I've been building a product around AI-powered reading (more on that later) and wanted to share findings on summarization quality across major LLMs.
Tested with 50 articles across news, research papers, blog posts, and technical docs:
Claude (Sonnet/Haiku):
- Best at preserving nuance and avoiding oversimplification
- Strongest at academic content
- Excellent for "explain this without losing the point"
GPT-4:
- Fastest summaries, often most concise
- Sometimes drops important context
- Good for news, weaker on academic
Gemini:
- Strongest source citations
- Tends to add information not in the original
- Good for factual but careful with creative content
Most surprising finding: bias detection accuracy. Claude flagged loaded language and framing in 78% of test articles correctly. GPT 64%. Gemini 51%.
Anyone else doing similar comparisons? Would love to hear what you're seeing
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