We Tested 30 LLM APIs with 150 Real Calls — 42.7% Failed (And Why That's Good News)
A recent test of 30 LLM APIs revealed a 42.7% failure rate, though most were due to model deprecations or rate limiting. When accounting for infrastructure issues like rate limits, the actual failure rate is closer to 4%, aligning with industry reports. The study highlighted significant instability with models hosted on GitHub, where several models were deprecated or frequently hit rate limits, necessitating fallback strategies for production use. NeuralBridge's SDK demonstrated a 100% self-healing rate for recoverable failures, potentially saving substantial energy and reducing carbon emissions. AI
IMPACT Highlights critical infrastructure instability in LLM APIs, impacting production deployments and suggesting a need for self-healing solutions.