AWS
on Orq.ai
Access foundation models available through Amazon Bedrock using Orq.ai for reasoning, coding, multimodal, and other AI workloads through one API.
Capabilities:
Chat
Reasoning
Vision
Code
Models Supported:
eu.anthropic.claude-opus-5
global.anthropic.claude-opus-5
us.anthropic.claude-opus-5
eu.anthropic.claude-sonnet-5
global.anthropic.claude-sonnet-5
us.anthropic.claude-sonnet-5
eu.anthropic.claude-fable-5
global.anthropic.claude-fable-5
us.anthropic.claude-fable-5
eu.anthropic.claude-opus-4-8
...
Provider HQ:
Seattle, Washington
Access AWS Bedrock through Orq.ai’s AI Router
Amazon Bedrock is AWS’s managed service for accessing foundation models from AWS and third-party providers. It gives teams a way to use models for reasoning, generation, coding, multimodal applications, and other AI workloads within the AWS ecosystem.
AWS Bedrock models available on Orq.ai
Compare the models currently available through AWS Bedrock on Orq.ai, including their supported capabilities, context windows, pricing, and regional availability.
Model
Type
Context
Input / 1M
Output / 1M
eu.anthropic.claude-opus-5
chat
Reasoning
Vision
1M
$5.00
$25.00
global.anthropic.claude-opus-5
chat
Reasoning
Vision
1M
$5.00
$25.00
us.anthropic.claude-opus-5
chat
Reasoning
Vision
1M
$5.00
$25.00
Why use AWS Bedrock through Orq.ai?
Using AWS Bedrock through Orq.ai lets teams combine models available through AWS with a wider model stack without maintaining separate routing, evaluation, observability, and cost-control logic for each provider.
Capability | Provider | Direct | Through Orq.ai |
|---|---|---|---|
Chat | Models available through Amazon Bedrock | Call supported models directly through Amazon Bedrock for chat, reasoning, coding, and multimodal workloads. | Use Bedrock-hosted models through Orq.ai’s OpenAI-compatible endpoint while applying routing, tracing, evals, budgets, and governance controls around each request. |
Code | Models available through Amazon Bedrock | Use supported models for code generation, debugging, refactoring, and agentic coding workflows. | Route coding workloads through Orq.ai, compare models and providers, and monitor cost, latency, and quality from a shared control layer. |
Embeddings | Supported embedding models | Use supported embedding models directly through Amazon Bedrock where available. | Route embedding workloads alongside reasoning, generation, and agent workflows through the same Orq.ai platform. |
Pricing
AWS Bedrock pricing varies by model, AWS region, usage type, and billing configuration.
You can connect supported AWS credentials to Orq.ai or use other available access options depending on your workspace configuration.
Check Orq.ai and your AWS setup for current per-model rates, quotas, and billing details.
Centralized cost tracking
Track AWS Bedrock usage across projects, teams, and routes to understand which workloads are driving spend and adjust routing or budgets accordingly.
Budgets and limits
Apply budgets and usage controls around AWS Bedrock workloads to manage costs and enforce team-level policies.
Compatible frameworks and tools
Orq.ai works with OpenAI-compatible clients and common AI development frameworks. Tools that support compatible APIs or supported integration standards can also connect through Orq.ai where available.
Check the Orq.ai integration documentation for the latest setup options and compatibility information for AWS Bedrock.
Alternatives to AWS Bedrock
4 cards linking to similar providers
FAQs
Do I need a separate AWS account to use Bedrock through Orq.ai?
You can connect supported AWS credentials to Orq.ai or use other available access options depending on your workspace, plan, and region. Orq.ai provides a shared layer for routing, observability, evaluations, and cost controls around that usage.
Can I route only some workflows to AWS and others to different providers?
Yes. Orq.ai lets you route different workloads to different providers, so you can use AWS Bedrock where its model availability, regional coverage, or other requirements fit the workload while routing other requests elsewhere.
Does using AWS Bedrock through Orq.ai add latency?
Orq.ai adds a routing layer between your application and the model provider. Teams can monitor end-to-end latency and use routing, caching, and provider controls where appropriate to manage performance.
Alternatives to
AWS
Anthropic
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Chat
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Chat
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Z.ai
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Chat
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