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ModelCap

Model decision surface

Compare AI models

Start with Fara1.5 4B and Nemotron Cascade 2 30B A3B, 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

Fara1.5 4B vs Nemotron Cascade 2 30B A3B

Live dataset updated 9/10/2026, 12:32:36 AM UTC

Open 1200×630 evidence receipt
Factual comparison of Fara1.5 4B and Nemotron Cascade 2 30B A3B
Field
Fara1.5 4B

Microsoft

ModelCap position#115#112
Index score37.138.3
EvidenceInheritedfinetune of Qwen/Qwen3.5-4B · finetune (100%)Estimatedpublisher-corpus-prior over 183 held-out anchors (56%); launch card against 3 resolved peers on 11 rows (44%); exceeds every named peer on 3 of 11 rows; optimism haircut 0 from cross-lab-probe; shrunk 4.8 up toward the measured corpus
Input / 1MUnavailableUnavailable
Output / 1MUnavailableUnavailable
Pricing statusunavailableunavailable
Context——
Providers00
Weight accessOpen weightsRestricted license

Decision facts

  • Fara1.5 4B is #115; Nemotron Cascade 2 30B A3B is #112 on the same current language board.
  • Index scores are 37.1 for Fara1.5 4B and 38.3 for Nemotron Cascade 2 30B A3B. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
  • Evidence differs: Fara1.5 4B is Inherited; Nemotron Cascade 2 30B A3B is Estimated.
  • Weight access differs: Fara1.5 4B is open; Nemotron Cascade 2 30B A3B is restricted.

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.