Guide to using the Amazon Bedrock console to explore models, test prompts in the Playground, compare behavior and pricing, and iterate safely before building applications
In this lesson we explore the Amazon Bedrock console and how it helps developers evaluate foundation models before writing any code. The Bedrock console provides an interactive environment for exploring available models, testing prompts, and comparing behavior—so you can pick the right model and design prompts before investing engineering time in code.Why experiment in the console? Interactive experimentation accelerates iteration, reduces wasted engineering effort, and improves prompt design. Conversational interfaces like the Bedrock Playground give a fast, familiar environment for initial testing instead of building and debugging in code immediately.Common evaluation challenges include differing model behavior, prompt-design iterations, safety concerns during testing, slow code-based testing cycles, and time-consuming evaluation processes.
Evaluation challenge
How the Bedrock console helps
Different model behavior across vendors/versions
Quickly compare multiple models from the Model Catalog and run identical prompts in the Playground
Iterating on prompts
Use single-prompt or multi-turn chat modes to refine phrasing and observe context effects
Safe experimentation
The console provides a sandboxed way to test prompts and review model outputs before integration
Slow code-based testing
Interactive Playground removes the friction of code/deploy cycles for initial evaluation
Time-consuming evaluation
View model capabilities, sample outputs, and pricing in one place to speed selection
The objective: evaluate Bedrock models without writing code so you can narrow your choices before development.Solution: use the AWS Management Console. The Management Console is the web control plane for AWS. From it you can open the Amazon Bedrock console, inspect the Model Catalog, and launch the Bedrock Playground — an interactive UI for testing prompts and conversations. The console also surfaces advanced Bedrock configuration (knowledge bases for semantic retrieval over private data, guardrails, and agents) so you can iterate quickly and safely before integrating models in an application.
Quick steps (high level)
Step
Action
1
Open the AWS Management Console and search for Bedrock
2
Open the Bedrock console and go to Model Catalog
3
Inspect model details (capabilities, languages, model ID, release date)
4
Open the Playground (Test → Playground or “Open in playground” on a model page)
5
Select an inference profile and run single-turn or multi-turn prompts to evaluate behavior and costs
Start at the AWS Management Console (the primary web UI). To open Bedrock, type “Bedrock” in the console search bar and select the Bedrock entry.Once in the Bedrock console, open Model Catalog to see which providers and models are available in your current region. Models can vary by region — the current region appears in the console header (top-right).Click a provider (for example, Meta) to see the provider’s available foundation models in your region. Click a specific model to open its details page. Model details commonly include capabilities (e.g., code generation, reasoning), release date, supported input/output modalities, supported languages, and the model ID. The model ID is useful because you can copy it and use it programmatically when making API calls to Bedrock.
From a model’s details you can view pricing. The pricing view shows cost per 1 million input tokens and per 1 million output tokens for each model. Accurate cost estimation requires understanding how prompt and response sizes translate into tokens. Use the catalog pricing links for rough comparisons and then verify with precise token calculations when estimating production costs.If you prefer Amazon-provided models, the catalog lists Amazon models such as Nova. For example, Nova 2 Lite indicates supported modalities (text, image, video), maximum token limits, and language coverage — over 200 languages in this case.
Open the Bedrock Playground to experiment with a selected model. You can reach the Playground by clicking “Open in playground” on a model page or navigating to Test → Playground in the Bedrock console. After selecting a model, the console will prompt you for an inference profile. Inference profiles indicate where the request is routed (for example, regional vs. global routing) and may affect latency, availability, or compliance. Choose the profile that matches your needs and apply it.
Inference profiles determine request routing and may impact latency, region-specific availability, and cost. Pick the profile that fits your deployment and compliance requirements before running evaluations.
The Playground is designed for prompt exploration rather than production chat systems. It supports single-prompt mode and multi-turn chat mode; multi-turn preserves conversation context across turns, which is helpful while refining prompts or simulating session-based interactions.As an example workflow, choose the Amazon Nova 2 Lite model and ask a simple geography question to test response quality:
Prompt: “What are the largest cities in South America by population?”
The model returns a concise, contextual answer that lists major cities (for example, São Paulo and Buenos Aires) with short explanations and a reference-style table. Use follow-up prompts to refine results — the Playground maintains the conversation context so subsequent turns are informed by earlier exchanges.
This demonstrates selecting a model, issuing prompts, and receiving text responses without writing code. From here you can iterate on prompt phrasing, compare multiple models for accuracy and cost, and factor pricing into model selection before building the integration.
The Playground is an experimentation tool, not a production chat platform. When moving to production, validate inference profiles, latency, token usage, and apply guardrails, knowledge bases, and access controls as appropriate.
Next steps and links
AWS Amazon Bedrock (console): open the Bedrock console via the AWS Management Console.
Bedrock developer documentation: get API, SDK, and integration guidance.
Bedrock pricing and token guidance: review pricing per input/output tokens to estimate costs.
AWS announcements and deprecation notices: monitor the AWS What’s New page for model access changes and feature deprecations.
