Amazon Bedrock now offers DeepSeek-R1 as a fully managed serverless model. Learn about AWS DeepSeek R1 pricing and how it supports secure, scalable AI solutions.
AWS Deepseek R1
DeepSeek-R1 models are now accessible in Amazon Bedrock via the Amazon Bedrock Marketplace and Amazon Bedrock Custom Model Import as of January 30. These models have since been implemented in Amazon Bedrock by thousands of clients. The strong safeguards and extensive tooling for safe AI deployment are valued by customers. With a new serverless solution and a wider variety of options, Amazon is making it even simpler to use DeepSeek in Amazon Bedrock.
Amazon Bedrock now offers the fully managed DeepSeek-R1 variant for general use. The first cloud service provider (CSP) to offer DeepSeek-R1 as a fully managed, publicly available model is Amazon Web Services (AWS). With DeepSeek on AWS, you can generate measurable business value and speed up innovation without having to worry about complicated infrastructure management. With only one API in Amazon Bedrock’s fully managed service, you can leverage DeepSeek-R1’s capabilities to power your generative AI applications and take advantage of its wealth of features and tooling.
DeepSeek claims that its model, which is openly accessible under an MIT license, has powerful coding, reasoning, and natural language comprehension capabilities. Software creation, scientific research, data insights, mathematical problem-solving, intelligent decision assistance, and complete information management systems are all powered by these skills.
As with any Artificial Intelligence solutions, make sure to monitor your results, check for bias in output, and carefully consider data privacy concerns when adopting in your production environments. Take into account the following when putting publically accessible models, such as DeepSeek-R1, into practice:
Data security
While maintaining total control of your data, you can take advantage of Amazon Bedrock’s enterprise-grade security, monitoring, and cost management features all crucial for implementing AI responsibly at scale. No model providers have access to user inputs or model outputs. When interacting with the DeepSeek-R1 model in Amazon Bedrock, you may utilise several important security features by default, such as data encryption both in transit and at rest, fine-grained access controls, secure connectivity choices, and the ability to download different compliance certificates.
Responsible AI
With Amazon Bedrock Guardrails, you can put in place responsible AI policies and protections tailored to your application’s needs. Key features like content filtering, sensitive information filtering, and customisable security measures that use Automated Reasoning tests and contextual grounding to stop hallucinations are all included in this. By filtering out unwanted and hazardous information from your generative AI applications, you may utilise your defined set of policies to regulate how users interact with the DeepSeek-R1 model in Bedrock.
Model evaluation
Using Amazon Bedrock model assessment tools, you can quickly compare and analyse models to determine which one is best for your use case, including DeepSeek-R1. You can do this automatically or manually. Automatic evaluation with preset metrics including toxicity, accuracy, and robustness is an option. As an alternative, you can select human evaluation methods for individualised or subjective measures like style, alignment with brand voice, and relevance. Either your own datasets or pre-curated datasets are available for model evaluation.
To provide strong safety for your generative AI applications, Amazon highly advise combining Amazon Bedrock Guardrails and utilising Amazon Bedrock model assessment tools with your DeepSeek-R1 model. Protect your DeepSeek model deployments using Amazon Bedrock Guardrails and Assess the effectiveness of Amazon Bedrock resources for additional information.
AWS Deepseek R1 Pricing
The price of DeepSeek R1 on AWS is a flexible ecosystem made to meet a range of computing needs rather than a one-size-fits-all approach. A number of important aspects largely impact the pricing structure.
| AI Model | Average Hourly Cost | Computational Efficiency | Specialized Strengths |
|---|---|---|---|
| DeepSeek R1 | $35-$45 | High | Multilingual, code generation |
Get started with the DeepSeek-R1 model in Amazon Bedrock
To get started with DeepSeek-R1 models, open the Amazon Bedrock dashboard and select Model access from the Bedrock configurations menu on the left. Request access for DeepSeek-R1 in DeepSeek to have access to the fully managed DeepSeek-R1 model. After that, you’ll be able to access the model in Amazon Bedrock.
Next, select Chat/Text from the Playgrounds menu pane on the left to test the DeepSeek-R1 model in Amazon Bedrock. Next, pick DeepSeek as the category and DeepSeek-R1 as the model by selecting Select model in the upper left corner. Next, select Apply.
This prompt necessitates a sophisticated line of thinking and yields extremely accurate conclusions.
Select Guardrails under Safeguards in the left navigation pane, then establish a guardrail by setting up as many filters as necessary to activate Amazon Bedrock Guardrails on the DeepSeek-R1 model. For instance, your guardrails will identify the term “politics” in the prompt and display the banned message if you filter for it.
To evaluate the guardrail’s performance, you can test it with various inputs. By adjusting the barred messaging, word filters, sensitive information filters, and denied themes, you can fine-tune the guardrail until it meets your requirements.
