AI Hardware Radar

Kingy topic graph pilot

AI hardware, mapped to the decision you actually need to make.

Start with the workload, check the memory fit, compare the platform, then validate against real local-AI results. This hub keeps Kingy’s guides, tests, runtimes and release coverage in one usable path.

Choose a starting path See tested results

Canonical routes only
Tested results separated from guidance
Release records kept distinct from product facts

Start here

Get to a defensible shortlist

Two routes cover most readers: the full 2026 field guide, or a direct compatibility check for hardware you already own.

Flagship guide

Local AI Hardware Guide 2026

See what model classes run at each budget, where memory becomes the constraint, and when cloud remains the rational choice.

Read the guide Compatibility

Will your current hardware work?

Check laptops, mini PCs, Macs and phones against the workloads they can realistically support.

Check the fit

Tested results

Receipts from the Local Lab

These are evidence routes, not generic recommendations. Each result stays attached to its named model and tested RTX 4090 configuration.

Kingy Local Lab

Browse the complete test bench

Follow reproducible local-AI runs, hardware context and evidence boundaries.

Open the lab

RTX 4090 · 24 GBGemma 4 31B-it RTX 4090 · 24 GBQwen3.6-27B RTX 4090 · 24 GBQwen3.8-27B

Memory & fit

Find the constraint before you shop

Memory capacity and bandwidth usually narrow the field faster than marketing labels do.

How much RAM for local AI?

System memory guidance by workload and setup.

How much VRAM for local AI?

GPU memory limits, tradeoffs and fit checks.

Compare platforms

Make the architecture tradeoff explicit

See all hardware comparisons

Platform comparisonApple Silicon vs NVIDIA GPU for local AI

Compare unified memory, acceleration, software support and upgrade paths.

Buying paths

Translate the workload into a purchase

See all buying guides

Decision guideBest hardware for running local LLMs

Move from model requirements to memory, GPU and form-factor choices.

Runtime records

Connect the machine to the software

Canonical product records are linked for profile and compatibility context. Product Facts remain withheld until a release state exists.

Canonical product recordOllama

Local model runtime and API workflow.

Canonical product recordLM Studio

Desktop model discovery, loading and serving.

Keep current

Follow launches without mixing evidence types

Release chronology belongs in the calendar; implementation depth belongs in the guide.

Live chronology

AI Hardware Release Calendar

Track dated hardware and local-runtime changes from a dedicated release surface.

Open the calendar Deep guide

Local AI Models: definitive guide

Carry the hardware decision through setup, installation, model selection and real-world use.

Continue to implementation