML research bench over the past year.
LM Studio Launches LM Link - Access Your GPU Rig's Models From Anywhere via Encrypted Mesh
LM Studio 0.4.5 introduces LM Link, built on Tailscale's tsnet library, letting users access local AI models on remote hardware through end-to-end encrypted connections with zero port forwarding.
Liquid AI Drops LFM2-24B - A 24 Billion Parameter Model That Runs on Your Laptop
MIT spinoff Liquid AI releases LFM2-24B-A2B, a hybrid mixture-of-experts model that activates only 2.3B parameters per token, fits in 32GB RAM, and hits 112 tokens per second on a consumer CPU.
