Amazon Bedrock vs. Vertex AI

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon Bedrock
Score 8.4 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
Vertex AI
Score 8.7 out of 10
N/A
Vertex AI on Google Cloud is an MLOps solution, used to build, deploy, and scale machine learning (ML) models with fully managed ML tools for any use case.
$0
Starting at
Pricing
Amazon BedrockVertex 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)
Imagen model for image generation
$0.0001
Starting at
Text, chat, and code generation
$0.0001
per 1,000 characters
Text data upload, training, deployment, prediction
$0.05
per hour
Video data training and prediction
$0.462
per node hour
Image data training, deployment, and prediction
$1.375
per node hour
Offerings
Pricing Offerings
Amazon BedrockVertex AI
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeOptional
Additional DetailsPricing is based on the Vertex AI tools and services, storage, compute, and Google Cloud resources used.
More Pricing Information
Community Pulse
Amazon BedrockVertex AI
Considered Both Products
Amazon Bedrock

No answer on this topic

Vertex AI
Best Alternatives
Amazon BedrockVertex AI
Small Businesses
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Score 7.8 out of 10
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Score 7.8 out of 10
Medium-sized Companies
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Score 7.8 out of 10
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Score 7.8 out of 10
Enterprises
Dataiku
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Score 8.2 out of 10
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Score 8.2 out of 10
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User Ratings
Amazon BedrockVertex AI
Likelihood to Recommend
-
(0 ratings)
7.9
(13 ratings)
Performance
-
(0 ratings)
7.1
(10 ratings)
Configurability
-
(0 ratings)
7.3
(10 ratings)
User Testimonials
Amazon BedrockVertex AI
Likelihood to Recommend
Amazon AWS
No answers on this topic
Google
Vertex AI seems to be a lot more accurate with image editing versus other competitors (including free one). We do a lot of image creation, especially of dogs in very certain scenarios. We use Adobe Stock to get us started, but many times we need some very specific edits done to the image. We've found Vertex can produce those with a lot more precision than other AI image generators.
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Pros
Amazon AWS
No answers on this topic
Google
  • Vertex AI comes with support for LOTs of LLMs out of the box
  • MLOps tools are available that help to standardize operational aspects
  • Document AI is an out of the box feature that works just perfectly for our use cases of automating lots to tedious data extraction tasks from images as well as papers
Read full review
Cons
Amazon AWS
No answers on this topic
Google
  • Customization of AutoML models - A must needed capability to be able to tweak hyperparameters and also working with different models
  • Model Explainability -Providing more comprehensive explanations about how models are utilizing features could be very beneficial
  • Model versioning and experiments tracking - Enhancing the versioning capability could be good for end users
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Performance
Amazon AWS
No answers on this topic
Google
It's not always instant, but understandable when it's under heavy load. It's not impressive nor disappointing, just what is expected. But when calling this platform through API's for it to do the actions requested there is minimal delay and wait time. It feels very responsive and quick when integrating it with a call center chat platform for example.
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Alternatives Considered
Amazon AWS
No answers on this topic
Google
Vertex AI is much more accessible to non-developers than IBM's product. Moreover, Vertex AI integrates well with other Google products, enhancing its capabilities. A big plus is its integration with cloud storage, that allows for better management and access of data. In all honesty, it wasn't much of a difficult choice to choose Vertex AI.
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Return on Investment
Amazon AWS
No answers on this topic
Google
  • It is pay as you go model so it'll save more cost of your org. In our case previously we used to incurred 1-2L/Month now we are reduced it to 80k-1L.
  • It'll help you save your model training & model selection time as it provides pre-trained models in autoML.
  • It'll help you in terms of Security wherein we can use row level security access to authorized persons.
Read full review
ScreenShots

Vertex AI Screenshots

Screenshot of an introduction to generative AI on Vertex AI - Vertex AI Studio offers a Google Cloud console tool for rapidly prototyping and testing generative AI models.Screenshot of gen AI for summarization, classification, and extraction - Text prompts can be created to handle any number of tasks with Vertex AI’s generative AI support. Some of the most common tasks are classification, summarization, and extraction. Vertex AI’s PaLM API for text can be used to design prompts with flexibility in terms of their structure and format.Screenshot of Custom ML training overview and documentation - An overview of the custom training workflow in Vertex AI, the benefits of custom training, and the various training options that are available. This page also details every step involved in the ML training workflow from preparing data to predictions.Screenshot of ML model training and creation -  A guide that shows how Vertex AI’s AutoML is used to create and train custom machine learning models with minimal effort and machine learning expertise.Screenshot of deployment for batch or online predictions - When using a model to solve a real-world problem, the Vertex AI prediction service can be used for batch and online predictions.