Amazon Bedrock vs. Vertex AI

Amazon Bedrock

Vertex AI

Overview
Product	Rating	Most Used By	Product Summary	Starting Price
Amazon Bedrock	Score 9.1 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 8.8 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 Bedrock

Vertex 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 Bedrock	Vertex AI
Free Trial
No	Yes
Free/Freemium Version
No	Yes
Premium Consulting/Integration Services
No	No

Entry-level Setup Fee

No setup fee

Optional

Additional Details

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Pricing is based on the Vertex AI tools and services, storage, compute, and Google Cloud resources used.

More Pricing Information

Community Pulse
	Amazon Bedrock	Vertex AI
Considered Both Products	Amazon Bedrock No answer on this topic	Vertex AI JM Jeff Montgomery CTO Chose Vertex AI Out the gate, Vertex just seemed to be more accurate on command with our prompts. We spent less time versus other platforms getting exactly what we wanted. Google's UI is way more robust, too, with how you can configure the exact settings you want when doing image generation. … Incentivized Helpful? Verified User Anonymous Chose Vertex AI We tend to adapt and use the platform that suits the customers needs the best. We return to Vertex AI because it is the most in-depth option out there so we can configure it any which way they want. However, it is not quick to market and constantly changing or updating it's … Incentivized Helpful? DK Dishant Kumbhar AI/ML engineer Chose Vertex AI Documentation,innovation Incentivized Helpful? TS Tirth Shah Senior Software Engineer Chose Vertex AI Amazon SageMaker Incentivized Helpful? DK Dipak Kawale ML Engineer Chose Vertex AI I have used OpenAI for their LLM and Vector Embedding service, they are really good at it. But Vertex AI has other better services like training pipeline , depolyment creation etc. Incentivized Helpful? ES Ekta Shah Associate Data Scientist Chose Vertex AI I have used AWS sagemaker is the past for AI/ML model development in my previous organization for everything. Sagemaker is good with respect to certain services but when we talk about Vertex AI in comparison, AutoML is the differentiator. AutoML is very strong and is able to … Incentivized Helpful? EL Edwin Leonard Senior Software Engineer Chose Vertex AI Google Cloud Build Incentivized Helpful? Verified User Anonymous Chose Vertex AI Let's say that Azure OpenAI Service offers you exactly what you look for in simple-to-understand terms: your own private instance of OpenAI API backend. Incentivized Helpful? Verified User Anonymous Chose Vertex AI 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 … Incentivized Helpful?

Best Alternatives
	Amazon Bedrock	Vertex AI
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Medium-sized Companies	InterSystems IRIS Score 7.7 out of 10	InterSystems IRIS Score 7.7 out of 10
Enterprises	InterSystems IRIS Score 7.7 out of 10	InterSystems IRIS Score 7.7 out of 10
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User Ratings
	Amazon Bedrock	Vertex AI
Likelihood to Recommend	10.0 (0 ratings)	6.8 (0 ratings)
Usability	10.0 (0 ratings)	- (0 ratings)
Performance	- (0 ratings)	7.3 (0 ratings)
Configurability	- (0 ratings)	7.0 (0 ratings)

User Testimonials
	Amazon Bedrock	Vertex AI
Likelihood to Recommend	No answers on this topic	Since we have used this platforms in multiple scenarios we can confidently say that where this excels is when you want to combine free form Q&A bots with structured responses. Gemini shines through and stands tall with it's natural language model and accurate reading of knowledge base to provide the best answers to whatever prompt you can throw at it. Incentivized Verified User Anonymous Read full review
Pros	No answers on this topic	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 Incentivized Verified User Anonymous Read full review
Cons	No answers on this topic	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 Incentivized Ekta Shah Associate Data Scientist Read full review
Performance	No answers on this topic	Google is always top notch with their security and user interface performance. We use Google's entire suite in our business anyways, so using Vertex became second nature very quickly. I will say, though, that Google does need to come down on the price somewhat with their token allocation. Also, their UI is very robust, so it does require some time for training to really master it. Incentivized JM Jeff Montgomery CTO Read full review
Alternatives Considered	No answers on this topic	Out the gate, Vertex just seemed to be more accurate on command with our prompts. We spent less time versus other platforms getting exactly what we wanted. Google's UI is way more robust, too, with how you can configure the exact settings you want when doing image generation. The other platforms do a decent job, but we've gravitated more towards using Vertex now. Incentivized JM Jeff Montgomery CTO Read full review
Return on Investment	No answers on this topic	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. Incentivized Verified User Anonymous Read full review
ScreenShots		Vertex AI Screenshots