I tried Claude 4.5 Haiku on Amazon Bedrock

I tried Claude 4.5 Haiku on Amazon Bedrock

Amazon Bedrock now offers Anthropic's new model "Claude 4.5 Haiku". I've tried comparing its performance in the playground, checking pricing, confirming terms when starting to use it, and attempting to increase usage limits.
2025.10.17

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On October 15, 2025, Anthropic's latest model "Claude 4.5 Haiku" became available on Amazon Bedrock.

https://aws.amazon.com/about-aws/whats-new/2025/10/claude-4-5-haiku-anthropic-amazon-bedrock/

This is the latest version of Haiku in the Claude series, which can be used quickly and at low cost. I had the opportunity to try the playground functionality and the process for quota increases, so I'd like to share my experience.

Model Catalog

  • "Claude 4.5 Haiku" is now available for selection as a model from the provider Anthropic.

Model Catalog

  • On the model overview screen, you can check details, pricing, and launch the "playground" for testing.

Open in Playground

Playground

Evaluation prompt prepared with Gemini.

Evaluation Prompt

I compared responses across three models: Haiku 4.5, Haiku 3, and Sonnet 4.5. (All system prompts etc. were left as default)

  • "Claude Haiku 4.5"

haiku45 chat

  • "Claude Haiku 3"

haiku3 chat

  • "Claude Sonnet 4.5"

sonnet45 chat

The responses from "Claude 4.5 Haiku" were clearly more detailed than those from "Claude 3 Haiku."
The content of the answers approached that of the higher-tier "Sonnet 4.5" model, suggesting excellent performance considering the cost and speed.

Cross-Region Inference Selection

When selecting a model, it's now possible to choose between Japan domestic and global cross-region inference.

Select Model

  • JP Anthropic Claude Haiku 4.5
  • Global Anthropic Claude Haiku 4.5

https://aws.amazon.com/jp/blogs/news/amazon-bedrock-now-supports-japan-cross-region-inference/

Please note that Japan-limited cross-region inference costs 10% more than global inference.

Cost

The per-token charge for "Claude Haiku 4.5" is the same as "3.5 Haiku". It's set at 1/3 the price of Sonnet.

models Price per 1,000 input tokens Price per 1,000 output tokens
Claude Haiku 4.5 $0.00100 $0.00500
Claude Sonnet 4.5 $0.00300 $0.01500
Claude 3.5 Haiku $0.00100 $0.00500
Claude 3 Haiku $0.00025 $0.00125
Claude 3 Sonnet $0.00300 $0.01500

※ Prices for "Claude Haiku 4.5" and "Claude Sonnet 4.5" are for global cross-region inference usage.

Usage Consent

When using Anthropic models in Amazon Bedrock for the first time, you need to complete a consent procedure.

When selecting the target model from the Bedrock console, a consent procedure screen will be displayed.
For this test, I applied using an individual name for verification purposes.

SubmitAnthropic

Within a few minutes, an email arrived to the AWS account administrator, and Haiku 4.5 became available for use.

Haiku Marketplace Subscription

Quota Increase

For the AWS account I used for this evaluation,
"Cross-region model inference requests per minute for Anthropic Claude Haiku 4.5" was set to "2", which is a low value of 2 requests per minute, so I attempted to increase the limit using Service Quotas.

Initial Service Quota

I requested an increase to AWS's default quota value of "125".

Service Quota 2

A support case was created, and I'm waiting for AWS Support to process it.

Case Details

Usage Restrictions on Reseller Accounts

When using AWS accounts issued through partners, a ValidationException may occur when using the Claude Haiku 4.5 model.

ValidationException

ValidationException
Access to this model is not available for channel program accounts. Reach out to your AWS Solution Provider or AWS Distributor for more information.

This is due to the limitations on Anthropic models in Bedrock partner reselling announced recently (October 14, 2025).

*Resale of Anthropic models subject to certain limitations.

https://aws.amazon.com/jp/blogs/apn/amazon-bedrock-now-available-for-partner-resale/

Summary

"Claude 4.5 Haiku," newly available on Amazon Bedrock, has the potential to be used as a cost-effective model. Please try out its performance.

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