Context Rot: How increasing input tokens impacts LLM performance

I work on research at Chroma, and I just published our latest technical report on context rot.

TLDR: Model performance is non-uniform across context lengths, including state-of-the-art GPT-4.1, Claude 4, Gemini 2.5, and Qwen3 models.

This highlights the need for context engineering. Whether relevant information is present in a model’s context is not all that matters; what matters more is how that information is presented.

Here is the complete open-source codebase to replicate our results: https://github.com/chroma-core/context-rot


Comments URL: https://news.ycombinator.com/item?id=44564248

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https://research.trychroma.com/context-rot

Vytvořeno 5h | 14. 7. 2025 22:20:16


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