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ModelCap

Model decision surface

Compare AI models

Start with Mercury 2.5 and MiniMax-01, 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

Mercury 2.5 vs MiniMax-01

Live dataset updated 9/22/2026, 10:37:09 PM UTC

Open 1200×630 evidence receipt
Factual comparison of Mercury 2.5 and MiniMax-01
Field
Mercury 2.5

Inception Labs

MiniMax-01

MiniMax

ModelCap position#135#134
Index score40.841.2
EvidenceEstimatedglobal-corpus-prior over 209 held-out anchors (21%); opens from measured predecessor inception/mercury-2 (79%); shrunk 4.4 up toward the measured corpusEstimatedpublisher-corpus-prior over 209 held-out anchors (44%); launch card against 2 resolved peers on 4 rows (56%); optimism haircut 6.45 from cross-lab-probe; shrunk 8.3 up toward the measured corpus
Input / 1M$0.04$0.20
Output / 1M$0.15$1.10
Pricing statusfreshfresh
Context260K1M
Providers11
Weight accessAPI onlyLicense unverified

Decision facts

  • Mercury 2.5 is #135; MiniMax-01 is #134 on the same current language board.
  • Index scores are 40.8 for Mercury 2.5 and 41.2 for MiniMax-01. 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.
  • Listed output price per 1M tokens is $0.15 for Mercury 2.5 and $1.10 for MiniMax-01. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $0.15 for Mercury 2.5 versus $0.95 for MiniMax-01. Mercury 2.5 costs 83.7% 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 260,000 tokens for Mercury 2.5 and 1,000,192 for MiniMax-01.
  • Weight access differs: Mercury 2.5 is none; MiniMax-01 is unknown.

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.