fast-litellm vs LiteLLM: a Rust drop-in that delivers 3.2× faster connections and 42× less memory
fast-litellm is a Rust+PyO3 acceleration layer for LiteLLM, the LLM gateway. Same Python API; faster connection pool, faster rate limiter, much lower memory.
$ pip install fast-litellm fast-litellm is a Rust-backed drop-in for
LiteLLM. Same API, faster hot paths.
Install: pip install fast-litellm.
3.2× faster connection pool acquisition (0.97ms vs 3.1ms, 100-iter median, 50 concurrent agents).
fast-litellm vs LiteLLM: the facts
3.2× faster connection pool acquisition (0.97ms vs 3.1ms, 100-iter median, 50 concurrent agents).
Pure-Python connection pool; bounded by the GIL under high concurrency.
42× less memory for high-cardinality rate limiting (0.055MB vs 2.3MB for 10K entries).
~232 bytes of Python object overhead per rate-limit entry.
1.6-1.7× faster token counting on large documents.
Bounded by Python string traversal.
Zero code changes: `import fast_litellm` before `import litellm`.
Direct Python import.
MIT licensed, prebuilt wheels for Linux, macOS, Windows (Python 3.8-3.13).
MIT licensed.
Benchmarks
Reproduction instructions in the project README. Numbers measured on AMD Ryzen 9 7950X, 64GB DDR5, NVMe SSD, Python 3.12.
| Metric | fast-litellm | LiteLLM |
|---|---|---|
| Connection pool acquisition (50 concurrent) | 0.97ms | 3.1ms |
| Rate-limit memory (10K entries) | 0.055MB | 2.3MB |
| Token counting (large doc) | 7.3ms | 12.4ms |
When to use fast-litellm
- You run LiteLLM in production with 50+ concurrent agent requests.
- You see OOM crashes in your LiteLLM rate-limiter when cardinality climbs.
- You want a 2-3× win with zero code changes.
When NOT to use fast-litellm
- You only run LiteLLM in a single-process script with <10 RPS — the overhead of importing fast-litellm is not worth it.
- You use a non-Python LiteLLM client (e.g. the Go or Node proxy) — fast-litellm is the Python client.
Frequently asked questions
Does fast-litellm work with all LiteLLM providers?
Yes. fast-litellm monkey-patches LiteLLM's connection pool, rate limiter, and token counter — all provider-agnostic code paths. The acceleration applies regardless of which providers (OpenAI, Anthropic, Bedrock, Vertex, vLLM, etc.) you route to.
Will fast-litellm break my existing LiteLLM code?
No. fast-litellm uses automatic monkeypatching with version detection and silent fallback. If the installed LiteLLM version is incompatible, the library reverts to the original implementation with no error.
Do I need to install Rust to use fast-litellm?
No. fast-litellm ships prebuilt binary wheels for Linux (x86_64, aarch64), macOS (Intel, Apple Silicon), and Windows. `pip install fast-litellm` and you're done.
How does fast-litellm compare to LiteLLM's built-in caching?
Caching reduces the number of LLM calls; fast-litellm makes the calls you do make faster. They are complementary: turn both on. fast-litellm is particularly impactful on the cold path (cache miss + connection acquisition).
Is fast-litellm production-safe?
Yes — it is MIT licensed, has version-detected fallback, and the Rust core is built with safe Rust. It is used in production by Neul Labs and a number of design partners.