Show HN: Optimizing LiteLLM with Rust – When Expectations Meet Reality (github.com)

Fast LiteLLM is a drop-in Rust acceleration layer for LiteLLM that claims 2–20x speedups across common server-side operations: 5–20x faster token counting (with batch processing), 3–8x faster request routing (lock-free data structures), 4–12x faster rate limiting (async-enabled), and 2–5x faster connection management. Installable via pip and activated simply by importing fast_litellm before litellm, it uses PyO3 to replace performance-critical Python code with Rust extensions (modules: core, tokens, connection_pool, rate_limiter) while preserving the original Python API. Prebuilt wheels mean Rust isn’t required to install; source builds use maturin and the Rust toolchain. This is significant because it offers an immediate, low-friction way to reduce latency and CPU overhead in LiteLLM deployments—helpful for scaling, cost reduction, and tighter real-time SLAs. The project emphasizes production readiness: feature flags, canary/percentage rollouts, runtime performance monitoring, automatic fallback to Python, type stubs, and comprehensive integration tests that run LiteLLM’s test suite with acceleration enabled. Technical choices like DashMap for lock-free concurrency and async-aware rate limiting make it suitable for high-concurrency environments. Developers should note the automatic monkeypatching approach may require validation in complex setups, but built-in monitoring and gradual rollout aim to mitigate risk.