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Amazon SageMaker vs Fireworks AI comparison

Amazon Web Services (AWS) and Fireworks AI are both solutions in the AI Development Platforms category. Amazon Web Services (AWS) is ranked #5 with an average rating of 8.0, while Fireworks AI is ranked #11 with an average rating of 10.0. Amazon Web Services (AWS) holds a 5.5% mindshare in AIDP, compared to Fireworks AI’s 6.3% mindshare. Additionally, 91% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of Fireworks AI users who would recommend it.
Amazon SageMaker
Read 37 Amazon SageMaker reviews
  • 4,140 Views
  • 3,302 Comparison Views
91% willing to recommend
Fireworks AI
Read 1 Fireworks AI review
  • 1,358 Views
  • 1,185 Comparison Views
100% willing to recommend
 

Comparison Buyer's Guide

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Executive Summary
We performed a comparison between Amazon SageMaker and Fireworks AI based on real PeerSpot user reviews.

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AI Development Platforms
March 2025
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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

Amazon SageMaker
Ranking in AI Development Platforms
5th
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
37
Ranking in other categories
Data Science Platforms (3rd)
Fireworks AI
Ranking in AI Development Platforms
11th
Average Rating
10.0
Reviews Sentiment
7.7
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of May 2025, in the AI Development Platforms category, the mindshare of Amazon SageMaker is 5.5%, down from 8.5% compared to the previous year. The mindshare of Fireworks AI is 6.3%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms
 

Featured Reviews

Hemant Paralkar - PeerSpot reviewer
Improves team collaboration with advanced feature sharing but needs a better user experience
Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker. This would empower citizen data scientists to utilize the tool more effectively since many data scientists do not have a core development background. Additionally, dealing with frequent UI updates can be challenging, especially for infrastructure architects like myself. It involves effort to migrate to new UIs, making the updates not seamless. User auditing requires enhancements as tracking operations performed by users can be difficult due to dynamic IP validation and role propagation.
Read full review
reviewer2588646 - PeerSpot reviewer
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…
Read full review

Quotes from Members

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

Pros

"I have contacted the solution's technical support, and they were really good. I rate the technical support a ten out of ten."
"They are doing a good job of evolving."
"SageMaker is a comprehensive platform where I can perform all machine learning activities."
"The intuitive interface and streamlined user experience make it easy to navigate and set up various tools like Visual Studio Code or Jupyter Notebook."
"We've had no problems with SageMaker's stability."
"They offer insights into everyone making calls in my organization."
"Amazon SageMaker is highly valuable for managing ML workloads. It connects to AWS cloud resources, making it easy to deploy algorithms and collaborate using tools like GitLab. It offers a wide range of Python libraries and other necessary tools for modelling and algorithms."
"We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to ChatGPT that requires models. We utilize Amazon SageMaker to create endpoints for these models, making accessing them convenient as needed."
More Amazon SageMaker pros
"Fireworks AI has a solid API and is quite easy to interact with."
 

Cons

"Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."
"The dashboard could be improved by including more features and providing more information about deployed models, their drift, performance, scaling, and customization options."
"The payment and monitoring metrics are a bit confusing not only for Amazon SageMaker but also for the range of other products that fall under AWS, especially for a new user of the product."
"In my opinion, one improvement for Amazon SageMaker would be to offer serverless GPUs. Currently, we incur costs on an hourly basis. It would be beneficial if the tool could provide pay-as-you-go pricing based on endpoints."
"The pricing of the solution is an issue...In SageMaker, monitoring could be improved by supporting more data types other than JSON and CSV."
"The user interface (UI) and user experience (UX) of SageMaker and AWS, in general, need improvement as they are not intuitive and require substantial time to learn how to use specific services."
"When starting a new session, the waiting time can be quite long, ranging from two to five minutes."
"Improvements are needed in terms of complexity, data security, and access policy integration in Amazon SageMaker."
More Amazon SageMaker cons
"When using the API, it does not return information about the charges for image generation, which would be useful for our solution."
 

Pricing and Cost Advice

"I rate the pricing a five on a scale of one to ten, where one is the lowest price, and ten is the highest price. The solution is priced reasonably. There is no additional cost to be paid in excess of the standard licensing fees."
"On average, customers pay about $300,000 USD per month."
"The tool's pricing is reasonable."
"Databricks solution is less costly than Amazon SageMaker."
"SageMaker is worth the money for our use case."
"The pricing could be better, especially for querying. The per-query model feels expensive."
"The support costs are 10% of the Amazon fees and it comes by default."
"The cost offers a pay-as-you-go pricing model. It depends on the instance that you do."
More Amazon SageMaker pricing and cost advice
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
19%
Educational Organization
11%
Computer Software Company
11%
Manufacturing Company
9%
University
16%
Computer Software Company
15%
Financial Services Firm
8%
Government
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

How would you compare Databricks vs Amazon SageMaker?
We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...
See all answers
What do you like most about Amazon SageMaker?
We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to ChatGPT that requires models. We utilize Amazon SageMaker to create endpoints for t...
See all answers
What is your experience regarding pricing and costs for Amazon SageMaker?
Before deploying SageMaker, I reviewed the pricing, especially for notebook instances. The cost for small to medium instances is not very high.
See all answers
What is your experience regarding pricing and costs for Fireworks AI?
I cannot comment on pricing or setup cost since others handle that aspect. As a developer, I primarily use the API.
See all answers
What needs improvement with Fireworks AI?
Returning the values charged for each event generation would improve Fireworks AI. When using the API, it does not return information about the charges for image generation, which would be useful f...
See all answers
What is your primary use case for Fireworks AI?
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 generate...
See all answers
 

Comparisons

Databricks vs Amazon SageMaker Logo
Databricks vs Amazon SageMaker
Compared 15% of the time
Azure OpenAI vs Amazon SageMaker Logo
Azure OpenAI vs Amazon SageMaker
Compared 12% of the time
Dataiku vs Amazon SageMaker Logo
Dataiku vs Amazon SageMaker
Compared 11% of the time
Google Vertex AI vs Amazon SageMaker Logo
Google Vertex AI vs Amazon SageMaker
Compared 9% of the time
Domino Data Science Platform vs Amazon SageMaker Logo
Domino Data Science Platform vs Amazon SageMaker
Compared 7% of the time
More Amazon SageMaker Competitors
Together Inference vs Fireworks AI Logo
Together Inference vs Fireworks AI
Compared 54% of the time
GroqCloud Platform vs Fireworks AI Logo
GroqCloud Platform vs Fireworks AI
Compared 13% of the time
Replicate vs Fireworks AI Logo
Replicate vs Fireworks AI
Compared 12% of the time
Hugging Face vs Fireworks AI Logo
Hugging Face vs Fireworks AI
Compared 10% of the time
Azure OpenAI vs Fireworks AI Logo
Azure OpenAI vs Fireworks AI
Compared 2% of the time
More Fireworks AI Competitors
 

Product Reports

Buyer's Guide
Amazon SageMaker
April 2025
Amazon SageMaker reportDownload Amazon SageMaker product report
Buyer's Guide
AI Development Platforms
March 2025
Fireworks AI reportDownload Fireworks AI product report
 

Also Known As

AWS SageMaker, SageMaker
No data available
 

Overview

Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.

Amazon Web Services (AWS)

Fireworks AI uses advanced technologies to streamline operations and enhance user experience, catering to industry-specific requirements and driving innovation.

Fireworks AI integrates cutting-edge tools for data processing, offering seamless automation in managing complex workflows. It addresses industry needs through scalable solutions adaptable to personalized requirements. Fireworks AI ensures optimized performance, enhancing decision-making efficiency across businesses.

What are the crucial features of Fireworks AI?
  • Automated Workflow Management: Streamlines complex processes efficiently.
  • Data Analytics: Provides insightful analytics for informed strategy development.
  • Scalability: Offers flexible scaling to match business growth trajectories.
  • Industry Integration: Solutions tailored to the unique demands of different industries.
Which benefits and ROI should users evaluate?
  • Increased Efficiency: Significant reduction in workload through automation.
  • Cost Savings: Optimizes resources, leading to reduced operational costs.
  • Enhanced Decision-Making: Supports data-driven decisions for better outcomes.
  • Scalability: Facilitates growth without proportional cost increases.

Industries such as healthcare and finance benefit from Fireworks AI by streamlining data management, improving client interaction, and supporting compliance through automated document handling. Each deployment adjusts to specific sector demands, ensuring relevant application across diverse business environments.

Fireworks AI
 

Sample Customers

DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit
Information Not Available
Buyer's Guide
AI Development Platforms
March 2025
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