Conduct comprehensive model suitability testing with Chemin Eval
Confidently assess LLM models with Chemin Eval to determine the model best for your use case and identify areas to fine-tune for excellence.
Pick your model backed by data analytics and human-led input
Harness the power of automated evaluation metrics with the insight of expert human reviewers for a 360° view of model suitability and ongoing performance.
Robust comparison between LLMs
Compare top-performing models with our intuitive, flexible interface:
- View model outputs side by side and quickly rank responses with intuitive buttons
- Add a question specific to your domain's use-case or prompt the AI for assistance
- Access a comprehensive, up-to-date list of models to ensure relevance
Customizable benchmarking criteria
Analyze how models perform on different settings for a balanced view:
- Adjust key parameters such as temperature, topP , and maximum tokens for a level playing field
- Break down evaluation based on tasks, modalities, or languages
- Randomize model selection and hide model names to reduce bias in evaluators
Comprehensive performance breakdown
Gain both quantitative metrics and qualitative insights to fully understand model behavior:
- Track real-world latency and generation speed to evaluate models' performance
- Analyze efficiency of outputs in terms of verbosity, balance, and conciseness
- Surface model biases and underlying behavior to diagnose and resolve performance issues
Collaborative model evaluation
Align understanding across teams by sharing feedback and insights
- Rank responses, explain reasoning, and suggest ideal outputs for the AI
- Export evaluation results for reporting or further analysis
- Distribute results quickly to accelerate learning and decision-making
Insights that drive model testing to business transformations
Make high-impact decisions anchored on the tenets of fairness, objectivity, and technical performance.
Strategic evaluation
Move quickly and decisively with comprehensive data to support selection of models that are grounded in real-world relevance instead of assumptions.
Fair and transparent
Remove hidden human biases with an unbiased framework of anonymized outputs to align teams in reaching a consensus of model fit.
Continuous improvement
Stay agile and monitor performance data, benchmarking against improved models to ensure your model is always up-to-date for users.
Maximize business impact with the right model
Select and validate models to align business objectives for now and the long term.