Amazon Comprehend vs Stanford CoreNLP
No leader: the top candidate Amazon Comprehend has only 0.33 confidence (low), below the 0.35 needed to declare a winner. The attribute-by-attribute breakdown below, with a source and date on every value, is the honest way to compare them.
Capabilities
Feature-by-feature on the axes that matter for nlp apis. “-” means undocumented, not absent.
What each one is
The product in its own terms, so the numbers below have context.
Amazon Comprehend
A machine learning service that processes text to identify entities, sentiment, topics, and key phrases. It supports both standard pre-built models and custom models trained on your own data, with APIs for document processing in multiple formats.
Stanford CoreNLP
An open-source toolkit that analyzes text to extract linguistic features including word boundaries, grammatical tags, entities, dependency relationships, and semantic properties, supporting eight languages.
Pricing
List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.
Amazon Comprehend
From $0.0001 per unit (100 characters) for standard APIs. Free tier: 50K units per month for 12 months.
- Standard APIs (Pay-per-use)$0.0001 per unit (100 characters)
- Entity recognition
- Sentiment analysis
- Syntax analysis
- Key phrase extraction
- Language detection
- +5 more
- Custom Classification & Entities$3/hour training + $0.50/month management + $0.0003/unit inference
- Custom model training
- Custom entity extraction
- Custom text classification
- Model management
- Managed Endpoints (Synchronous)$0.0005 per second per Inference Unit
- Real-time synchronous inference
- Scalable throughput with multiple IUs
Platform & deployment
Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.
Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.