Amazon Bedrock vs. Google Cloud AI

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon Bedrock
Score 6.4 out of 10
N/A
Amazon Bedrock offers a way to build and scale generative AI applications with foundation models, providing a developer experience to work with a broad range of FMs from AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon.
$0
Price for 1,000 input or $0.0004 for 1000 output tokens
Google Cloud AI
Score 8.7 out of 10
N/A
Google Cloud AI provides modern machine learning services, with pre-trained models and a service to generate tailored models.N/A
Pricing
Amazon BedrockGoogle Cloud AI
Editions & Modules
Amazon Titan models- Titan Text – Lite
$0.0003
Price for 1,000 input or $0.0004 for 1000 output tokens
Cohere models - Command Light
$0.0003
Price for 1,000 input
Cohere models - Command Light
$0.0006
Price for 1,000 output
Meta model - Llama 2 Chat (13B)
$0.00075
Price for 1,000 input
Meta model - Llama 2 Chat (13B)
$0.001
Price for 1,000 output
Amazon Titan models- Titan Text – Express
$0.0013
Price for 1,000 input tokens or $0.0017 for 1000 output tokens
Cohere models - Command
$0.0015
Price for 1,000 inputtokens
Anthropic models - Claude Instant
$0.00163
Price for 1,000 input tokens
Cohere models - Command
$0.0020
Price for 1,000 output
Anthropic models - Claude Instant
$0.00551
Price for 1,000 output tokens
Anthropic models - Claude
$0.01102
Price for 1,000 input tokens
AI21 models - Jurassic-2 Mid
$0.0125
Price for 1,000 input or output tokens
AI21 models - Jurassic-2 Ultra
$0.0188
Price for 1,000 input or output tokens
Anthropic models - Claude
$0.03268
Price for 1,000 output tokens
Stability AI Model - SDXL1.0
$49.86
per hour (one month commitment)
No answers on this topic
Offerings
Pricing Offerings
Amazon BedrockGoogle Cloud AI
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Amazon BedrockGoogle Cloud AI
Best Alternatives
Amazon BedrockGoogle Cloud AI
Small Businesses
InterSystems IRIS
InterSystems IRIS
Score 7.7 out of 10
InterSystems IRIS
InterSystems IRIS
Score 7.7 out of 10
Medium-sized Companies
InterSystems IRIS
InterSystems IRIS
Score 7.7 out of 10
Posit
Posit
Score 10.0 out of 10
Enterprises
InterSystems IRIS
InterSystems IRIS
Score 7.7 out of 10
Posit
Posit
Score 10.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Amazon BedrockGoogle Cloud AI
Likelihood to Recommend
-
(0 ratings)
8.0
(0 ratings)
Likelihood to Renew
-
(0 ratings)
10.0
(0 ratings)
Usability
-
(0 ratings)
8.0
(0 ratings)
Support Rating
-
(0 ratings)
7.3
(0 ratings)
Implementation Rating
-
(0 ratings)
10.0
(0 ratings)
User Testimonials
Amazon BedrockGoogle Cloud AI
Likelihood to Recommend
No answers on this topic
Google Images analysis model is a good one and I think is very useful in our case of detections. Speech AI is also a good one. I can only recommend Google Cloud AI API and the model for that second will be SpeechKit by Yandex both these tools have exceptional values one can utilise to enhance their projects.
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Pros
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  • Smart reply and its AI suggestions make the organization think more carefully about their e-mail responses in Gmail. We were skeptical at first but it really works well for many instances.
  • We do a lot of business and contracts in Western Europe and South America, so the translate solutions make this much easier for our banking paperwork.
  • When we go to meetings or during a meeting, we often use the Google voice search to save time on research and filtering ideas or analysis.
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Cons
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  • Hard to find what to use - To find the right products, you need look closely at the details of each API, and find which suits your purposes. This can be easily fixed by creating a main page that details all of the products simply.
  • Expensive - The API costs can quickly add up, especially during the setup process and as engineers figure out the usage of the API.
  • No playground or training - There is a lack of an "API playground" or training sessions that could make onboarding engineers to this API much easier.
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Likelihood to Renew
No answers on this topic
We are extremely satisfied with the impact that this tool has made on our organization since we have practically moved from crawling to walking in the process of generating information for our main task to investigate in the field through interviews. With the audio to text translation tool there is a difference from heaven to earth in the time of feeding our internal data.
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Usability
No answers on this topic
I give 8 because although it´s a tool I really enjoy working with, I think Google Cloud AI's impact is just starting, therefore I can visualize a lot/space of improvements in this tool. As an example the application of AI in international environments with different languages is a good example of that space/room to improve.
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Support Rating
No answers on this topic
Every rep has been nice and helpful whenever I call for help. One of the systems froze and wouldn't start back up and with the help of our assigned rep we got everything back up in a timely manner. This helped us not lose customers and money.
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Implementation Rating
No answers on this topic
In fact, you only need the basic tech knowledge to do a Google search. You need to know if your organization requires it or not,. our organization required it. And that is why we acquired it and solved a need that we had been suffering from. This is part of the modernization of an organization and part of its growth as a company.
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Alternatives Considered
No answers on this topic
Google's documentation for their AI and Machine Learning products is a bit more straightforward and still much easier to onboard into compared to the Azure Machine Learning and other AI products. Additionally, Google's Cloud AI products provide more comprehensive specific use-cases that are API-optimized, and easier to integrate into existing scripts and backends.
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Return on Investment
No answers on this topic
  • Positive impact on ROI due to reduction in staff needed to build, deploy and manage a AI workload pipeline.
  • Positive impact on the business by moving to OpEx without need for upfront CapEx investment.
  • Improvement in time to analyze the data (structured and unstructured), increasing the business's ability to act based on AI results.
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ScreenShots