What is Fast-LangGraph?
Fast-LangGraph reimplements parts of LangGraph in Rust and exposes them to Python. One mode patches LangGraph at start-up, through an environment variable or a function call, to reuse a thread pool and apply channel writes in Rust. The other mode is explicit: a Rust-backed SQLite checkpointer, a fast state-merge function, an LLM response cache decorator and a profiler.
It is made by Neul Labs, which publishes similar accelerators for LiteLLM, CrewAI and Axolotl. The package is on PyPI and crates.io, needs Python 3.9 or later, and is MIT-licensed. It is an add-on, not a fork: your graphs, nodes and edges stay plain LangGraph.
Is Fast-LangGraph worth it?
Fast-LangGraph's 700x figure needs reading carefully before it shapes a decision. In the project's own BENCHMARK.md, the 737x result compares Rust checkpoint serialisation of a 235.5KB state with Python's deepcopy, not with LangGraph's own checkpointers. The end-to-end number is more modest: a simulated 20-node graph over 50 iterations ran 2.77x faster. The same file shows the Rust LastValue channel at 317 ns per update against 51 ns in Python, slower by about six times, which the README concedes when it says simple dict operations are already fast in Python.
That leaves a narrow but genuine case. Agents that carry large state and checkpoint every step spend real time copying it, and the automatic patch is low-risk to try: set FAST_LANGGRAPH_AUTO_PATCH=1 and measure. The @cached decorator is a plain in-process memo for identical prompts, which a production system usually gets from a shared cache or the provider's prompt caching instead.
Adoption is the larger concern. The repository has 27 stars, two contributors and no forks, and PyPI counted 59 downloads in the last month. The last release, v0.1.15, came on 6 May 2026, and the newest commits in July were documentation; five Dependabot pull requests, including a langgraph-checkpoint bump to 4.1.1, sit unmerged. A monkey-patch on a framework that ships as often as LangGraph needs someone tracking each release.
Treat it as a profiling aid and a source of ideas rather than a dependency: run its GraphProfiler, and if checkpoint copying really dominates, a Postgres checkpointer or a smaller state schema may get most of the gain without a Rust extension in the stack.
Where it earns its place
A backend engineer running a LangGraph research agent with 200KB of state
Find out why each step is slow before rewriting anything
Wrap one run in GraphProfiler.profile_run() and print the report; if checkpointing dominates, try RustSQLiteCheckpointer in a branch. No cost beyond an afternoon.
A team lead evaluating framework add-ons for a production agent
Decide whether a third-party patch is safe to ship
Pin the LangGraph version, enable FAST_LANGGRAPH_AUTO_PATCH=1 in staging and compare latency with and without it; the open Dependabot backlog is the signal to watch before upgrading LangGraph.
Before you commit
- Setup
- pip install fast-langgraph or uv add fast-langgraph, then either the environment variable or fast_langgraph.shim.patch_langgraph() at start-up; prebuilt wheels avoid a Rust toolchain.
- Integrations
- LangGraph only, for Python 3.9+; a Rust crate is published for direct use. Neul Labs makes sibling packages for LiteLLM, CrewAI and Axolotl.
- Data and privacy
- Runs in-process; the SQLite checkpointer writes to a local file you name. MIT licence, no service attached.
- Limits
- Two contributors; five unmerged dependency pull requests; speedups depend on state size and shrink to about 2.8x for typical graphs by the README's own estimate.
What’s good
- One environment variable turns on the automatic patch
- Large-state checkpoint serialisation is far faster than deepcopy in its benchmarks
- Built-in profiler helps find where a graph spends time
- MIT licence, on PyPI and crates.io
What’s not
- Headline speedups are measured against deepcopy, not LangGraph's checkpointers
- Its own benchmark shows some channel operations slower than Python
- 27 stars, two contributors and 59 downloads in a month
- Monkey-patching risks breaking on new LangGraph releases
Best for
LangGraph teams with large, frequently checkpointed state who want to measure whether serialisation is their bottleneck.
Fast-LangGraph alternatives
Fast-LangGraph: common questions
- Is Fast-LangGraph worth it?
- A real idea with headline numbers that compare against the wrong baseline, maintained by two people and installed by almost nobody. We rate it 3.0 out of 5.
- How much does Fast-LangGraph cost?
- Free and open source under the MIT licence.
- What are the downsides of Fast-LangGraph?
- Headline speedups are measured against deepcopy, not LangGraph's checkpointers; its own benchmark shows some channel operations slower than Python; 27 stars, two contributors and 59 downloads in a month; monkey-patching risks breaking on new LangGraph releases.
- Who is Fast-LangGraph best for?
- LangGraph teams with large, frequently checkpointed state who want to measure whether serialisation is their bottleneck.
- Is Fast-LangGraph safe for company data?
- Runs in-process; the SQLite checkpointer writes to a local file you name. MIT licence, no service attached.
- What are the best Fast-LangGraph alternatives?
- The closest alternatives we have reviewed are LangGraph.
Answers checked Nov 3, 2026.