LLMTest launches model picks, fallbacks

This is less about “testing LLMs” and more about making LLM apps survivable in production. The best hook is the fallback layer: model selection is useful, but automatic recovery from outages and malformed output is what turns a nice tool into infrastructure.

• –Real-prompt benchmarking plus an AI judge is the right way to avoid overfitting to benchmark theater.
• –MCP support is a smart distribution move because it puts optimization directly inside the workflow builders already use.
• –The weekly autopilot angle is compelling, but it raises the bar on safety gates, rollback quality, and trust.
• –The product sits in a crowded lane with OpenRouter, liteLLM, Langfuse, and Helicone, so differentiation depends on how well the automation actually works.
• –The pricing pitch is straightforward: no monthly fee, pay only on usage, and let the platform earn its keep by cutting model waste.