Together Evaluations: Benchmark LLMs with LLM Judges
Action Required
Organizations can now rapidly assess and compare LLM performance, leading to more informed model selection and optimized deployments, ultimately improving the quality and reliability of their AI applications.
AI Impact Summary
Together Evaluations introduces a new framework for benchmarking LLMs using LLMs themselves as judges, offering a faster and more flexible alternative to traditional human annotation or algorithmic metrics. This capability allows businesses to quickly assess model quality for specific tasks, particularly useful for evaluating new open-source models like Kimi, Qwen, and GLM. The platform's customizable evaluation modes (classify, score, compare) and support for various LLM-as-judge models provide a powerful tool for optimizing LLM deployments and ensuring high-quality outputs.
Affected Systems
- Date
- Date not specified
- Change type
- capability
- Severity
- high