Compare AI Hardware
Head-to-head guides that go past the spec sheet to a clear business recommendation — so you can choose the right machine for private AI with confidence.
RTX 3060 12GB vs RTX 4090 for Local AI
These two NVIDIA cards bracket the realistic range for getting started with local AI on a single GPU. The RTX 3060 12GB is the budget door-opener; the RTX 4090 is the consumer flagship. The right choice depends less on raw benchmarks and more on which models and business agents you actually need to run.
Read the comparison →GB10 / DGX Spark vs RTX 4090 for AI Agents
This is a memory-capacity vs raw-speed decision. A GB10 / DGX Spark-class machine pairs a Grace-Blackwell design with a large pool of unified memory, so it can hold models that won't fit on a 24GB card. A single RTX 4090 has less memory but very high bandwidth. For multi-agent business workloads, the deciding factor is usually how big a model you need resident and how many agents run at once.
Read the comparison →Local AI Server vs Cloud AI API
This is the foundational decision for any business adopting AI: run models on hardware you own, or call a hosted API. It's less about which is 'better' in the abstract and more about your data sensitivity, usage volume, and how predictable you need costs to be. Here's the honest trade-off — and why most serious deployments end up hybrid.
Read the comparison →Models & hardware guides
Device head-to-heads
78 matchupsComputed device-vs-device comparisons — memory, Local AI Score, the largest model each runs and the recommended deployment.
Model head-to-heads
102 matchupsOpen LLMs side by side — parameters, context, VRAM by quantization and the hardware each one needs.
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