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Today, we’re announcing a new console experience in Amazon Bedrock for you to experiment, iterate, and scale with the latest AI models on Amazon Bedrock’s next-generation inference engine built for high performance, reliability, and security. This console has a refreshed workflow optimized for bedrock-mantle endpoint, which supports the latest GPT, Claude, and open-weight models with the OpenAI Responses API, OpenAI Chat Completions API, and the Anthropic Messages API.

The new console experience makes it simple to find the right model and move quickly from evaluation to production.

• New model card – You can browse the full model catalog, compare them side by side on capabilities, modality support, context window, and applicable service quotas in a single view, removing the need to stitch together documentation, and limit calculators.
• Project-based work – You can make a project to run evaluations and review usage insights in one streamlined workflow that mirrors the lifecycle of building a generative AI application.
• Live documentation – You can use project-aware live documentation: code samples, SDK snippets, and API references are automatically prefilled with your project variables. You can copy a snippet straight from the console into your application and run it without modification.

How to get started
You can try a new experience by choosing Try the Bedrock Mantle Console from within the Amazon Bedrock console, or by using the new console link directly.

You can find a project-based dashboard to show inference requests and error by range of recent dates, recently used models, and the project list. You can create a project, assign models, configure API keys, and start making inference requests in minutes.

A new model catalog shows the latest GPT, Claude, and open-weight models that are supported on the bedrock-mantle engine. You can see the details of features, tokens, pricing, input/output, pricing information, and Regional availability. You can also compare up to 3 models in a single view.

When you choose the project dashboard, you can see the models used in the project, the distribution of your token usage such as total token usage, token usage per minute, inference requests per minute, and tokens per inference request. This can inform your model selection, prompt optimization, and workload consistency decisions.

You can select up to 3 models to start evaluating to compare responses side by side with the same prompt.

To build your application in the project, choose Getting started. You can migrate existing code, build a new app with the Anthropic or OpenAI SDK, or connect an AI coding assistant to Bedrock.

Choose the API & SDK, your SDK (either Anthropic or OpenAI), your preferred programming language, and your authentication method. It shows your environment code to run these in your terminal for a quick test, or save to a .env file for your application. You can also send your first request with sample code snippets to verify your setup.

When you choose Clients, you can select the AI coding agent source such as Claude Code, Cline, Codex, Cursor, or OpenCode that you want to connect to the bedrock-mantle engine. It provides instructions on how to install the AI agent, use your AWS IAM credentials or use a Bedrock API key, set environment variables, and route requests from each AI agent through Bedrock.

To learn about Anthropic- and OpenAI-compatible APIs, choose Live API docs. You can choose Anthropic API Protocol for access to Claude model features like the Messages API or OpenAI API Protocol for access to features like Responses API.

For example, when you choose OpenAI Response API, it retrieves a model response with the given model ID. These API references are automatically prefilled with the project’s selected model ID, Region, bedrock-mantle endpoint URL, and API key reference, and they update in place as you change models or settings.

You can also choose the existing Bedrock console to manage fully-managed features such as Agents, Knowledge Bases, Guardrails, fine-tuning, or the InvokeModel and Converse APIs to run on the bedrock-runtime endpoint.

Now available
The new console experience is available in all AWS Regions where the bedrock-mantle endpoint is offered: US East (N. Virginia, Ohio), US West (Oregon), Asia Pacific (Jakarta, Mumbai, Sydney, Tokyo), Europe (Frankfurt, Ireland, London, Milan, Stockholm), and South America (São Paulo). Check the full list of Regions for future updates.

Give the new console experience a try in the new Amazon Bedrock console and send feedback to AWS re:Post for Amazon Bedrock or through your usual AWS Support contacts.

— Channy

This post was originally published on this site

As we previewed in What’s Next with AWS 2026, we’re announcing the general availability of OpenAI GPT-5.5, GPT-5.4 models, and Codex on Amazon Bedrock, giving you access to frontier models and a coding agent for software development.

According to OpenAI, GPT-5.5 and GPT-5.4 models are excellent for coding, reasoning, agentic workflows, and complex professional work. You can use GPT-5.5 for the hardest customer workloads and GPT-5.4 for the best price-performance. You can call them through Responses API on Amazon Bedrock’s next-generation inference engine built for high performance, reliability, and security.

Codex is the OpenAI coding agent for AI-powered software development. According to OpenAI, more than 4 million developers use Codex every week to write, refactor, debug, test, and validate code across large codebases. With GPT-5.5 powering inference, Codex introduces a new class of intelligence optimized for complex, long-horizon developer workflows. You can use the Codex App, the Codex CLI, and IDE integrations with Visual Studio Code, JetBrains, and Xcode, with all model inference routed through the Responses API on Amazon Bedrock.

For customers with data residency requirements, all processing stays within the Bedrock Region you select. You pay per token with no seat licenses and no per-developer commitments.

GPT-5.5 and GPT-5.4 models on Bedrock in action
You can access the model programmatically using the OpenAI Responses API to call the bedrock-mantle endpoints through the OpenAI SDK, command-line tools such as curl.

Let’s start with OpenAI SDK for Python. Install OpenAI SDK.

pip install -U openai

Set the environment variables for authentication.

export OPENAI_BASE_URL="https://bedrock-mantle.us-east-2.api.aws/openai/v1"
export OPENAI_API_KEY="<BEDROCK_API_KEY>"
export BEDROCK_OPENAI_MODEL_ID="openai.gpt-5.5"

Here is a sample Python code to call GPT-5.5 model on Bedrock:

import os
from openai import OpenAI
 
client = OpenAI(
    base_url=os.environ["OPENAI_BASE_URL"],
    api_key=os.environ["OPENAI_API_KEY"],
)
 
response = client.responses.create(
    model=os.environ["BEDROCK_OPENAI_MODEL_ID"],
    input=[
        {
            "role": "developer",
            "content": "You are a software engineer with excellent AWS cloud knowledge. Be concise and practical.",
        },
        {
            "role": "user",
            "content": "Design a distributed architecture on AWS in Python that should support 100k requests per second across multiple geographic regions.",
        },
    ],
    reasoning={"effort": "medium"},
    text={"verbosity": "low"},
)
 
print(response.output_text)

You can call directly the model endpoint using curl.

curl "$OPENAI_BASE_URL/responses" 
  -H "Content-Type: application/json" 
  -H "Authorization: Bearer $OPENAI_API_KEY" 
  -d '{
    "model": "openai.gpt-5.5",
    "input": [
      {
        "role": "developer",
        "content": "You are a software engineer with excellent AWS cloud knowledge."
      },
      {
        "role": "user",
        "content": "Design a distributed architecture on AWS in Python that should support 100k requests per second across multiple geographic regions."
      }
    ],
    "reasoning": {"effort": "medium"},
    "text": {"verbosity": "low"}
  }'

You can use the Responses API when you want to use model-managed multi-turn state, need hosted tools, function tools, or richer tool orchestration, and run background or long-running work. To learn more, visit the OpenAI Cookbook Responses examples.

Using OpenAI Codex with GPT-5.5 on Amazon Bedrock
You can download Codex CLI, Codex App or Codex VS Code extension and get started with the Bedrock for model inference. Codex supports two Bedrock authentication pathways: Amazon Bedrock API key or AWS SDK credential chain. If you set AWS_BEARER_TOKEN_BEDROCK, Codex uses it first; otherwise Codex falls back to AWS SDK credential chain.

Set AWS_BEARER_TOKEN_BEDROCK in the environment that Codex will read:

export AWS_BEARER_TOKEN_BEDROCK=<your-bedrock-api-key>

Then, configure your preferred Region and set the model ID to openai.gpt-5.5 in ~/.codex/config.toml, which is required for Bedrock API-key authentication. You can also choose openai.gpt-5.4, openai.gpt-oss-120b, or openai.gpt-oss-20b. For the desktop app or VS Code extension, put any environment variables the app needs in ~/.codex/.env.

model = "openai.gpt-5.5"
model_provider = "amazon-bedrock"
[model_providers.amazon-bedrock.aws]
region = "us-east-2"

Restart the desktop app or VS Code extension after changing ~/.codex/config.toml or ~/.codex/.env. In Codex CLI, you should see a /status tab that looks like this:

In Codex App, you can use GPT-5.5 model through Amazon Bedrock inference.

Things to know
Let me share some important technical details that I think you’ll find useful.

• Model latency: OpenAI model information positions GPT-5.5 as fast and GPT-5.4 as medium speed, but customer-perceived latency depends on reasoning effort, output length, tool calls, background mode, Region, quotas, throttling, prompt size, and cache hits. Start GPT-5.5 at medium effort. Start GPT-5.4 with effort set explicitly rather than relying on its none default.
• Scaling and capacity: Bedrock’s new inference engine is designed to rapidly provision and serve capacity across many different models. When accepting requests, we prioritize keeping steady state workloads running, and ramp usage and capacity rapidly in response to changes in demand. During periods of high demand, requests are queued, rather than rejected.

Now available
OpenAI GPT models and Codex on Amazon Bedrock are available today: GPT-5.5 model in the US East (Ohio) Region, GPT-5.4 model in the US East (Ohio) and US West (Oregon) Regions. Check the full list of Regions for future updates. To learn more, visit the OpenAI on Amazon Bedrock page and the Amazon Bedrock pricing page.

Give GPT-5.5, GPT-5.4 models, and Codex on Amazon Bedrock a try today and send feedback to AWS re:Post for Amazon Bedrock or through your usual AWS Support contacts.

— Channy