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ModelCap

Model decision surface

Compare AI models

Start with gemma 3n E2B it and Phi 3.5 mini instruct, 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

gemma 3n E2B it vs Phi 3.5 mini instruct

Live dataset updated 9/22/2026, 10:37:09 PM UTC

Open 1200×630 evidence receipt
Factual comparison of gemma 3n E2B it and Phi 3.5 mini instruct
Field
ModelCap position#182#186
Index score27.324.1
EvidenceInheritedfinetune of google/gemma-3n-E4B-it · finetune (100%)Estimatedglobal-corpus-prior over 209 held-out anchors (26%); launch card against 4 resolved peers on 6 rows (74%); exceeds every named peer on 1 of 6 rows; optimism haircut 0.67 from cross-lab-probe; shrunk 11.5 up toward the measured corpus
Input / 1MUnavailableUnavailable
Output / 1MUnavailableUnavailable
Pricing statusunavailableunavailable
Context——
Providers00
Weight accessGated accessOpen weights

Decision facts

  • gemma 3n E2B it is #182; Phi 3.5 mini instruct is #186 on the same current language board.
  • Index scores are 27.3 for gemma 3n E2B it and 24.1 for Phi 3.5 mini instruct. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
  • Evidence differs: gemma 3n E2B it is Inherited; Phi 3.5 mini instruct is Estimated.
  • Weight access differs: gemma 3n E2B it is gated; Phi 3.5 mini instruct 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.