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ModelCap

Model decision surface

Compare AI models

Start with Perceptron Mk1 and Relace Apply 3, or choose any two current ranked language models. Compare capability evidence, price, context, provider availability, and weight access without pretending one field decides every use case.

Current public data

Perceptron Mk1 vs Relace Apply 3

Live dataset updated 8/17/2026, 11:13:20 PM UTC

Open 1200×630 evidence receipt
Factual comparison of Perceptron Mk1 and Relace Apply 3
Field
Perceptron Mk1

Perceptron

ModelCap position#151#154
Index score22.522.5
EvidenceEstimatedglobal corpus prior · leave-one-anchor-out calibratedEstimatedglobal corpus prior · leave-one-anchor-out calibrated
Input / 1M$0.15$0.85
Output / 1M$1.50$1.25
Pricing statusfreshfresh
Context33K256K
Providers11
Weight accessAPI onlyAPI only

Decision facts

  • Perceptron Mk1 is #151; Relace Apply 3 is #154 on the same current language board.
  • Index scores are 22.5 for Perceptron Mk1 and 22.5 for Relace Apply 3.
  • Both positions use Estimated evidence.
  • Listed output price per 1M tokens is $1.50 for Perceptron Mk1 and $1.25 for Relace Apply 3.
  • Published context is 32,768 tokens for Perceptron Mk1 and 256,000 for Relace Apply 3.

These are separate published fields, not a synthetic winner. ModelCap does not collapse price, access, context, and capability evidence into a hidden recommendation score.

Each comparison page is a permanent, shareable URL with the same live figures as this tool: ModelCap Index position, API pricing, context window, provider count, weight access and every shared benchmark board.