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Model decision surface

Compare AI models

Start with Codestral 2508 and Mistral Nemo, 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

Codestral 2508 vs Mistral Nemo

Live dataset updated 8/17/2026, 11:13:20 PM UTC

Open 1200×630 evidence receipt
Factual comparison of Codestral 2508 and Mistral Nemo
Field
Codestral 2508

Mistral AI

Mistral Nemo

Mistral AI

ModelCap position#226#227
Index score0.00.0
EvidenceEstimatedpublisher corpus prior · leave-one-anchor-out calibratedEstimatedpublisher corpus prior · leave-one-anchor-out calibrated
Input / 1M$0.30$0.019
Output / 1M$0.90$0.03
Pricing statusfreshfresh
Context256K131K
Providers14
Weight accessAPI onlyOpen weights

Decision facts

  • Codestral 2508 is #226; Mistral Nemo is #227 on the same current language board.
  • Index scores are 0.0 for Codestral 2508 and 0.0 for Mistral Nemo.
  • Both positions use Estimated evidence.
  • Listed output price per 1M tokens is $0.90 for Codestral 2508 and $0.03 for Mistral Nemo.
  • Published context is 256,000 tokens for Codestral 2508 and 131,072 for Mistral Nemo.
  • Weight access differs: Codestral 2508 is none; Mistral Nemo is open.
  • ModelCap currently lists 1 providers for Codestral 2508 and 4 for Mistral Nemo.

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.