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CUDA Lock-In Is Real: A Precise Cost Accounting of What Switching GPU Vendors Actually Breaks
Switching away from CUDA isn't one migration — it's five separate porting problems, hidden revalidation costs, and an org chart that fights you the whole way.
BitByteCore Silicon Desk · Aug 6, 2026 · 9 min read

The best home-server hardware for self-hosting AI in 2026
The used RTX 3090 is still the value pick for local AI in 2026 — but a brutal memory shortage reshuffled every price, and 128GB unified boxes (DGX Spark, Strix Halo, Mac Studio) now run big MoE models a 24GB GPU can't hold. Here's what to actually buy.
BitByteCore Research · Aug 3, 2026 · 13 min read

The best cloud GPU providers for AI training in 2026
CoreWeave shipped NVIDIA's GB300 NVL72 first and runs GB200 at scale; Google's Ironwood TPU reached GA in late 2025; AWS and Azure now ship Blackwell; Lambda and Nebius rent B200 affordably. A skeptic's 2026 buyer's guide to hardware, trade-offs, and representative pricing.
BitByteCore Research · Aug 3, 2026 · 11 min read

The best cloud hosting for running AI models in 2026
AWS and Google Cloud are still the safest full-stack bets, but RunPod, Lambda, and Vast.ai win on raw GPU price — and OpenAI is no longer strictly Azure-only. A buyer's guide to nine AI clouds, with honest trade-offs and mid-2026 ballpark pricing.
BitByteCore Research · Aug 2, 2026 · 11 min read

HBM Explained: Why High-Bandwidth Memory Is the Real Bottleneck in AI Chips
Peak FLOPS are a distraction. The real constraint in every AI accelerator is how fast memory can feed the compute, and HBM is that constraint. Here is how it is built, why inference is memory-bound, why HBM4 doubles the bus instead of the clock, and why packaging, not silicon, is the supply
BitByteCore Silicon Desk · Jul 29, 2026 · 12 min read


