How to use a custom trained model in Amazon Bedrock?

A company is using an Amazon Bedrock base model to summarize documents for an internal use case. The company trained a custom model to improve the summarization quality. Which action must the company take to use the custom model through Amazon Bedrock?

Purchase Provisioned Throughput for the custom model. Source Reference Answer
Deploy the custom model in an Amazon SageMaker endpoint for real-time inference.
Register the model with the Amazon SageMaker Model Registry.
Grant access to the custom model in Amazon Bedrock.

Community Votes

58%

42%

58% of anonymous learners picked answer A. Votes are pick records left by other test-takers — they are not the verified answer.

Community Insight

This question tests the specific Bedrock rule that custom (fine-tuned or imported) models can only be invoked through Provisioned Throughput — on-demand inference is not available for them.

To invoke a custom fine-tuned or imported model through Amazon Bedrock, you must purchase Provisioned Throughput for that custom model. Community candidates are split between provisioning throughput and granting access, but AWS documentation makes the throughput requirement explicit for custom models.

Many candidates choose D (Grant access) because granting model access is a familiar Bedrock step for base models, but access alone does not enable invocation of a custom model without Provisioned Throughput.

Community Discussion (26 comments)

LR2023 👍 14 Selected: A

Initially I was going with D but after reading this article sticking with A https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-use.html?form=MG0AV3

CTao 👍 5 Selected: A

A To customize model you must purchase Provisioned Throughput.

sudarshanbisht 👍 1 Selected: D

When you train a custom model using Amazon Bedrock, especially via fine-tuning a base foundation model (e.g., Anthropic Claude, AI21, etc.), the custom model is managed within Bedrock itself. To use it in your applications via Bedrock APIs, you must: Grant access to the fine-tuned (custom) model within Bedrock. This allows your applications to invoke it using Bedrock's InvokeModel API.

chdaphne 👍 1 Selected: D

Amazon Bedrock allows companies to import and use their customized models alongside base models through its Custom Model Import feature. By registering the custom model within Amazon Bedrock, it can be accessed seamlessly via Bedrock’s unified API without requiring deployment in SageMaker or other infrastructure management.

SP888 👍 1 Selected: D

Yes, D for sure.

SP888 👍 1 Selected: D

Correct Answer: ✅ D. Grant access to the custom model in Amazon Bedrock. Explanation: Since the company has trained a custom model to enhance summarization and wants to use it through Amazon Bedrock, they must grant access to the custom model within Bedrock so it can be used for inference. • Amazon Bedrock allows fine-tuning of base models → After fine-tuning, the custom model must be registered and access must be granted. • Ensures secure and controlled model usage → This step enables API access for the custom summarization model. • Bedrock manages model deployment internally → The model does not need an Amazon SageMaker endpoint for use within Bedrock.

Jessiii 👍 2 Selected: D

D. Grant access to the custom model in Amazon Bedrock: When using Amazon Bedrock, you can fine-tune models or create custom versions of base models. To use your custom model, you would need to grant access to it within the Amazon Bedrock environment, enabling the model to be accessed and invoked by your application for summarization tasks.

85b5b55 👍 1 Selected: A

Provisioned Throughput helps to improve the quality.

Ginopress 👍 1 Selected: A

Accordingly to https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-use.html?form=MG0AV3

kopper2019 👍 2 Selected: D

A particularly insightful comment from user "may2021_r" clarifies this: "Bottom Line: Required to use a custom model? Give Bedrock permissions and register your model so it can retrieve your artifacts. Optional but recommended at scale? Purchase Provisioned Throughput to guarantee a certain level of concurrency and avoid throttling." The key distinction is: Granting access is the fundamental requirement to use the model at all Provisioned Throughput is about performance and scaling, not basic access

Moon 👍 2 Selected: D

D: Grant access to the custom model in Amazon Bedrock. Explanation: When a company trains a custom model to improve the performance of a base model provided by Amazon Bedrock, they need to ensure the custom model is accessible through the Amazon Bedrock service. Granting access to the custom model ensures it can be integrated and used through Bedrock's APIs and workflows for inference tasks like document summarization.

may2021_r 👍 1 Selected: D

The correct answer is D. Access must be granted in Bedrock to use custom models.

AKG85 👍 1 Selected: D

To use the custom model with Amazon Bedrock, you need to grant access to the model first.

RightAnswers 👍 1 Selected: D

When a company has trained a custom model to improve the functionality of an Amazon Bedrock base model, they need to explicitly grant access to that custom model within the Bedrock environment. This allows Bedrock to utilize the custom model's capabilities for the desired use case. Why option A is incorrect: While purchasing provisioned throughput can improve the performance and responsiveness of a model in SageMaker, it's not necessary to use a custom model with Bedrock. Bedrock itself handles the infrastructure and resource allocation. Access granting is the key step for integration.

grzeev 👍 2 Selected: D

The correct answer is D: Grant access to the custom model in Amazon Bedrock. Why not B (Purchase Provisioned Throughput): 1. Provisioned Throughput is about performance and capacity, not access 2. Granting access is a mandatory first step for using custom models in Bedrock 3. Without proper access permissions, the model cannot be used at all, even with Provisioned Throughput Granting access (C) is essential because it: - Enables model visibility in Bedrock - Controls who can use the custom model - Is a prerequisite for any model operations

6c8c706 👍 5 Selected: A

https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-use.html

Contactfornitish 👍 1 Selected: B

A. Purchase Provisioned Throughput for the custom model Provisioned Throughput is not relevant to Amazon Bedrock or custom models. It is generally associated with services like DynamoDB for performance scaling. C. Register the model with the Amazon SageMaker Model Registry While the Model Registry helps manage and track model versions, registering the model alone does not make it usable for inference. The model must still be deployed to a SageMaker endpoint. D. Grant access to the custom model in Amazon Bedrock Amazon Bedrock only provides access to foundation models hosted and managed by AWS. Custom models trained by the company need to be deployed separately via Amazon SageMaker.

leo321 👍 3

A - is the right answer, as you NEED to Purchase Provisioned Throughput for customized model: https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-use.html D - is NOT (less) correct as IAM is OPTIONAL: https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-prereq.html

RY66 👍 1

The correct answer is D. Grant access to the custom model in Amazon Bedrock.

fed6485 👍 4 Selected: A

B, and C, CANNOT be as the question is clear: "..using an Amazon Bedrock.. through Amazon BedRock" , in short SageMaker is out of the picture in this case. we are talking about a customize Bedrock Model.. so .. A is the only possible answer, we are not deploying a custom model in bedrock, we are using a bedrock customised model.. and in that case you have to pay the premium... as per this link: https://docs.aws.amazon.com/bedrock/latest/userguide/prov-throughput.html ...If you customized a model, you must purchase Provisioned Throughput to be able to use it

Blair77 👍 2 Selected: D

The question specifically mentions using the custom model "through Amazon Bedrock," which implies that the model should be integrated with Bedrock's infrastructure.

AlwaysHungry 👍 1

Has to be B

leyunjohn 👍 2 Selected: D

I agree the answer is D

jove 👍 1

Indeed, you need to "import" the custom model first : https://aws.amazon.com/bedrock/custom-model-import/

Jack78 👍 4

A. Purchase Provisioned Throughput for the custom model. https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-use.html

jove 👍 3 Selected: D

To use the custom model through Amazon Bedrock, the company needs to grant access to that model within the Bedrock environment, ensuring that the model can be utilized for tasks like document summarization.

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Expert Analysis

The correct answer is A: Purchase Provisioned Throughput for the custom model.

In Amazon Bedrock, custom models — which include models that have been fine-tuned via Bedrock's model customization feature or imported from your own account — behave differently from base foundation models when it comes to invocation. While base models can be invoked on a pay-per-token on-demand basis, custom models can only be invoked using Provisioned Throughput. This is a hard requirement stated in the AWS documentation: you must purchase a Provisioned Throughput commitment (measured in model units) for each custom model before any InvokeModel calls can succeed against it.

Why option A is correct: Provisioned Throughput provides dedicated, guaranteed capacity for a model. For custom models specifically, AWS does not offer an on-demand invocation path at all — the only way to call a fine-tuned or imported model through the Bedrock API is by attaching it to a Provisioned Throughput purchase. This is why the company must take this action.

Why option D is the common trap: Option D — Grant access to the custom model in Amazon Bedrock — is a real and necessary step for base models (e.g., enabling Claude or Llama in your account). Many candidates, including several in the community discussion, correctly note that access must be granted, but they conflate this with the invocation-enabling step for custom models. Granting access is a prerequisite for base models, but it does not unlock invocation of a custom model; only Provisioned Throughput does. Community members such as LR2023 and Ginopress explicitly reference the Bedrock customization documentation to support answer A.

Why options B and C are wrong:

B (Deploy in a SageMaker endpoint) defeats the purpose of using Bedrock. Once a model is customized or imported into Bedrock, it is invoked through Bedrock's unified API — not through SageMaker endpoints.
C (Register in SageMaker Model Registry) is a SageMaker MLOps workflow step and is unrelated to invoking a model through Bedrock. Bedrock has its own model catalog and customization pipeline.

The community is split (A: 57 vs D: 42), but the candidates citing the official Bedrock model customization guide consistently land on A, which aligns with AWS's published behavior.

Official Reference

https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-use.html

Exam Strategy

When a Bedrock question involves a custom, fine-tuned, or imported model and asks what is required to use/invoke it, immediately look for Provisioned Throughput as the answer — on-demand invocation is never available for custom models. Reserve 'Grant access' answers for questions about enabling base foundation models in a new account.

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