
gensim
Python developers can use gensim for topic modeling and related natural language processing tasks.

About gensim
gensim is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. It includes multicore implementations of LSA, LDA, Random Projections, HDP and word2vec, with streamed out-of-core processing and distributed computing for LSA and LDA.
The project is in stable maintenance mode and is not accepting new features, though bug and documentation fixes are still accepted. It depends on NumPy and no longer supports Python 2.7 in version 4.0.0 and later.
Key features
- Topic modelling, document indexing and similarity retrieval with large corpora
- Streamed out-of-core processing for corpora larger than RAM
- Multicore implementations of LSA, LDA, RP, HDP and word2vec
- Distributed LSA and LDA across a cluster of computers
- Plug in custom corpus or datastream via streaming API
- Extend with other Vector Space algorithms via transformation API
- Processes corpora larger than RAM through streamed, out-of-core handling
- Provides multicore implementations of common topic modelling algorithms
- Allows custom input streams and additional algorithms via APIs
- In stable maintenance mode and not accepting new features
- Does not support Python 2.7 in version 4.0.0 and later
- Depends on NumPy, which can require BLAS linking when built from source
gensim at a glance
- Category
- Development › Developer Tools
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
Guides for Developer Tools
gensim alternatives
Tools and sites you could use instead, ranked by how closely they match.
jSciPy provides Java scientific computing tools for signal processing, FFT, filtering, power spectral density, and DCT.
Machine learning pipelines can use whylogs, an open-source library for logging data quality and model performance.
Weights & Biases supports model training, fine tuning, and management from experimentation through production.
SynapseML provides distributed machine learning algorithms for Spark through its Python library.
mlxtend adds helper modules for Python data analysis and machine learning libraries.
The Geni project provides a Clojure dataframe library that runs on Apache Spark.
Popular in Developer Tools
Well-known listings from the same topic.
gensim FAQ
How do I install gensim?
How is gensim memory efficient if it is written in Python?
Does gensim support Python 2.7?
Tell us and an editor will check it.
Claim the listing and suggest updates yourself. An editor checks every claim first.













