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ModelCap

Model decision surface

Compare AI models

Start with Qwen3 4B Instruct 2507 and Qwen3.5 4B, 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

Qwen3 4B Instruct 2507 vs Qwen3.5 4B

Live dataset updated 9/9/2026, 9:50:24 PM UTC

Open 1200×630 evidence receipt
Factual comparison of Qwen3 4B Instruct 2507 and Qwen3.5 4B
Field
ModelCap position#124#105
Index score32.439.5
EvidenceEstimatedpublisher-corpus-prior over 180 held-out anchors (18%); launch card against 2 resolved peers on 9 rows (82%); exceeds every named peer on 7 of 9 rows; no cross-lab optimism probe available; shrunk 4.1 up toward the measured corpusEstimatedpublisher-corpus-prior over 180 held-out anchors (28%); launch card against 3 resolved peers on 10 rows (73%); exceeds every named peer on 2 of 10 rows; optimism haircut 0.6 from cross-lab-probe; shrunk 4.3 up toward the measured corpus
Input / 1MUnavailableUnavailable
Output / 1MUnavailableUnavailable
Pricing statusunavailableunavailable
Context262K—
Providers00
Weight accessOpen weightsOpen weights

Decision facts

  • Qwen3 4B Instruct 2507 is #124; Qwen3.5 4B is #105 on the same current language board.
  • Index scores are 32.4 for Qwen3 4B Instruct 2507 and 39.5 for Qwen3.5 4B. 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.

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.