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Why Continuous Batching Made My LLM Inference Engine Slower

This story is from 2026-10-11. It is preserved in the archive; the latest stories are on the live feed.

I had been adding optimizations to mini-vllm-rs , my Rust LLM inference engine for macOS, including prefix caching and speculative decoding. Continuous batching looked like the next easy win. Process requests together, reuse model weights across more tokens, and watch throughput climb. What could g…

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  1. 2026-10-11 22:16 · DEV Community — AI
    Why Continuous Batching Made My LLM Inference Engine Slower

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