Head-to-head comparisons of AI hardware
Two Chinese labs shipped open-weight coding models a day apart. We fact-check the specs, context windows, pricing, licenses and benchmarks of GLM 5.2 and Kimi K2.7 Code to see which open coder actually fits your workflow.
China’s two biggest labs shipped flagship models six weeks apart. DeepSeek V4 is open-weight and dirt cheap; Qwen3.7 Max is closed, faster, and scores a touch higher. We compare them on coding, reasoning, context, speed, and cost.
DeepSeek V4 now rivals GPT-5.5 on raw capability and costs a fraction of the price — but ChatGPT still wins on polish, ecosystem, and data privacy. Here’s which one fits your needs.
The RX 7900 XTX matches the RTX 4090 on VRAM and undercuts it on price. The catch is software: ROCm versus CUDA. Here’s where AMD’s flagship genuinely competes — and where it still doesn’t.
The RTX 5090 has double the VRAM of the 5080 and double the price. For AI, that VRAM gap decides everything — here’s which Blackwell card fits your work.
It’s the classic 2026 local-AI dilemma: an RTX 5090’s blistering speed and 32 GB, or a Mac Studio M4 Ultra’s enormous unified memory. Here’s which platform wins, and why.
The RTX 5080 and RTX 4080 Super both ship 16 GB of VRAM at a $999 price. The difference is Blackwell’s GDDR7 bandwidth and FP4 — here’s whether it matters for AI.
The RTX 5070 Ti and 4070 Ti Super are the value-enthusiast picks for local AI — both 16 GB. Here’s whether Blackwell’s bandwidth gain is worth choosing the newer card.
Both the RTX 4090 and RTX 3090 ship 24 GB of VRAM — so for AI, the question isn’t whether a model fits, it’s how fast it runs. Here’s the benchmark-backed verdict.
The RTX 4060 Ti 16GB and RTX 3060 12GB are the two entry points to serious local AI. More VRAM or lower price? Here’s the budget-builder’s verdict.
NVIDIA DIGITS and the Mac Studio are the two compact desktop machines purpose-built for running large AI models at home. Here’s how they actually compare.
On a Mac, the AI question is unified memory: how much, and how fast. Here’s how the M4 Max and M4 Ultra Mac Studio configurations compare for running local LLMs.
