Local AI hardware compatibility
Build a local AI setup your machine can actually run.
Choose a GPU, Mac, or mini-PC and a model. See whether it fits in VRAM or unified memory, which quantization and context work, how fast it should feel, and which runtime supports it.
Check your hardware
No machine yet? Build a complete stackSourced + stamped data · computes in your browser
One connected answer
The five layers of a local AI setup
TokenAssemble connects the parts other tools leave separate. Each step opens the sourced directory behind the verdict.
01 / MEMORY
Hardware
GPUs and complete systems
02 / WEIGHTS
Model
Architecture, size, and context
03 / FIT
Quant
Measured artifact sizes per model
04 / SERVE
Runtime
Support, compatibility, and ease
05 / USE
Software
Apps connected to local runtimes
Start from the job
What are you building?
Four complete workflow templates connect software, runtime, and model picks, then grade the hardware underneath.
Local coding assistant
A private Copilot alternative: an editor assistant pointed at a model your own machine serves.
See the workflowPrivate chat server
A self-hosted ChatGPT-style app for your household or team — nothing leaves the box.
See the workflowLocal transcription + summary pipeline
Voice notes and meetings to searchable text and summaries, fully offline: a local STT engine feeding a small LLM.
See the workflowLocal agent stack
An agent harness with a locally served model behind it — autonomy without an API bill.
See the workflowPlan the machine
Need hardware too?
Answer three different purchase questions: what should I build, which machine is better, and whether buying beats cloud.
Build a complete AI stack
Compatible hardware, model, quant, runtime, and software—ranked within your budget.
Build my stackCompare hardware
Compare GPU, Mac, and mini-PC tradeoffs with links to computed feasibility checks.
Compare machinesLocal vs cloud ROI
Estimate whether a local hardware purchase breaks even for your usage and electricity cost.
Run the numbersThe answer shows its work.
Fit physics, source dates, runtime gates, assumptions, and beta labels stay visible. Speed is always a tier, never a fabricated number.