In my experience with AI coding, very large context windows aren't useful in practice. Every model seems to get confused when you feed them more than ~25-30k tokens. The models stop obeying their system prompts, can't correctly find/transcribe pieces of code in the context, etc.
Developing aider, I've seen this problem with gpt-4o, Sonnet, DeepSeek, etc. Many aider users report this too. It's perhaps the #1 problem users have, so I created a dedicated help page.
Very large context may be useful for certain tasks with lots of "low value" context. But for coding, it seems to lure users into a problematic regime.
Recent articles
- The last six months in LLMs, illustrated by pelicans on bicycles - 6th June 2025
- Tips on prompting ChatGPT for UK technology secretary Peter Kyle - 3rd June 2025
- How often do LLMs snitch? Recreating Theo's SnitchBench with LLM - 31st May 2025