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ModelCap

Model decision surface

Compare AI models

Start with gemma 4 E4B it and Qwen3.5-9B, 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 Qwen3.5-9B

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

Open 1200×630 evidence receipt
Factual comparison of gemma 4 E4B it and Qwen3.5-9B
Field
ModelCap position#98#97
Index score41.141.1
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 corpusEstimatedpublisher-corpus-prior over 182 held-out anchors (30%); launch card against 3 resolved peers on 10 rows (70%); exceeds every named peer on 4 of 10 rows; optimism haircut 0.6 from cross-lab-probe; shrunk 3.7 up toward the measured corpus
Input / 1MUnavailable$0.10
Output / 1MUnavailable$0.15
Pricing statusunavailablefresh
Context—262K
Providers06
Weight accessOpen weightsOpen weights

Decision facts

  • gemma 4 E4B it is #98; Qwen3.5-9B is #97 on the same current language board.
  • Index scores are 41.1 for gemma 4 E4B it and 41.1 for Qwen3.5-9B. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
  • Both positions use Estimated evidence.
  • ModelCap currently lists 0 providers for gemma 4 E4B it and 6 for Qwen3.5-9B.

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.