# Gensim Reviews **Vendor:** RaRe Consulting **Category:** [Natural Language Understanding (NLU) Software](https://www.g2.com/categories/natural-language-understanding-nlu) **Average Rating:** 4.4/5.0 **Total Reviews:** 15 ## About Gensim Gensim is a Python library that analyze plain-text documents for semantic structure and retrieve semantically similar document. ## Gensim Reviews ### 1. Document Indexing and retrieval **Rating:** 5.0/5.0 stars **Reviewed by:** Naresh R. | Enterprise Solution Architect, Small-Business (50 or fewer emp.) **Reviewed Date:** August 08, 2023 **What do you like best about Gensim?** INdexing and retrival of indexed data in frequent manner **What do you dislike about Gensim?** Server cost is more need to have good explosure on Python **What problems is Gensim solving and how is that benefiting you?** Quick document indexing and pulling matched records when needed by passing matching key words ### 2. Perfect package for NLP folks! **Rating:** 5.0/5.0 stars **Reviewed by:** KUNJAN M. | Freelancing, Small-Business (50 or fewer emp.) **Reviewed Date:** July 15, 2021 **What do you like best about Gensim?** Best tools for unsupervised learning, Topic and language modeling, document indexing, similarity retrieval with large corpora, Vector Space algorithms, and deep neural network supplementary tools such as NLTK, Keras, word2vec, FastText, etc. Compiled models, conda integration, API for maximizing the computations without depending on the high computational power. Visualization and model analysis is also provided that helps while developing the customized neural network models. **What do you dislike about Gensim?** Optimized for platform independence but could be hectic to manage the codebase since the Gensim dependencies are separate from the independent stand-alone packages like TensorFlow, Keras, etc. **Recommendations to others considering Gensim:** Must adapt to use the Gensim package if working on the NLP topic modeling with platform independence, fast computations, distributed computing support, and supportive community to debug and solve the problems occurring during the implementation. **What problems is Gensim solving and how is that benefiting you?** Availability of word embeddings, compiled models, their methods, and documentation are the benefits. I found bit hectic while working on FastText since the separate FastText package is available and it is easy to follow their guide than Gensim. Working great with the conda installation. However, if installed separately, sometimes standalone TensorFlow and Numpy versions compatibility issues occurred. ### 3. Easy to learn and implement library **Rating:** 4.0/5.0 stars **Reviewed by:** Aishwarya M. | Data Analyst, Small-Business (50 or fewer emp.) **Reviewed Date:** July 14, 2021 **What do you like best about Gensim?** I have used this library for topic modelling the unstructured text data. As compared to other libraries I have tested genism works super fast. Another thing I like the most about its ease of implementation if you read the documentation. Also, their pre-train corpus is useful if you focus on one domain. **What do you dislike about Gensim?** Since it's a prebuild library sometimes it's hard to find the things that happened at the backend. Its something like a black box. **What problems is Gensim solving and how is that benefiting you?** I solved the categorization of unstructured data problem with Gensim. It was really messed up data and with topic modelling, it was easy to cluster the documents and find out the pattern of each. Topic modelling part was easy with gensim. ### 4. Fast library for vector embeddings **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** June 23, 2021 **What do you like best about Gensim?** - Easier implementation - Lot of optional parameters to configure - Feasibility to develop many types - word2vec, fastext, etc - Easier model building, updating, saving in a single line of code **What do you dislike about Gensim?** - library should have been updated to work with the latest embeddings using transfer learning like bert/Albert. orlese sooner it could become outdated without recent developments **Recommendations to others considering Gensim:** Its a good library to work with NLP and apply different word embeddings in your usecases. Definitely a good go for NLP scientists **What problems is Gensim solving and how is that benefiting you?** Problems solved: - Building Custom Word2vec model & fastext model - Re-Use public available word embeddings for our usecases Benefits: - Faster training - Very accurate results of semantic meaning of words and phrases - Multiple approaches like skip-gram and cbow ### 5. Gensim for NLP **Rating:** 4.5/5.0 stars **Reviewed by:** Nikhil J. | Sr. Cloud Architect | AI/ML Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** June 25, 2021 **What do you like best about Gensim?** Gensim is one of the best NLP libraries using which one can train and build NLP models with ease along with high accuracy. **What do you dislike about Gensim?** Gensim is best suited for NLP related tasks only and not for wide array of Machine learning tasks. For other use cases, one should make use of other libraries as suited. **Recommendations to others considering Gensim:** Easy to use, super community and documentation. **What problems is Gensim solving and how is that benefiting you?** I've worked on Topic Modeling use cases in particular using Gensim. This is primarily for Clustering of large documents/articles. ### 6. Review from both academic and industry view point **Rating:** 5.0/5.0 stars **Reviewed by:** Annamalai N. | Machine Learning Scientist, Small-Business (50 or fewer emp.) **Reviewed Date:** July 15, 2021 **What do you like best about Gensim?** Gensim's word embedding models and NLP pipelines **What do you dislike about Gensim?** Inability to use State-of-the-art (SOTA) models such as Transformers Inability to use GPUs **What problems is Gensim solving and how is that benefiting you?** I have extensively used Word embeddings models (with Cython). I have ported them to do graph embedding. In fact, my most cited paper "graph2vec" uses Gensim to build graph embeddings ### 7. Easy to use, Good Documentation, Less Training time and Decent Results **Rating:** 4.5/5.0 stars **Reviewed by:** Tanmay K. | Data Scientist, Small-Business (50 or fewer emp.) **Reviewed Date:** July 15, 2021 **What do you like best about Gensim?** Less Training time with decent results. Good for creating a custom vocabulary **What do you dislike about Gensim?** Need to preprocess the text particularly stemming/ lemmatization to reduce vocab size. This does not help in cases where you need words in their original form **What problems is Gensim solving and how is that benefiting you?** We are using this for creating custom insurance industry specific vocabulary ### 8. Integral part of my team’s activities **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Financial Services | Enterprise (> 1000 emp.) **Reviewed Date:** August 10, 2021 **What do you like best about Gensim?** I work in an NLP based team and we have all been frequently using Gensim to serve the needs of several projects. Word2vec, Doc2vec and LDA have been life savers **What do you dislike about Gensim?** Although I've been using Gensim for a while now, I haven't particularly found anything to be a downside yet. **What problems is Gensim solving and how is that benefiting you?** I work with topic modelling tasks and text classification tasks. Gensim’s documentation and community support have been more very helpful ### 9. Makes life easy **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Medical Devices | Small-Business (50 or fewer emp.) **Reviewed Date:** August 04, 2021 **What do you like best about Gensim?** I have mostly worked with preprocessing tools from Gensim. It was simple to implement and compaer results with different tools like word2vec, gensim, etc **What do you dislike about Gensim?** It's been a while. Don't remember what I disliked **What problems is Gensim solving and how is that benefiting you?** I used it to solve the prediction problem of mortality in diabetic patients from clinical notes ### 10. Text segmentation with Gensim **Rating:** 4.0/5.0 stars **Reviewed by:** Bhavesh P. | Quantitative Analyst, Small-Business (50 or fewer emp.) **Reviewed Date:** June 17, 2021 **What do you like best about Gensim?** Gensim provides pre-trained contextual vectors **What do you dislike about Gensim?** More variety of vector dimensions can be offered for pre-trained vectors. **What problems is Gensim solving and how is that benefiting you?** I was solving a text segmentation of subtitles. I have created features out ot text data using Gensim ### 11. Great library for NLP-related tasks **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Mid-Market (51-1000 emp.) **Reviewed Date:** June 18, 2021 **What do you like best about Gensim?** A great library for NLP-related tasks from preprocessing to training. You can find almost everything there. I have worked on LDA using gensim, word2vec, you can use n-grams, and so much more. **What do you dislike about Gensim?** Previously didn't like the documentation but they have fixed that as well. Easier to read. **What problems is Gensim solving and how is that benefiting you?** Topic Modelling. Similarity Search Could find everything in one place. Even have their own algorithms for vectorization like Doc2Vec. ### 12. text classification **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** June 19, 2021 **What do you like best about Gensim?** It is a great library for the text classification **What do you dislike about Gensim?** I didn't found any drawbacks. I used it 3 years ago **Recommendations to others considering Gensim:** go through the documentation properly. It is not only used for text classification. **What problems is Gensim solving and how is that benefiting you?** I used a Gensim library in classifying the entities from millions of documents and rank them to find the optimal result. ### 13. Like the usage of the packages **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Education Management | Enterprise (> 1000 emp.) **Reviewed Date:** July 13, 2021 **What do you like best about Gensim?** Easy approach and the packages are really good amd efficient **What do you dislike about Gensim?** Documentation should be more on how to install and errors answering questions **What problems is Gensim solving and how is that benefiting you?** NLP ### 14. Word embeddings made easy **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Education Management | Enterprise (> 1000 emp.) **Reviewed Date:** March 08, 2019 **What do you like best about Gensim?** Easy to use interface. Python makes it very easy to work with. **What do you dislike about Gensim?** Would have liked to access more underlying code to understand their process. **Recommendations to others considering Gensim:** Read documentation well and figure out what methods are most relevant to you. Gensim can do many types of text analysis and implement word embeddings. Knowing what exactly is needed for your task is the most important part. After that Gensim can help you implement it. **What problems is Gensim solving and how is that benefiting you?** Making word2vec embeddings for a research project. Made word2vec very accessible. Was also very efficient and could handle large text corpora easily. ### 15. Deep Learning with Gensim **Rating:** 3.0/5.0 stars **Reviewed by:** Luciano Gabriel G. | Programmatic Buying Trader - Affiperf, Small-Business (50 or fewer emp.) **Reviewed Date:** June 12, 2018 **What do you like best about Gensim?** The best of Gensim is that it is an open-source toolkit implemented on Python so, in only a phrase "It's free" and it also uses NumPy, SciPy and optionally Cython for performance **What do you dislike about Gensim?** Well it's hard to find something I don't like about but, I would say that it was made mostly for a discipline like Medicine and most of their functionality goes in that way. **Recommendations to others considering Gensim:** When it becomes to Deep Learning and Machine Learning, Gensim can be an excelent option! **What problems is Gensim solving and how is that benefiting you?** The first time I Hear about Gensim was when I was doing a research for a Deep Learning proyect, where i really need to uses NumPy and SciPy together, so this library gave me the chance to do it in an easy way. ## Gensim Discussions - [What is Gensim in NLP?](https://www.g2.com/discussions/what-is-gensim-in-nlp) - [What algorithm does Gensim use?](https://www.g2.com/discussions/what-algorithm-does-gensim-use) - [How to develop chatbots with this Library?](https://www.g2.com/discussions/how-to-develop-chatbots-with-this-library) - 1 upvote - [What is the best way to make it integrated on the cloud such as AWS, Azure?](https://www.g2.com/discussions/what-is-the-best-way-to-make-it-integrated-on-the-cloud-such-as-aws-azure) - 1 upvote - [Is it possible to apply Transfer learning using bert/albert embeddings in Gensim?](https://www.g2.com/discussions/is-it-possible-to-apply-transfer-learning-using-bert-albert-embeddings-in-gensim) - 1 upvote - [View Gensim pricing details and edition comparison](https://www.g2.com/products/gensim/reviews?section=pricing&secure%5Bexpires_at%5D=2026-05-15+15%3A56%3A20+-0500&secure%5Bsession_id%5D=cc547fb7-a624-47e6-85b3-6c20afb83cac&secure%5Btoken%5D=8bba78e52964afdea43fb332c9aabf064cda443fdfd9845f8f969a4892620b99&format=llm_user) ## Gensim Features **Algorithm** - Part of Speech Tagging - Summarization - Named Entity Recognition - Sentiment Analysis - Emotion Detection - Language Detection **System** - Data Ingestion & Wrangling - Programming Language Support - Drag and Drop - Pre-Built Algorithms - Customizable Models ## Top Gensim Alternatives - [Google Cloud Translation API](https://www.g2.com/products/google-cloud-translation-api/reviews) - 4.4/5.0 (325 reviews) - [InMoment Experience Improvement (XI) Platform](https://www.g2.com/products/inmoment-experience-improvement-xi-platform/reviews) - 4.7/5.0 (314 reviews) - [Claude](https://www.g2.com/products/claude-2025-12-11/reviews) - 4.6/5.0 (241 reviews)