Older stories and guides from the Convly archive.
You can build a capable AI workstation for under $1500 — if you spend the GPU budget wisely. Here are the best value GPUs for local AI work on a tight budget.
The best GPUs for AI and ML development in 2026, ranked by what actually matters for experimentation: VRAM, performance, and value. One clear pick for each budget.
The Snapdragon 8 Elite and Apple A18 Pro power the most AI-capable phones of their generation. Here’s how their on-device AI engines actually compare.
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.
An RTX 5090 offers far more speed but only 32 GB; a Mac Studio M3 Ultra offers up to 512 GB of unified memory. Which platform runs big local models better, based on published specs and public llama.cpp results.
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’s DGX Spark (announced as Project DIGITS) and Apple’s Mac Studio with M5 Max or M5 Ultra are the two compact desktops built for running large AI models at home. Memory, bandwidth, price and which one to buy.
There is no M4 Ultra. The 2026 Mac Studio uses the M5 Max (up to 128 GB, 614 GB/s) and M5 Ultra (up to 512 GB, 1.2 TB/s). What each runs for local AI, from Apple’s specs and real model file sizes.
