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Choose an AI model

Compare versions, quality and cost per accepted result.

Use a copy with fictional data. The exercise workbook, when offered, includes an answer sheet; other files are templates to fill in.

AI models in October 2026: OpenAI, Gemini, Claude, Meta, Grok, Mistral and DeepSeek

LearnIA — teaching template — 2026-10-14

Use fictional data for the first trial. Adapt this template to your context and verify the result before using it.

Brief to complete

  • Objective and intended decision :
  • Audience and context :
  • Documents, versions and sources :
  • Constraints and boundaries :
  • Expected output format :
  • Information to confirm :
  • Reviewer :

Starter instruction

Help me compare models for a specific task. Define fictional test inputs, an expected result, five verifiable criteria and one critical failure. Create a table for model version, tools, reasoning settings, cost, total duration and corrections. Do not claim to have run the trials or choose a winner before results exist.

Quality review

  • Every candidate receives the same task and inputs.
  • Versions and tools are recorded.
  • Critical errors block acceptance.
  • Costs include retries and review.

Verification log

ItemSource or calculationResultCorrection

Approval and next step

  • Remaining errors :
  • Assumptions to resolve :
  • Retained version :
  • Next action and owner :

Full tutorial, example and sources : https://learn-prompting.fr/blog/modeles-ia-octobre-2026-comparatif

This resource prepares a draft; it is not a certification, a grading decision, legal advice or a guarantee of results.