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Cohere vs OpenVINO 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)
OpenVINO
Ranking in AI Development Platforms
13th
Average Rating
8.2
Reviews Sentiment
6.3
Number of Reviews
7
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 OpenVINO is 1.9%, up from 1.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms Market Share Distribution
ProductMarket Share (%)
Cohere1.3%
OpenVINO1.9%
Other96.8%
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.
Mahender Reddy Pokala - PeerSpot reviewer
AI Developer at University of Chicago
Improved model deployment on edge devices, but compatibility and scalability present challenges
I found OpenVINO's ability to convert custom models into its format particularly beneficial, as businesses sometimes require unique models specific to their use cases. Utilizing OpenVINO allowed me to run these custom models on devices directly, which I found quite impressive. Additionally, the Model Zoo offered by OpenVINO added value to the product.

Quotes from Members

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

Pros

"Cohere positively impacted my organization by improving the performance of my RAG system."
"The best feature Cohere offers is the Reranking model."
"Cohere has positively impacted my organization by helping our customers work more efficiently when creating requests, and the embedding results are of very high quality."
"Cohere helped us with all three aspects: money is saved, time is saved, and we needed fewer resources to meet our end goals."
"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'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."
"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."
"The benefit from using OpenVINO is that NVIDIA is dominating the market of GPUs and they set the price, so if I am able to run an LLM doing inference in commodity hardware, I am saving costs."
"The inferencing and processing capabilities are quite beneficial for our requirements."
"One positive aspect about OpenVINO is that it supports more frameworks than the Google Coral TPU."
"The runtime of OpenVINO is highly valuable for running different computer vision models."
"The initial setup is quite simple."
"Intel's support team is very good."
"The features for model comparison, the feature for model testing, evaluation, and deployment are very nice. It can work almost with all the models."
 

Cons

"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."
"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."
"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."
"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."
"When performing similarity matching between text descriptions and the catalog descriptions created using Cohere, the matching could be improved."
"One thing that Cohere can improve is related to some distances when I am trying similarity search."
"The documentation and support could be improved, as there is limited documentation available on the web."
"At this point, the product could probably just use a greater integration with more machine learning model tools."
"It would be great if OpenVINO could convert new models into its format more quickly."
"It has some disadvantages because when you're working with very complex models, neural networks if OpenVINO cannot convert them automatically and you have to do a custom layer and later add it to the model. It is difficult."
"The model optimization is a little bit slow — it could be improved."
"I think that it's not properly designed for scalability. It's designed for other purposes, specifically to be able to use Intel hardware and run inference using generative models or deep learning models in Intel hardware."
"I couldn't get it to run on my Raspberry Pi 4 because the software packages to download were no longer available."
"Scalability is a challenge with OpenVINO, particularly when I try to connect multiple streams of input or run multiple edge devices consecutively."
 

Pricing and Cost Advice

Information not available
"We didn't have to pay for any licensing with Intel OpenVINO. Everything is available on their site and easily downloadable for free."
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Top Industries

By visitors reading reviews
Manufacturing Company
11%
Educational Organization
8%
Financial Services Firm
8%
University
7%
Manufacturing Company
32%
Financial Services Firm
8%
Comms Service Provider
8%
Educational Organization
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business2
Midsize Enterprise1
Large Enterprise6
No data available
 

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 needs improvement with OpenVINO?
I have heard good things about OpenVINO. It doesn't consume much current for external GPU usage. However, it has some downsides because I couldn't get it to run on my Raspberry Pi 4. While not spec...
What is your primary use case for OpenVINO?
I wanted to use OpenVINO for my Raspberry Pi to analyze my sleep with a night vision camera and to improve GPU performance on my Raspberry Pi. I would have used OpenVINO's Model Optimizer feature t...
 

Comparisons

 

Overview

Find out what your peers are saying about Cohere vs. OpenVINO and other solutions. Updated: December 2025.
881,082 professionals have used our research since 2012.