Quilter published a detailed comparison of the three main AI PCB autorouting tools: Quilter, DeepPCB, and Flux.ai. It is, of course, written by Quilter -- but the technical specifics are concrete enough to evaluate independently.
Where the tools actually differ:
The physics validation gap is the most significant differentiator. Quilter runs circuit-level checks: bypass capacitor placement, differential pair integrity, power net capacity, and impedance via an integrated Simbeor field solver. DeepPCB focuses on geometric DRC (clearances, trace widths, via counts). Flux.ai optimizes trace geometry but requires manual routing of critical signals. If you need signal integrity sign-off built into the autoroute pass, only one of these tools attempts it.
Scale matters too:
Quilter demonstrated its router on an 843-component board with 5,141 pins across 8 layers. DeepPCB's public tier caps at 1,000 components and 2,200 pins. Flux.ai examples run 40-100 components on 2-4 layers. These are not equivalent tools targeting the same market segment -- they're addressing different complexity tiers.
The deployment angle:
Quilter runs self-hosted via Kubernetes and supports air-gapped and GovCloud environments. DeepPCB and Flux.ai are cloud-only. For defense and industrial customers with data residency requirements, this is not a minor feature -- it may be the entire decision. Test these tools on your own actual boards. Vendor benchmarks are starting points, not conclusions.