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ModelCap

Model decision surface

Compare AI models

Start with gemma 4 E4B it and Ling 3.0 tiny, 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 4 E4B it vs Ling 3.0 tiny

Live dataset updated 9/9/2026, 8:46:14 PM UTC

Open 1200×630 evidence receipt
Factual comparison of gemma 4 E4B it and Ling 3.0 tiny
Field
Ling 3.0 tiny

InclusionAI

ModelCap position#98#95
Index score41.141.7
EvidenceEstimatedpublisher-corpus-prior over 182 held-out anchors (7%); launch card against 3 resolved peers on 5 rows (93%); no cross-lab optimism probe available; shrunk 1.7 up toward the measured corpusMeasured1 public benchmark observation across 1 board
Input / 1MUnavailableUnavailable
Output / 1MUnavailableUnavailable
Pricing statusunavailableunavailable
Context——
Providers00
Weight accessOpen weightsOpen weights

Decision facts

  • gemma 4 E4B it is #98; Ling 3.0 tiny is #95 on the same current language board.
  • Index scores are 41.1 for gemma 4 E4B it and 41.7 for Ling 3.0 tiny. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
  • Evidence differs: gemma 4 E4B it is Estimated; Ling 3.0 tiny is Measured.

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.