A study quantified how large context windows degrade LLM performance on coding tasks using GPT-5.6 Sol and Claude Opus 5. GPT-5.6 Sol showed significant performance drops at 250k+ tokens regardless of context relevance, while Claude Opus 5 only degraded when context was task-related. The models use different tokenizers, requiring normalization to UTF-8 MB for fair comparison.