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LLMTest is a platform for building and optimizing AI features with large language models. It helps teams ship prompts through a production workflow, monitor real user traffic, and improve outputs over time with automated prompt optimization, model benchmarking, and fallback routing.
The app supports both early-stage testing and live production use. In the build phase, it can generate test prompts and run benchmarks across a large set of models to help compare output quality, latency, and cost before deployment. In the scaling phase, it monitors real traffic, detects performance drift, and identifies better or cheaper models for specific flows. It also includes automatic failover so requests can route to alternative models when a primary API is unavailable or rate-limited.
LLMTest also provides cost tracking by flow, AI quality evaluation, and integration with developer tools such as IDEs and MCP-compatible environments. Its features are designed to help users manage LLM prompt optimization, model selection, AI workflow reliability, and per-request cost control in a single tool.
Website: llmtest.io
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