Structured Outputs at Scale: Three Approaches, One Clear Winner

1. 1Apply constrained decoding to your LLM model for structured outputs
2. 2Compare the performance of constrained decoding with prompt engineering
3. 3Test the reliability and speed of constrained decoding
4. 4Configure your model to use constrained decoding for production
5. 5Evaluate the results of constrained decoding against your baseline

Data scientists and machine learning engineers can benefit from this approach to improve the efficiency of their LLM-based systems

💡 Constrained decoding is a more reliable and faster approach than prompt engineering for generating structured outputs

💡 Constrained decoding beats prompt engineering for structured outputs in reliability and speed!