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ModelCap

Model decision surface

Compare AI models

Start with Gemini 3.1 Pro Preview and Gemini 3.8 Flash, 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

Gemini 3.1 Pro Preview vs Gemini 3.8 Flash

Live dataset updated 10/18/2026, 4:49:00 AM UTC

Open 1200×630 evidence receipt
Factual comparison of Gemini 3.1 Pro Preview and Gemini 3.8 Flash
Field
ModelCap position#10#5
Index score81.183.5
EvidenceMeasured3 public benchmark observations across 3 boardsMeasured5 public benchmark observations across 5 boards
Input / 1M$2.00$0.825
Output / 1M$12.00$4.13
Pricing statusfreshfresh
Context1M1M
Providers22
Weight accessNo linked weightsNo linked weights

Decision facts

  • Gemini 3.1 Pro Preview is #10; Gemini 3.8 Flash is #5 on the same current language board.
  • Index scores are 81.1 for Gemini 3.1 Pro Preview and 83.5 for Gemini 3.8 Flash. 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 $12.00 for Gemini 3.1 Pro Preview and $4.13 for Gemini 3.8 Flash. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $10.00 for Gemini 3.1 Pro Preview versus $3.71 for Gemini 3.8 Flash. Gemini 3.8 Flash costs 62.9% 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 1,048,576 tokens for Gemini 3.1 Pro Preview and 1,048,576 for Gemini 3.8 Flash.

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.