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ModelCap

Model decision surface

Compare AI models

Start with Gemma 3 27B and Mercury 2.5, 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 27B vs Mercury 2.5

Live dataset updated 9/10/2026, 1:00:55 AM UTC

Open 1200×630 evidence receipt
Factual comparison of Gemma 3 27B and Mercury 2.5
Field
Mercury 2.5

Inception Labs

ModelCap position#119#117
Index score35.937.1
EvidenceMeasured3 public benchmark observations across 3 boardsEstimatedglobal-corpus-prior over 183 held-out anchors (22%); opens from measured predecessor inception/mercury-2 (79%); shrunk 4.5 up toward the measured corpus
Input / 1M$0.08$0.04
Output / 1M$0.45$0.15
Pricing statusfreshfresh
Context131K260K
Providers41
Weight accessGated accessAPI only

Decision facts

  • Gemma 3 27B is #119; Mercury 2.5 is #117 on the same current language board.
  • Index scores are 35.9 for Gemma 3 27B and 37.1 for Mercury 2.5. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
  • Evidence differs: Gemma 3 27B is Measured; Mercury 2.5 is Estimated.
  • Listed output price per 1M tokens is $0.45 for Gemma 3 27B and $0.15 for Mercury 2.5. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $0.39 for Gemma 3 27B versus $0.15 for Mercury 2.5. Mercury 2.5 costs 59.7% 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 27B and 260,000 for Mercury 2.5.
  • Weight access differs: Gemma 3 27B is gated; Mercury 2.5 is none.
  • ModelCap currently lists 4 providers for Gemma 3 27B and 1 for Mercury 2.5.

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.