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To enable GPT-6 in an Asia Pacific Amazon Bedrock Region, choose GPT-6 Astra or GPT-6 Luna, use a supported APAC source Region, and invoke the matching Global inference profile through that Region’s bedrock-runtime endpoint. The APAC entries for both variants are Global cross-Region profiles, so the source Region is where your request starts—not a promise that processing remains in Asia Pacific. Confirm that routing model with your data-policy owner before sending regulated or residency-restricted data.
Which Asia Pacific Regions support GPT-6 in Amazon Bedrock?
Support is variant-specific. GPT-6 Astra and GPT-6 Luna have different APAC source-Region lists, and neither model card lists an APAC In-Region or Geo profile. The following entries are the Regions from which you can start a Global cross-Region runtime call.
| GPT-6 variant | APAC source Regions listed for Global inference | APAC In-Region or Geo profile listed? |
|---|---|---|
| GPT-6 Astra | ap-northeast-1 (Tokyo); ap-northeast-2 (Seoul); ap-northeast-3 (Osaka); ap-south-1 (Mumbai); ap-southeast-1 (Singapore); ap-southeast-2 (Sydney) |
No |
| GPT-6 Luna | ap-east-2 (Taipei); ap-northeast-1 (Tokyo); ap-northeast-2 (Seoul); ap-northeast-3 (Osaka); ap-south-1 (Mumbai); ap-south-2 (Hyderabad); ap-southeast-1 (Singapore); ap-southeast-2 (Sydney); ap-southeast-3 (Jakarta); ap-southeast-4 (Melbourne); ap-southeast-5 (Malaysia); ap-southeast-6 (New Zealand); ap-southeast-7 (Thailand) |
No |
These are model-specific source entries in the GPT-6 Astra model card and GPT-6 Luna model card. The fact that bedrock-runtime has an endpoint in a Region does not prove that every GPT-6 variant is available there; AWS publishes endpoint availability separately in its regional endpoint table.
What Global cross-Region inference means for your data
For each APAC entry above, AWS identifies the available profile as Global. Your application selects a source Region, but AWS may route the request to any supported commercial Region worldwide. The destination can vary by source Region and can change as AWS adds commercial Regions. Therefore, Singapore, Tokyo, Sydney, or another APAC source does not constitute an APAC-only processing guarantee.
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Before enabling either model, have your security or compliance owner answer three questions:
- Does the workload permit processing outside the country or APAC?
- Does your contract or regulation require a fixed processing location rather than a source endpoint?
- Can you record and periodically recheck the current destination mapping?
To inspect current destinations, call GetInferenceProfile from the same source Region you intend to use and review the model ARNs returned. AWS documents this regional lookup in its model regional-compatibility guidance. Treat that response as a point-in-time mapping, because Global destinations may change.
Choose GPT-6 Astra or GPT-6 Luna
Select the exact variant before configuring permissions or code. The model cards describe different workload emphases; these descriptions are vendor guidance, not independent benchmark results.
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| Decision point | GPT-6 Astra | GPT-6 Luna |
|---|---|---|
| Published workload focus | Complex reasoning, coding, computer use, research, and document creation | Repeatable work at scale, including summarization, information extraction, and focused questions |
| Launch date | September 8, 2026 | September 22, 2026 |
| Context window | 1,050,000 tokens | 1,050,000 tokens |
| Maximum output | 128,000 tokens | 128,000 tokens |
| Global profile ID for OpenAI-compatible runtime | global.openai.gpt-6-astra |
global.openai.gpt-6-luna |
| APAC source-Region coverage | Six listed Regions | Thirteen listed Regions |
The context and output figures are model-card specifications from 2026, not independent performance measurements. AWS also cautions that usable quotas vary by account and Region, so check the quota attached to the account and source Region you will deploy.
Choose Astra when the application is centered on complex, multi-step reasoning, coding, computer-use tasks, research workflows, or document creation and your chosen source Region is in Astra’s six-Region list. Choose Luna when you need repeatable, high-volume summarization, extraction, or focused question answering, or when your required APAC source location appears only in Luna’s list. This is a fit decision based on the published descriptions; it does not establish that one variant is faster, cheaper, or more accurate for every workload.
Prerequisites before you enable a model
1. An AWS account and an allowed source Region
Set the source Region in your deployment configuration to one of the entries for the selected variant. Do not infer availability from a nearby endpoint or from another GPT-6 model. If your organization uses separate development and production accounts, verify both: Bedrock model access is account-specific, and accounts in the same AWS Organization can have different results.
2. Bedrock and Marketplace permissions
AWS states that Access to many Amazon Bedrock foundation models is enabled by default with the correct AWS Marketplace permissions.
For serverless Marketplace models, the relevant IAM actions include aws-marketplace:Subscribe, aws-marketplace:Unsubscribe, and aws-marketplace:ViewSubscriptions. AWS notes that a first use of a third-party model can start a subscription automatically. Account restrictions, missing prerequisites, or an organization policy can still cause AccessDeniedException. Review the model-access instructions before testing.
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Use an IAM role, user, or workload identity that can invoke the selected inference profile. Both model cards list Responses, Chat Completions, and Converse for runtime use. Choose one API deliberately, then confirm your client supports that API’s request and response shape.
4. A residency decision documented in advance
Global routing is a product behavior, not merely a label in the console. If your policy requires a specific country, do not proceed on the assumption that an APAC source endpoint supplies that guarantee. Escalate the requirement to AWS and your compliance team instead of treating Global as In-Region.
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5. A quota and capacity check
The published one-million-plus-token context window does not automatically mean your account can submit prompts of that size. AWS quotas vary by account and Region, and endpoint quotas can be shared with other inference APIs on the same endpoint. Check the current service quota before load testing, and design request limits that leave headroom for retries and concurrent traffic.
How to enable GPT-6 in Bedrock step by step
Step 1: Pick the variant and source Region
Use the regional table above to select Astra or Luna and a source Region that your application can reach. For example, Singapore is listed for both variants, while Taipei is listed for Luna but not Astra. The source Region is used in the runtime hostname and in regional profile lookups.
Step 2: Check the live profile from that Region
Open the selected model card, then query ListInferenceProfiles in the intended source Region. Use the returned profile information to confirm that the Global profile is currently available. For the destination list, call GetInferenceProfile from that same source Region and inspect its model ARNs. This check matters because AWS can add or change Global commercial destinations.
Run this check separately for every source Region you plan to use. A profile visible from Tokyo is not proof that an identical lookup from Mumbai, Singapore, or Sydney will return the same mapping. Save the profile response, timestamp, source Region, and account in your deployment record so a later compliance or incident review can distinguish a changed AWS mapping from an application change.
Step 3: Confirm account access
In the AWS account that will run the workload, verify Bedrock model access and Marketplace prerequisites. If the model is documented for the Region and all prerequisites are complete but access is still denied, AWS advises contacting AWS Sales. Do not assume that activating Marketplace permissions in one account grants access to every account in the organization.
Step 4: Grant runtime permissions
Attach the least-privilege permissions required by the API and profile. Luna’s model card specifically requires bedrock:InvokeModel on both the inference profile and the account default project resource:
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Replace {region} and {account-id} with the values for the calling account and source Region. Apply the equivalent invocation permissions required by your Astra deployment, and check the model card’s current authorization guidance rather than copying a Luna-only resource statement.
Permission scope is a common source of confusion. Granting access to a foundation-model ARN alone may not authorize a call made through a Global inference profile. Review the resource shown in the model card and test with the same IAM principal, source Region, and profile ID that production will use. If a role is assumed through another account, verify the trust policy and the effective permissions in the account where the request originates.
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Step 5: Configure the OpenAI-compatible endpoint
For an OpenAI SDK client, set the Bedrock runtime base URL to:
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Use the profile ID that matches the selected variant:
- Astra:
global.openai.gpt-6-astra - Luna:
global.openai.gpt-6-luna
Use a Bedrock API key with the OpenAI-compatible client, or use AWS credentials when making HTTP requests directly. The Bedrock Responses API documentation describes the compatible endpoint and authentication options.
Do not substitute a bare foundation-model ID for these Global runtime calls. The model cards identify the Global profile IDs separately from foundation-model IDs, and APAC In-Region support is not listed for these variants.
Step 6: Select Responses, Chat Completions, or Converse
Both variants list Responses, Chat Completions, and Converse as supported runtime APIs. Match the API to your application’s existing client and required features. Keep the API choice consistent while troubleshooting so that an authorization or payload error is not confused with a model-availability problem.
Responses and Chat Completions are useful when an existing OpenAI-compatible client is already part of the application. Converse is the Bedrock-native option listed by the model cards. Whichever route you choose, verify streaming behavior, tool or structured-output requirements, and error handling against the API documentation before switching a production workload.
Step 7: Send a controlled test
Start with a non-sensitive prompt and the smallest output limit that exercises your integration. Confirm four things in the response and logs: the request reached the intended Bedrock source endpoint, the profile ID is the selected Global ID, the call used the expected API, and the IAM principal was the one you granted. Only after this succeeds should you test production payload sizes or sensitive data.
Use a test that is representative enough to validate the request shape but contains no customer, health, financial, or confidential business information. Record latency, HTTP status, request identifier, and quota-related headers or errors without logging the prompt or response content unnecessarily. Repeat the smoke test after changing the source Region, account, role, client library, or profile ID.
Region-specific examples
Singapore
ap-southeast-1 is listed as an APAC source Region for both Astra and Luna. Use the Singapore runtime hostname with the corresponding Global profile ID. The profile still uses Global routing, so Singapore is not an APAC-only processing commitment.
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Tokyo
ap-northeast-1 is listed for both variants. Query the profile from Tokyo before deployment and record the current destination mapping. A Tokyo source endpoint does not force every inference step to remain in Japan.
Sydney
ap-southeast-2 is listed for both variants. Configure the Sydney source endpoint and the matching Astra or Luna Global ID, then validate account access and invocation permissions in the account that will run the workload.
Regions listed only for Luna
Taipei, Hyderabad, Jakarta, Melbourne, Malaysia, New Zealand, and Thailand appear in the Luna list but not in the Astra list. If your workload must start in one of those Regions, Luna is the only one of these two variants documented for that source location.
How to validate a production-ready configuration
A successful first response is only the beginning of enablement. Use a short checklist before promoting the integration:
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- Confirm the configured model value is the exact Global profile ID and that the URL contains the same source-Region code.
- Confirm the deployment account has current model access and Marketplace permissions.
- Confirm the runtime role can invoke the profile and any additional resource required by the model card.
- Confirm the API in use is one of Responses, Chat Completions, or Converse and that the client’s payload format matches it.
- Confirm the latest
GetInferenceProfileresponse has been reviewed by the team responsible for data location. - Confirm quota limits and concurrency assumptions have been tested in the production account, not inferred from a development account.
- Confirm logs capture enough metadata to troubleshoot endpoint, profile, account, and authorization issues without exposing sensitive content.
If you operate active-active deployments in multiple APAC Regions, perform the same checks for each source. A failover from Singapore to Tokyo changes the source endpoint and may produce a different Global destination mapping, even though the application still uses the same model variant.
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AccessDeniedException before inference starts
- Confirm that the account has the required Marketplace permissions and that an organization SCP or account policy is not blocking them.
- Verify that the IAM principal can invoke the inference profile, not only a foundation-model ARN.
- For Luna, check both the profile resource and
arn:aws:bedrock:{region}:{account-id}:project/default. - Make sure the source Region is listed for the exact variant. Endpoint availability alone is insufficient.
- If documentation, prerequisites, and permissions all match but access remains denied, follow AWS’s instruction to contact AWS Sales.
Model-not-found or unsupported-model errors
- Check the spelling of
global.openai.gpt-6-astraorglobal.openai.gpt-6-luna. - Ensure the base URL uses the source Region’s
bedrock-runtimehostname and ends in/openai/v1for the OpenAI-compatible API. - Recheck
ListInferenceProfilesandGetInferenceProfilefrom that source Region; Global destinations are not static. - Do not use a bare foundation-model ID when the selected option is Global.
Requests work in one account but not another
Model access is account-specific, even within one AWS Organization. Repeat the Marketplace, Bedrock, IAM, and profile checks in the failing account. Credentials from a developer account do not demonstrate production-account access.
Requests fail only at larger prompts or outputs
The 1,050,000-token context and 128,000-token maximum output are model-card limits, not a promise that your account can consume them. AWS quotas vary by account and Region, and endpoint quotas can be shared with other inference APIs on the same endpoint. Check the current service quota and reduce context or output limits while isolating the failure.
Compliance review rejects the deployment
Show the reviewer the Global profile behavior and the destination list returned by GetInferenceProfile. If the requirement is APAC-only or country-specific processing, these APAC Global entries may not satisfy it because AWS can route to supported commercial Regions worldwide. Do not describe the source Region as the processing location.
Only one API path fails
If Converse succeeds but an OpenAI-compatible request fails, or the reverse, keep the model and source Region unchanged while checking the endpoint path, authentication method, request schema, and client version. The model cards list all three APIs, but support for a model does not remove the need to use the correct API-specific URL and payload.
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Operational checks after launch
- Record the selected variant, source Region, Global profile ID, API, account, and IAM role in the deployment record.
- Recheck the inference profile when AWS announces new commercial Regions or when a residency assessment is renewed.
- Monitor quota consumption because endpoint limits may be shared with other inference APIs.
- Keep the model-card links in your runbook and verify the supported API table before upgrading client libraries.
- Separate non-sensitive smoke tests from production data and retain enough request metadata to diagnose routing and authorization without logging confidential prompts.
- Review failover configurations after every Region change. A backup APAC source may have different variant coverage or a different destination set.
- Revalidate Marketplace and IAM permissions after account reorganizations, new service-control policies, or changes to the assumed role.
Key takeaways
- GPT-6 availability in APAC is not a single switch: Astra and Luna have different source-Region lists.
- Both variants are documented in APAC through Global cross-Region inference, not APAC In-Region or Geo profiles.
- Use the matching Global profile ID with a
bedrock-runtime.<source-region>.amazonaws.com/openai/v1endpoint. - Verify Marketplace access, account-level model access, IAM invocation permissions, and the live profile destination before sending production data.
- Global destinations and account quotas can change, so treat regional and capacity checks as ongoing operational controls.
Frequently Asked Questions
Can I use GPT-6 in Singapore, Tokyo, or Sydney?
Yes. Singapore (ap-southeast-1), Tokyo (ap-northeast-1), and Sydney (ap-southeast-2) are listed as APAC source Regions for both GPT-6 Astra and GPT-6 Luna. You still need account access, the matching Global profile ID, and the correct bedrock-runtime endpoint.
Is GPT-6 processing guaranteed to stay in Asia Pacific when I select an APAC Region?
No. The APAC entries for Astra and Luna are Global cross-Region profiles. AWS may route a request to supported commercial Regions worldwide, and destinations can change. An APAC source endpoint is not an APAC-only or country-specific residency guarantee.
Which GPT-6 variant supports Taipei, Hyderabad, or Thailand as a source Region?
Those locations are listed for GPT-6 Luna. Taipei (ap-east-2), Hyderabad (ap-south-2), and Thailand (ap-southeast-7) do not appear in Astra’s APAC source-Region list.
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What model ID should an OpenAI-compatible client use?
Use global.openai.gpt-6-astra for Astra or global.openai.gpt-6-luna for Luna. Set the base URL to https://bedrock-runtime.<source-region>.amazonaws.com/openai/v1. Do not replace the Global profile ID with a bare foundation-model ID.
Do I need to subscribe to GPT-6 manually?
Many Bedrock models are enabled by default when the account has the correct AWS Marketplace permissions. AWS lists aws-marketplace:Subscribe, aws-marketplace:Unsubscribe, and aws-marketplace:ViewSubscriptions as relevant actions for serverless Marketplace models. A first use can start a subscription automatically, but organization restrictions or missing prerequisites can still block access.
What IAM permission is specifically required for GPT-6 Luna?
Luna’s model card requires bedrock:InvokeModel on both the inference profile and the account default project resource, arn:aws:bedrock:{region}:{account-id}:project/default. Check the current model-card guidance for the exact resources needed by your Astra deployment.
How can I see where Global inference may route a request?
Call GetInferenceProfile from the intended source Region and inspect the model ARNs returned. Also use ListInferenceProfiles to confirm the profile is currently available there. Recheck when regional coverage or residency requirements change because AWS can update Global destinations.
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Both model cards list a 1,050,000-token context window and a maximum output of 128,000 tokens. These are published model specifications, not a guarantee that your account can use the full limits. AWS quotas vary by account and Region.
Which APIs can I use with these models in Bedrock?
The model cards list Responses, Chat Completions, and Converse for both Astra and Luna. Select the API that matches your client and verify its endpoint, authentication, request schema, and response handling separately.
Why does an endpoint exist in my Region if GPT-6 is unavailable there?
Bedrock endpoint availability and model availability are published separately. A bedrock-runtime endpoint in a Region does not prove that every GPT-6 variant is supported there. Check the exact variant’s model card and query inference profiles from the source Region.
The Bottom Line
Enable GPT-6 by matching the exact variant to a documented APAC source Region, using its Global inference profile ID, and granting the account and IAM permissions required for that profile. Validate the profile with ListInferenceProfiles and GetInferenceProfile, then confirm that your compliance policy accepts Global cross-Region routing. Singapore, Tokyo, Sydney, and the other listed APAC locations identify where a request starts—not necessarily where it is processed.
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