Fireworks AI vs Hugging Face comparison

Fireworks AI and Hugging Face are both solutions in the AI Development Platforms category. Fireworks AI is ranked #16, while Hugging Face is ranked #5 with an average rating of 8.2. Additionally, 100% of Fireworks AI users are willing to recommend the solution, compared to 100% of Hugging Face users who would recommend it.

Fireworks AI

Read 1 Fireworks AI review

546 Views
503 Comparison Views

100% willing to recommend

Hugging Face

Read 10 Hugging Face reviews

4,367 Views
3,787 Comparison Views

100% willing to recommend

Fireworks AI

Hugging Face

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Executive Summary

We performed a comparison between Fireworks AI and Hugging Face based on real PeerSpot user reviews.

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November 2024

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Categories and Ranking

Fireworks AI

Ranking in AI Development Platforms

16th

Average Rating

10.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Hugging Face

Ranking in AI Development Platforms

5th

Average Rating

8.2

Number of Reviews

Ranking in other categories

No ranking in other categories

Featured Reviews

reviewer2588646

Senior Software Development Engineer at a tech services company with 1-10 employees

Nov 6, 2024

Enhanced text-to-image creation with solid API and fine-tuning support

We primarily use Fireworks AI for text-to-image generation. We are developing a platform for artists to sell their art styles, where the system helps them tune a model and then sell images generated from their signature Fireworks AI has helped our organization by enabling us to create a platform…

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AshishKumar11

Associate Software Engineer at Linkfields Innovations (Pty) Ltd

Jul 25, 2024

Open-sourced, reliable, and enables organizations to finetune data for business requirements

Hugging Face is a website that provides various open-source models. We use them to finetune models for our business. It is just like ChatGPT, but ChatGPT has paid sources. If we have to call an API, we must pay for it. However, Hugging Face has various open-source models like Llama 2 and Llama 3…

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Quotes from Members

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

Pros

"Fireworks AI has a solid API and is quite easy to interact with."

"My preferred aspects are natural language processing and question-answering."

"It is stable."

"What I find the most valuable about Hugging Face is that I can check all the models on it and see which ones have the best performance without using another platform."

"The tool's most valuable feature is that it shows trending models. All the new models, even Google's demo models, appear at the top. You can find all the open-source models in one place. You can use them directly and easily find their documentation. It's very simple to find documentation and write code. If you want to work with AI and machine learning, Hugging Face is a perfect place to start."

"The solution is easy to use compared to other frameworks like PyTorch and TensorFlow."

"Hugging Face provides open-source models, making it the best open-source and reliable solution."

"The tool's most valuable feature is that it's open-source and has hundreds of packages already available. This makes it quite helpful for creating our LLMs."

"There are numerous libraries available, and the documentation is rich and step-by-step, helping us understand which model to use in particular conditions."

More Hugging Face pros

Cons

"When using the API, it does not return information about the charges for image generation, which would be useful for our solution."

"Hugging Face could improve by implementing a search engine or chat bot feature similar to ChatGPT."

"I believe Hugging Face has some room for improvement. There are some security issues. They provide code, but API tokens aren't indicated. Also, the documentation for particular models could use more explanation. But I think these things are improving daily. The main change I'd like to see is making the deployment of inference endpoints more customizable for users."

"I've worked on three projects using Hugging Face, and only once did we encounter a problem with the code. We had to use another open-source embedding from OpenAI to resolve it. Our team has three members: me, my colleague, and a team leader. We looked at the problem and resolved it."

"The area that needs improvement would be the organization of the materials. It could be clearer and more systematic. It would be good if the layout was clear and we could search the models easily."

"The solution must provide an efficient LLM."

"Initially, I faced issues with the solution's configuration."

"Most people upload their pre-trained models on Hugging Face, but more details should be added about the models."

"It can incorporate AI into its services."

More Hugging Face cons

Pricing and Cost Advice

Information not available

"I recall seeing a fee of nine dollars, and there's also an enterprise option priced at twenty dollars per month."

"The tool is open-source. The cost depends on what task you're doing. If you're using a large language model with around 12 million parameters, it will cost more. On average, Hugging Face is open source so you can download models to your local machine for free. For deployment, you can use any cloud service."

"The solution is open source."

"Hugging Face is an open-source solution."

"We do not have to pay for the product."

"So, it's requires expensive machines to open services or open LLM models."

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815,854 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Computer Software Company

17%

University

17%

Financial Services Firm

Comms Service Provider

Computer Software Company

11%

Manufacturing Company

11%

Financial Services Firm

10%

University

10%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

Ask a question

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What do you like most about Hugging Face?

My preferred aspects are natural language processing and question-answering.

See all answers

What needs improvement with Hugging Face?

Hugging Face could improve by implementing a search engine or chat bot feature similar to ChatGPT. This would aid developers in easily finding how to fine-tune models with specific data or get mode...

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What is your primary use case for Hugging Face?

I use Hugging Face primarily to work with open LLM models. I recently started using the open LOM models and also use embedding models. I use these models to train custom data and monitor our deskto...

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Product Reports

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Fireworks AI

Hugging Face

Overview

Fireworks partners with the world's leading generative AI researchers to serve the best models, at the fastest speeds. Independently benchmarked to have the top speed of all inference providers. Our proprietary stack blows open source options out of the water. Use powerful models curated by Fireworks or our in-house trained multi-modal and function-calling models. Fireworks is the 2nd most used open-source model provider and also generates over 1M images/day. Our OpenAI-compatible API makes it easy to start building with Fireworks!

The AI community building the future. Build, train and deploy state of the art models powered by the reference open source in machine learning.

Buyer's Guide

AI Development Platforms

November 2024

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We monitor all AI Development Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.