Calmkeep significantly outperforms Claude in consistency testing, achieving 85% accuracy on code tasks and perfect 100% on legal documents versus Claude's 50-60%.

Calmkeep demonstrates superior performance in a 25-turn benchmark test, maintaining 85% accuracy on code generation compared to Claude's 60%

Legal document handling shows the widest performance gap, with Calmkeep achieving 100% accuracy versus Claude's 50%

The comparison highlights concerns about LLM drift, suggesting consistency degrades differently across model types over extended interaction sequences