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ModelCap

Model decision surface

Compare AI models

Start with Gemma 3 12B and Gemma 3 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

Gemma 3 12B vs Gemma 3 4B

Live dataset updated 9/22/2026, 9:31:46 PM UTC

Open 1200×630 evidence receipt
Factual comparison of Gemma 3 12B and Gemma 3 4B
Field
ModelCap position#160#186
Index score36.024.1
EvidenceMeasured2 public benchmark observations across 2 boardsMeasured2 public benchmark observations across 2 boards
Input / 1M$0.05$0.05
Output / 1M$0.15$0.10
Pricing statusfreshfresh
Context131K131K
Providers11
Weight accessGated accessGated access

Decision facts

  • Gemma 3 12B is #160; Gemma 3 4B is #186 on the same current language board.
  • Index scores are 36.0 for Gemma 3 12B and 24.1 for Gemma 3 4B. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
  • Both positions use Measured evidence.
  • Listed output price per 1M tokens is $0.15 for Gemma 3 12B and $0.10 for Gemma 3 4B. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $0.17 for Gemma 3 12B versus $0.15 for Gemma 3 4B. Gemma 3 4B costs 14.3% less in this scenario. This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the selected endpoint before budgeting.
  • Published context is 131,072 tokens for Gemma 3 12B and 131,072 for Gemma 3 4B.

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.