← AI Recommendation IndexOpen Data · Rolling 4-week window

AWS vs DeepL

A fact-by-fact comparison of AWS and DeepL — sourced and dated — plus the part no generic comparison shows: which one AI assistants actually recommend more, engine by engine.

Measured by Orbatormethodology owner Henrik Tellewindow ends Sep 6, 2026

What AI recommends — by engine

Recommendation share = the % of sampled AI answers, over a 4-week rolling window, that recommend each product. Higher is better.

CLAUDE

AWS

2.5%

DeepL

0.4%

GEMINI

AWS

4.1%

DeepL

0.4%

GROK

AWS

4.4%

DeepL

0.6%

CHATGPT

AWS

2%

DeepL

0.3%

PERPLEXITY

AWS

1.8%

DeepL

0.3%

The facts — sourced & dated

aws.amazon.com

Features

  • Private PricingSource · Verified Sep 5, 2026
  • over 240 comprehensive servicesSource · Verified Sep 5, 2026
  • pay-as-you-go approach for pricingSource · Verified Sep 5, 2026
  • Savings PlansSource · Verified Sep 5, 2026
  • volume based discountsSource · Verified Sep 5, 2026
  • AWS Pricing CalculatorSource · Verified Sep 5, 2026
deepl.com

Features

  • Translate textSource · Verified Sep 5, 2026
  • Translate filesSource · Verified Sep 5, 2026
  • Translate speechSource · Verified Sep 5, 2026
  • Real-time voice translationSource · Verified Sep 5, 2026
  • GlossariesSource · Verified Sep 5, 2026
  • RulesSource · Verified Sep 5, 2026
  • ClarifySource · Verified Sep 5, 2026
  • Style and tone adaptationsSource · Verified Sep 5, 2026

Integrations

  • Microsoft WordSource · Verified Sep 5, 2026
  • Google WorkspaceSource · Verified Sep 5, 2026
  • Microsoft 365Source · Verified Sep 5, 2026
  • AI agentsSource · Verified Sep 5, 2026

Platforms

  • Browser extensionSource · Verified Sep 5, 2026
  • APISource · Verified Sep 5, 2026
  • Desktop appSource · Verified Sep 5, 2026
  • Mobile appsSource · Verified Sep 5, 2026

AWS vs DeepL — FAQ

Does AI recommend AWS or DeepL more?

AWS is recommended more often: it appears in 2.8% of sampled AI answers versus 0.4% for DeepL, measured across the live AI engines over a rolling 4-week window.

Which AI engines were used to compare AWS and DeepL?

Recommendation share is measured on CLAUDE, GEMINI, GROK, CHATGPT, PERPLEXITY using neutral, buyer-shaped prompts (no product names), aggregated over a 4-week rolling window. See the methodology for prompt design and sample sizes.

Own one of these products? Claim your profile to keep its facts accurate.

Recommendation share and entity resolution follow the Index methodology. Facts are sourced from each vendor's own pages and re-verified periodically. Customer status does not affect measurement. Free to use with attribution to orbator.io.

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