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ModelCap

Model decision surface

Compare AI models

Start with Ling-2.6-1T and Nex-N2-Mini, 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

Ling-2.6-1T vs Nex-N2-Mini

Live dataset updated 8/18/2026, 3:36:20 AM UTC

Open 1200×630 evidence receipt
Factual comparison of Ling-2.6-1T and Nex-N2-Mini
Field
Ling-2.6-1T

InclusionAI

ModelCap position#74#25
Index score36.063.5
EvidenceMeasured1 public benchmark observation across 1 boardEstimatedstart rank interpolated from the launch card's own comparison table against resolved catalogue peers, discounted for measured cross-lab optimism
Input / 1M$0.075$0.025
Output / 1M$0.625$0.10
Pricing statusfreshfresh
Context262K262K
Providers11
Weight accessAPI onlyOpen weights

Decision facts

  • Ling-2.6-1T is #74; Nex-N2-Mini is #25 on the same current language board.
  • Index scores are 36.0 for Ling-2.6-1T and 63.5 for Nex-N2-Mini.
  • Evidence differs: Ling-2.6-1T is Measured; Nex-N2-Mini is Estimated.
  • Listed output price per 1M tokens is $0.63 for Ling-2.6-1T and $0.10 for Nex-N2-Mini.
  • Published context is 262,144 tokens for Ling-2.6-1T and 262,144 for Nex-N2-Mini.
  • Weight access differs: Ling-2.6-1T is none; Nex-N2-Mini is open.

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.