Learn how constrained decoding guarantees JSON, regex, and schema compliance in LLMs. Explore performance trade-offs, model comparisons, and implementation tools for structured generation.
Learn how to slash LLM response times using streaming, continuous batching, and KV caching. A practical guide to improving TTFT and OTPS for production AI.
Speculative decoding accelerates large language models by pairing a fast draft model with a verifier model, cutting response times by up to 5x without losing quality. Used by AWS, Google, and Meta, it's now standard in enterprise AI.