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Cohere vs TensorFlow comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Cohere
Ranking in AI Development Platforms
12th
Average Rating
7.6
Reviews Sentiment
6.7
Number of Reviews
8
Ranking in other categories
AI Writing Tools (3rd), Large Language Models (LLMs) (5th), AI Proofreading Tools (5th)
TensorFlow
Ranking in AI Development Platforms
8th
Average Rating
8.8
Reviews Sentiment
7.4
Number of Reviews
19
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of January 2026, in the AI Development Platforms category, the mindshare of Cohere is 1.3%, up from 0.3% compared to the previous year. The mindshare of TensorFlow is 5.8%, up from 4.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms Market Share Distribution
ProductMarket Share (%)
TensorFlow5.8%
Cohere1.3%
Other92.9%
AI Development Platforms
 

Featured Reviews

AS
Engineer at Roche
Have improved project workflows using faster response times and reduced data embedding costs
One thing that Cohere can improve is related to some distances when I am trying similarity search. Let's suppose I have provided textual data that has been embedded. I have to use some extra process from numpy after embedding the model. In the case of OpenAI embedding models, I do not have to use that extra process, and they provide lower distances compared to my results from Cohere. I was getting distances of approximately 0.005 sometimes, but in the case of Cohere, I was getting distances around 0.5 or sometimes more than that. I think that can be improved. It was possibly because of some configuration or the way I was using it, but I am not exactly sure about that.
TJ
Owner at Go knowledge
Has good stability, but the process of creating models could be more user-friendly
The platform integrates well with other tools, especially Python, which we use to create models. These models can be deployed on mobile devices, which perfectly suits our requirements. It supports our AI-driven initiatives very well by producing AI models, which is its primary function. I recommend it for those seeking specialized scripting. However, it's important to consider other options as well. It is better suited for specialists in the field and is less user-friendly than general tools like Excel. I rate it overall at six out of ten. While it is a powerful tool, other software options are slightly simpler for training models.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The very first thing that I really like about it is the support team. They're really available on Discord, and they answer all of your questions."
"Cohere positively impacted my organization by improving the performance of my RAG system."
"The best feature Cohere offers is the Reranking model."
"Cohere's Embed English v3.0 is a cloud-hosted model that took less time to embed the textual data and was more than 50 to 60% faster than other models, even somewhat faster than text-embedding-3 from OpenAI, helping to reduce development and embedding times."
"A key advantage of integrating Cohere’s reranking model is that it aligns with client requests to include a reranking module — a widely recognized method for improving RAG quality. Additionally, the API demonstrates strong performance in terms of response speed."
"Speed has helped me in my day-to-day work, and I really notice the difference because it responds very quickly to LLM requests."
"Cohere helped us with all three aspects: money is saved, time is saved, and we needed fewer resources to meet our end goals."
"When it creates a new test, it creates it almost 70 to 80% correctly without errors; the time savings are significant—what previously took one or two days can now be completed in two to three hours maximum."
"It is also totally Open-Source and free. Open-source applications are not good usually. but TensorFlow actually changed my view about it and I thought, "Look, Oh my God. This is an open-source application and it's as good as it could be." I learned that TensorFlow, by sharing their own knowledge and their own platform with other developers, it improved the lives of many people around the globe."
"Our clients were not aware they were using TensorFlow, so that aspect was transparent. I think we personally chose TensorFlow because it provided us with more of the end-to-end package that you can use for all the steps regarding billing and our models. So basically data processing, training the model, evaluating the model, updating the model, deploying the model and all of these steps without having to change to a new environment."
"I would rate the solution an eight out of ten. I am not a developer but more of an account manager. I can find what I want with TensorFlow. I haven’t contacted technical support for any issues. Since TensorFlow is vastly documented on the internet, I usually find some good websites where people exchange their views about the solution and apply that."
"The most valuable feature of TensorFlow is deep learning. It is the best tool for deep learning in the market."
"Optimization is very good in TensorFlow. There are many opportunities to do hyper-parameter training."
"TensorFlow improves my organization because our clients get a lot of investment from their investors and we are progressively improving the products. Every six months we release new features."
"TensorFlow is an efficient product for building neural networks."
"It is open-source, and it is being worked on all the time. You don't have to pay all the big bucks like Azure and Databricks. You can just use your local machine with the open-source TensorFlow and create pretty good models."
 

Cons

"Cohere has text generation. I think it is mainly focused on AI search. If there was a way to combine the searches with images, I think it would be nice to include that."
"I believe Cohere can be improved technically by providing more feedback, logs, and metrics for embedding requests, as it currently appears to be a black box without any understanding of quality."
"It's challenging for us to make a conclusion about quality enhancement by using reranking models, as solid evaluation methodology for reranking is still immature."
"The documentation and support could be improved, as there is limited documentation available on the web."
"Cohere could improve in areas where the command model is not as creative as some larger LLMs available in the market, which is expected but noticeable in open-ended generative tasks."
"One thing that Cohere can improve is related to some distances when I am trying similarity search."
"When performing similarity matching between text descriptions and the catalog descriptions created using Cohere, the matching could be improved."
"There are connection issues that interrupt the download needed for the data sets. We need to prepare them ourselves."
"It currently offers inbuilt functions, however, having the ability to implement custom libraries would enhance its usefulness for enterprise-level applications."
"It doesn't allow for fast the proto-typing. So usually when we do proto-typing we will start with PyTorch and then once we have a good model that we trust, we convert it into TensorFlow. So definitely, TensorFlow is not very flexible."
"In terms of improvement, we always look for ways they can optimize the model, accelerate the speed and the accuracy, and how can we optimize with our different techniques. There are various techniques available in TensorFlow. Maintaining accuracy is an area they should work on."
"It would be nice to have more pre-trained models that we can utilize within layers. I utilize a Mac, and I am unable to utilize AMD GPUs. That's something that I would definitely be like to be able to access within TensorFlow since most of it is with CUDA ML. This only matters for local machines because, in Azure, you can just access any GPU you want from the cloud. It doesn't really matter, but the clients that I work with don't have cloud accounts, or they don't want to utilize that or spend the money. They all see it as too expensive and want to know what they can do on their local machines."
"We encountered version mismatch errors while using the product."
"JavaScript is a different thing and all the websites and web apps and all the mobile apps are built-in JavaScript. JavaScript is the core of that. However, TensorFlow is like a machine learning item. What can be improved with TensorFlow is how it can mix in how the JavaScript developers can use TensorFlow."
"The solution is hard to integrate with the GPUs."
 

Pricing and Cost Advice

Information not available
"TensorFlow is free."
"We are using the free version."
"I rate TensorFlow's pricing a five out of ten."
"The solution is free."
"It is open-source software. You don't have to pay all the big bucks like Azure and Databricks."
"I think for learners to deploy a project, you can actually use TensorFlow for free. It's just amazing to have an open-source platform like TensorFlow to deploy your own project. Here in Russia no one really cares about licenses, as it is totally open source and free. My clients in the United States were also pleased to learn when they enquired, that licensing is free."
"I am using the open-source version of TensorFlow and it is free."
"I did not require a license for this solution. It a free open-source solution."
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Top Industries

By visitors reading reviews
Manufacturing Company
11%
Educational Organization
8%
Financial Services Firm
8%
University
7%
Manufacturing Company
14%
Comms Service Provider
9%
University
9%
Computer Software Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business2
Midsize Enterprise1
Large Enterprise6
By reviewers
Company SizeCount
Small Business12
Midsize Enterprise3
Large Enterprise3
 

Questions from the Community

What is your experience regarding pricing and costs for Cohere?
Compared to models available in the market, Cohere's pricing, setup cost, and licensing are better.
What needs improvement with Cohere?
Cohere could improve in areas where the command model is not as creative as some larger LLMs available in the market, which is expected but noticeable in open-ended generative tasks. Reporting and ...
What is your primary use case for Cohere?
We adopted Cohere primarily for their command model to support enterprise-grade text generation and NLP workflows. There was a use case for one of our customers where they required automated text g...
What is your experience regarding pricing and costs for TensorFlow?
I am not familiar with the pricing setup cost and licensing.
What needs improvement with TensorFlow?
Providing more control by allowing users to build custom functions would make TensorFlow a better option. It currently offers inbuilt functions, however, having the ability to implement custom libr...
What is your primary use case for TensorFlow?
I've used TensorFlow for image classification tasks, object detection tasks, and OCR.
 

Comparisons

 

Overview

 

Sample Customers

Information Not Available
Airbnb, NVIDIA, Twitter, Google, Dropbox, Intel, SAP, eBay, Uber, Coca-Cola, Qualcomm
Find out what your peers are saying about Cohere vs. TensorFlow and other solutions. Updated: December 2025.
881,082 professionals have used our research since 2012.