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.
The H200 is not a faster compute chip than the H100 — it is the same Hopper GPU with far more memory. For large-model inference, that distinction is everything.
The H100 outclasses the A100 on every performance axis — but the A100 still rents for a fraction of the price. Here’s exactly when the older card wins on cost-efficiency.
Both NPUs hit ~40 TOPS. Both promise all-day battery. But Snapdragon X Elite + Copilot+ PC and Apple M4 MacBook Air are very different machines. Here’s which to buy.
Both ship with 16 GB GDDR7 and Blackwell. The 5080 costs 33% more — is it 33% better for AI? We tested both side-by-side.
Google’s Pixel 10 Pro is the most AI-first phone of 2026 — by design. Here’s every feature it can do, and how it actually compares to iPhone 17 Pro and Galaxy S26 Ultra.
Top open-source LLMs in 2026 ranked by capability + the exact hardware you need to run each locally. Llama 3 405B, Qwen 2.5 72B, DeepSeek V3, Mistral Large 2.
