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You can use GPT-6 in Amazon Bedrock from supported Asia Pacific (APAC) source Regions, but the setup is variant-specific and both currently use Global cross-Region inference. Choose GPT-6 Astra or GPT-6 Luna, select a listed APAC source Region, verify account access and IAM permissions, then call the matching global inference profile through that Region’s Bedrock Runtime endpoint. Global routing can process a request outside APAC, so it is not an APAC-only data-residency guarantee.
Which Asia Pacific Regions support GPT-6?
Amazon Bedrock documents two GPT-6 variants: GPT-6 Astra and GPT-6 Luna. Their APAC source-Region lists are different. The entries below come from the individual model cards, not from the general list of Regions where the Bedrock Runtime endpoint exists.
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| Variant | Supported APAC source Regions for Global inference | APAC In-Region or Geo availability |
|---|---|---|
| GPT-6 Astra | Tokyo (ap-northeast-1), Seoul (ap-northeast-2), Osaka (ap-northeast-3), Mumbai (ap-south-1), Singapore (ap-southeast-1), Sydney (ap-southeast-2) |
No APAC In-Region or Geo entry is listed |
| GPT-6 Luna | Taipei (ap-east-2), Tokyo (ap-northeast-1), Seoul (ap-northeast-2), Osaka (ap-northeast-3), Mumbai (ap-south-1), Hyderabad (ap-south-2), Singapore (ap-southeast-1), Sydney (ap-southeast-2), Jakarta (ap-southeast-3), Melbourne (ap-southeast-4), Malaysia (ap-southeast-5), New Zealand (ap-southeast-6), Thailand (ap-southeast-7) |
No APAC In-Region or Geo entry is listed |
For the authoritative, model-specific entries, see the GPT-6 Astra model card and GPT-6 Luna model card. A Region appearing in the endpoint directory does not automatically mean that either GPT-6 variant is available there; compare the model card with the Bedrock endpoint availability list.
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The list describes where a request may originate, not a separate GPT-6 deployment in each city. For example, Melbourne is a valid Luna source Region, but not an Astra source Region in the current model card. Likewise, Taipei, Hyderabad, Jakarta, Malaysia, New Zealand and Thailand are listed for Luna only. Treat the variant and Region as a pair when documenting an architecture or writing deployment rules.
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What “Global” means for an APAC deployment
Every APAC entry currently documented for Astra and Luna is under the Global cross-Region runtime option. The APAC Region you choose is the source Region for the request. AWS may route that request to another supported commercial Region, including a Region outside APAC, to run inference.
Therefore, selecting Singapore, Tokyo, Sydney or another APAC source does not promise that prompts, outputs or processing remain in Asia Pacific. If your contract, regulator or internal policy requires geographic residency, treat Global inference as unsuitable unless your compliance team accepts AWS’s routing model. AWS can add commercial destinations over time, so the current route must be checked rather than assumed.
To inspect the live mapping, call GetInferenceProfile from the source Region and examine the model ARNs it returns. AWS also documents ListInferenceProfiles for discovering profiles from a Region. The current mapping is described in Regional availability by models.
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Choose Astra or Luna before configuring anything
GPT-6 Astra
AWS describes Astra for more complex reasoning, coding, computer use, research and document creation. Those are vendor-described workload categories, not independent benchmark results. Astra launched on September 8, 2026. Its model card lists a 1,050,000-token context window and a maximum output of 128,000 tokens.
GPT-6 Luna
AWS describes Luna for repeatable work at scale, including summarization, information extraction and focused questions. These descriptions likewise are not an independent performance ranking. Luna launched on September 22, 2026, with a 1,050,000-token context window and a maximum output of 128,000 tokens.
| Decision factor | Astra | Luna |
|---|---|---|
| Vendor-described focus | Complex end-to-end reasoning, coding, computer use, research and document creation | Repeatable summarization, information extraction and focused questions at scale |
| 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 |
| APAC source-Region coverage | Six listed APAC Regions | Thirteen listed APAC Regions |
The context and output figures are model-card specifications, not independent measurements. AWS says quotas vary by account and Region; confirm the quota for the account and source Region where you will deploy.
Use workload fit as a first filter, then apply operational constraints. If the application needs computer-use or long, multi-step reasoning, Astra’s published focus may be the better starting point. If it processes large queues of summaries or extracted fields, Luna’s published focus and broader APAC source coverage may simplify placement. Neither description establishes that one variant is universally faster, cheaper or more accurate; run an evaluation with representative inputs before committing.
Requirements before you enable GPT-6
- An AWS account and a calling IAM identity (user or role).
- A source Region listed for the exact variant you selected.
- Access to the model in that account. Accounts in the same AWS Organization can have different access.
- The required AWS Marketplace permissions where applicable. AWS states that access to many Bedrock foundation models is enabled by default when the correct AWS Marketplace permissions are present.
- Permission to invoke the selected inference profile and any additional resource required by the model card.
- A client using one of the APIs listed for the model: Responses, Chat Completions or Converse.
- A decision from your security or compliance team that Global cross-Region routing is acceptable for the data you will send.
For the account-level process and prerequisites, consult AWS’s model access documentation. First use of a third-party model can start a subscription automatically. AWS identifies aws-marketplace:Subscribe, aws-marketplace:Unsubscribe and aws-marketplace:ViewSubscriptions as relevant IAM actions for serverless Marketplace models.
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Access is evaluated per account, not merely per Organization or per developer workstation. Confirm the permissions in the account that will make the production call. A successful test in a development account does not prove that the production account has model access, Marketplace permissions or the same service quotas.
Step-by-step: enable GPT-6 from an APAC source Region
1. Select the variant and source Region
Start with the two model cards, not the general endpoint list. If your application must originate in Singapore, for example, both Astra and Luna list ap-southeast-1. If it must originate in Melbourne, Luna lists ap-southeast-4, while Astra does not. If you need Taipei, Hyderabad, Jakarta, Malaysia, New Zealand or Thailand, those entries are listed for Luna but not Astra.
The source Region controls the Bedrock Runtime hostname and the profile lookup. It does not, by itself, restrict the processing destination to that geography. Write the selected variant, source code and business justification into the environment configuration rather than allowing an SDK default to choose a Region.
2. Confirm the profile is currently available
From the selected source Region, use ListInferenceProfiles to discover the available profiles or open the appropriate model card. For a deployment that depends on exact destinations, call GetInferenceProfile from that same source Region and inspect the returned model ARNs. Repeat this check when geography matters because AWS says Global destinations can change as new commercial Regions are added.
Do this check during deployment and again during change reviews. A profile that was valid when infrastructure was written can have a different destination set later. Keep a record of the date and source Region used for the lookup, especially when a compliance assessment refers to a specific routing configuration.
3. Verify account access and Marketplace prerequisites
Check model access for the specific AWS account, even if another account in the same Organization can use GPT-6. Make sure the account can perform the Marketplace actions required for the model. A successful subscription or Marketplace activation does not necessarily satisfy every separate account-level access requirement.
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4. Give the IAM identity invocation permissions
The application’s role must be allowed to invoke the inference profile. Luna’s model card specifically requires bedrock:InvokeModel on both the inference profile and the account’s default project resource:
arn:aws:bedrock:{region}:{account-id}:project/defaultReplace the braces with the actual source Region and AWS account ID in your policy; the text above is the ARN pattern documented for the default project. Review the Astra card as well for the permissions applicable to the API and profile you use. Keep permissions limited to the profile and project resources your application actually needs.
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When troubleshooting, check the identity policy, permission boundaries, session policies and any organization-level service-control policy. A role can have an apparently correct allow statement and still be blocked by a higher-level policy. Test with the same role and source Region that the application uses, not with an administrator session.
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5. Configure the Bedrock Runtime endpoint
For an OpenAI-compatible client, use the Bedrock Runtime URL for the source Region. A Singapore example is:
https://bedrock-runtime.ap-southeast-1.amazonaws.com/openai/v1For Tokyo, the corresponding hostname is https://bedrock-runtime.ap-northeast-1.amazonaws.com/openai/v1; for Sydney, it is https://bedrock-runtime.ap-southeast-2.amazonaws.com/openai/v1. The hostname must match the source Region you selected.
Bedrock’s OpenAI-compatible interface accepts a Bedrock API key, and AWS credentials are also supported for HTTP requests. Configure credentials using the method approved for your environment; do not place long-lived secrets in source code or client-side applications. Endpoint quotas apply and can be shared with other inference APIs on the same endpoint.
Keep the endpoint and model identifier as separate configuration values. Changing a hostname without changing the intended source Region can make diagnostics confusing, while changing only the model identifier can accidentally select a profile that is not supported by the endpoint’s Region.
6. Use the global profile ID, not a bare foundation-model ID
Pass the system-defined Global profile ID that matches your variant:
| Variant | Runtime model/profile ID |
|---|---|
| GPT-6 Astra | global.openai.gpt-6-astra |
| GPT-6 Luna | global.openai.gpt-6-luna |
Model cards list foundation-model IDs and profile IDs separately. For these APAC calls, use the Global profile ID required by the inference option. Do not substitute a bare base-model ID for an in-Region call: the APAC entries for these cards do not list APAC In-Region support.
7. Select a supported API
The model cards list Responses, Chat Completions and Converse for runtime use. Configure your SDK or HTTP request so that the API, endpoint and profile ID all refer to the same variant. If an application currently assumes a foundation-model identifier, update that setting to the Global profile ID and keep the source-Region endpoint unchanged.
Choose the API that matches the application contract. Responses and Chat Completions suit clients already built around OpenAI-compatible request formats, while Converse is the Bedrock-native option for applications using that interface. Do not infer API support from the endpoint alone; use the support table on the selected model card and test the exact operation your code will call.
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8. Run a controlled first request
Begin with a non-sensitive prompt that fits your intended API. Confirm that the request reaches the selected Bedrock Runtime endpoint, that the response identifies the expected model/profile, and that your logs record the source Region without recording confidential prompt content. Then test your actual context sizes, output limits and concurrency against the quota assigned to the account.
Start small enough to isolate configuration errors. After a successful smoke test, test a long context, a near-limit output and the expected parallel request count separately. Record latency and throttling responses, but do not treat one short test as a performance comparison between Astra and Luna.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to answer “Can I use GPT-6 in Singapore, Tokyo or Sydney?”
Singapore
Yes. Singapore (ap-southeast-1) appears in the APAC Global source-Region list for both Astra and Luna. Use the Singapore Bedrock Runtime endpoint and the matching Global profile ID.
Tokyo
Yes. Tokyo (ap-northeast-1) appears for both variants. It is still a Global route, not a promise that processing remains in Japan or APAC.
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Yes. Sydney (ap-southeast-2) appears for both variants. The same Global-routing qualification applies.
Other APAC locations require checking the variant: Luna has the broader list, including Taipei, Hyderabad, Jakarta, Melbourne, Malaysia, New Zealand and Thailand, while Astra’s documented list contains Tokyo, Seoul, Osaka, Mumbai, Singapore and Sydney.
Costs, quotas and capacity planning
The model cards and setup documentation do not provide a single fixed price that applies to every account or Region. Plan your budget using the current Bedrock pricing information and the usage dimensions shown for your account, then validate the estimate with a controlled workload. Do not assume that choosing an APAC source Region creates a special APAC price.
Capacity is governed by account- and Region-specific quotas. Global routing does not remove those limits, and quotas can be shared with other inference APIs on the same endpoint. Request a quota review if the expected concurrency, context length or output volume exceeds the current allocation. Include both normal traffic and retry behavior in the estimate so throttling does not turn retries into a traffic spike.
Troubleshooting common enablement failures
| Symptom | Likely cause | What to check |
|---|---|---|
| Model is not shown in the console | The selected source Region is not listed for that variant, or account access is incomplete | Recheck the exact model card, account access and Marketplace prerequisites |
AccessDeniedException |
Missing account access, Marketplace action or invocation permission | Verify model access, aws-marketplace permissions, profile permissions and (for Luna) the default project ARN |
| Validation error for model ID | A bare foundation-model ID was used instead of the Global profile ID | Use global.openai.gpt-6-astra or global.openai.gpt-6-luna |
| Endpoint responds but GPT-6 is unavailable | Bedrock Runtime endpoint availability was mistaken for model availability | Compare the model card’s source-Region list with the endpoint directory |
| Compliance review rejects the deployment | Global routing does not meet an APAC-only residency requirement | Inspect the current inference profile destinations and obtain a policy decision before sending production data |
| Requests throttle unexpectedly | Account or Region quota is insufficient, or quotas are shared with another inference API on the endpoint | Check the current quota in the intended account and source Region and review concurrent endpoint usage |
A missing console entry and an invocation denial are not always the same problem. The first usually points to variant or account availability; the second can arise after the model is visible but the calling role lacks a profile or project permission. Capture the exact API operation and identifier before changing policies.
Operational checks for production
- Record the exact variant, profile ID and source Region in deployment configuration.
- Recheck
GetInferenceProfilewhen a residency assessment depends on the destination list. - Keep an account-level access check in onboarding because Organization accounts can differ.
- Monitor quota consumption across APIs sharing the endpoint.
- Separate test prompts from production data while validating permissions and routing.
- Document that Global inference can add destinations as AWS expands commercial-Region coverage.
- Alert on changes to the profile destination list when routing geography is part of the control set.
- Review credential rotation and secret storage for Bedrock API keys or AWS credentials.
Maintain a short runbook with the source Region, endpoint URL, profile ID, IAM role, account ID and last profile-destination check. That information lets an operator distinguish a changed AWS destination map from a local endpoint, credential or policy failure.
The central distinction is simple: an APAC source Region tells Bedrock where your request enters the service, while the Global profile determines where inference may run. Configure both deliberately, and verify the live profile instead of treating an APAC endpoint as an APAC residency control.
Frequently Asked Questions
Which Asia Pacific Regions support GPT-6 in Amazon Bedrock?
GPT-6 Astra lists Tokyo, Seoul, Osaka, Mumbai, Singapore and Sydney as APAC source Regions for Global inference. GPT-6 Luna lists those locations plus Taipei, Hyderabad, Jakarta, Melbourne, Malaysia, New Zealand and Thailand. Neither model card lists APAC In-Region or Geo availability.
How do I enable GPT-6 in Bedrock?
Choose Astra or Luna, select a source Region listed for that variant, confirm account and Marketplace access, grant the required IAM permissions, configure the matching Bedrock Runtime endpoint and use the corresponding Global profile ID: global.openai.gpt-6-astra or global.openai.gpt-6-luna. Test with Responses, Chat Completions or Converse as supported by the model card.
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 Global source Regions for both Astra and Luna. The request can still be processed outside APAC.
Does Global cross-Region inference keep my data in Asia Pacific?
No. Global means AWS may route the request to any supported commercial destination, including outside APAC. Query GetInferenceProfile from the source Region and have your compliance team decide whether that routing is acceptable.
What is the correct model ID for GPT-6 on an OpenAI-compatible client?
Use global.openai.gpt-6-astra for Astra or global.openai.gpt-6-luna for Luna. Use the Bedrock Runtime URL for the selected source Region, ending in /openai/v1; a bare foundation-model ID is not the correct Global runtime identifier.
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Check account-level model access, AWS Marketplace actions, the calling role’s permission to invoke the inference profile and any model-specific resource. Luna also requires bedrock:InvokeModel on the account default project ARN. Organization accounts can have different access. If the prerequisites are complete and denial continues, AWS advises contacting AWS Sales.
Which variant should I choose, Astra or Luna?
AWS describes Astra for complex reasoning, coding, computer use, research and document creation, while Luna is described for repeatable summarization, information extraction and focused questions at scale. Also compare source-Region coverage, residency requirements and API support. These descriptions are not independent benchmark results.
Do Astra and Luna have the same context and output limits?
Both model cards list a 1,050,000-token context window and a maximum output of 128,000 tokens. AWS notes that actual quotas vary by account and Region, so verify the assigned quota before production use.
The Bottom Line
To enable GPT-6 in an APAC Bedrock Region, match the exact variant to a listed source Region, use its Global profile ID and regional Runtime endpoint, and verify account, Marketplace and IAM access. Global routing may process data outside APAC, so confirm the live inference profile and obtain a residency decision before sending sensitive workloads.
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