---
title: GPT-6 Sol and Luna on Amazon Bedrock (September 2026): Routing Guide
description: On September 22, 2026 AWS made GPT-6 Sol and GPT-6 Luna generally available on Bedrock. OpenAI’s internal eval found Sol makes about half as many factual mistakes as GPT-5.6 Sol. GPT-6.1 Sol followed on September 29, Ultrafast on October 8, and GPT-6.1 Terra on October 26 at half the price of 6.1 Sol. This post covers the lane routing.
url: https://www.joinhorizon.co/blog/openai-gpt-6-sol-luna-amazon-bedrock-2026/
datePublished: 2026-09-23T00:00:00.000Z
dateModified: 2026-10-28T00:00:00.000Z
author: palaniappan-p
category: Generative AI
tags: amazon-bedrock, openai, generative-ai, finops, foundation-models, cost-optimization
---

# GPT-6 Sol and Luna on Amazon Bedrock (September 2026): Routing Guide

> On September 22, 2026 AWS made GPT-6 Sol and GPT-6 Luna generally available on Bedrock. OpenAI’s internal eval found Sol makes about half as many factual mistakes as GPT-5.6 Sol. GPT-6.1 Sol followed on September 29, Ultrafast on October 8, and GPT-6.1 Terra on October 26 at half the price of 6.1 Sol. This post covers the lane routing.

> **AWS lifecycle notice (June 30, 2026):** Amazon Bedrock Agents Classic is in maintenance for new customers after **July 30, 2026**. Net-new agent builds should use [Bedrock AgentCore](https://www.joinhorizon.co/blog/amazon-bedrock-agentcore-production/). Full matrix: [lifecycle roundup](https://www.joinhorizon.co/blog/aws-service-lifecycle-updates-june-2026/).

On **September 22, 2026**, AWS [made GPT-6 Sol and GPT-6 Luna generally available on Amazon Bedrock](https://aws.amazon.com/about-aws/whats-new/2026/09/openai-gpt-6-sol-luna-on-amazon-bedrock/). The [Machine Learning Blog post](https://aws.amazon.com/blogs/machine-learning/bring-more-intelligence-to-everyday-work-with-gpt-6-sol-and-gpt-6-luna-on-amazon-bedrock/) positions them under **GPT-6 Astra**, which was already the top of the family. Sol is the daily model for recurring complex work. Luna is the high-volume model. On an internal OpenAI factuality evaluation, **Sol makes roughly half as many mistakes as GPT-5.6 Sol**.

This is a routing event on top of the [July 30, 2026 GPT-5.6 price cuts](https://www.joinhorizon.co/blog/openai-gpt-5-6-luna-terra-bedrock-pricing-2026/). Do not flip production model IDs because the family number changed.

## New lane: GPT-6.1 Terra (October 26, 2026)

**What AWS changed:** on **October 26, 2026**, [GPT-6.1 Terra became generally available on Amazon Bedrock](https://aws.amazon.com/about-aws/whats-new/2026/10/openai-gpt-6-1-terra-on-amazon-bedrock/). It is the first Terra in the GPT-6 family. There was no GPT-6 Terra. AWS positions it for everyday work that needs more than Luna and less than Sol. Per the [model card](https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-6-1-terra.html): text and image input, **1,050,000**-token context, **128,000** max output tokens. The card lists the Standard tier only. Priority, Flex, and Reserved are marked unsupported, and Ultrafast is not listed.

| Endpoint | Model ID | APIs |
| --- | --- | --- |
| bedrock-mantle, **us-east-1** | `openai.gpt-6.1-terra` | Responses, Chat Completions (`/openai/v1`) |
| bedrock-runtime, **US Geo CRIS** | `us.openai.gpt-6.1-terra` | Responses, Chat Completions, Converse, Invoke |
| bedrock-runtime, **Global CRIS** | `global.openai.gpt-6.1-terra` | Responses, Chat Completions, Converse, Invoke |

Per 1M tokens, 272K input tokens or fewer, Standard: **$1.10 input, $1.375 cache write, $0.055 cache read, $5.50 output** on Mantle and US Geo, and **$1.00 / $1.25 / $0.05 / $5.00** on Global CRIS. Above 272K input tokens the whole request moves to $2.20 / $8.25 on Mantle and US Geo, and $2.00 / $7.50 on Global CRIS.

Against GPT-6.1 Sol on US Geo ($2.20 / $11.00), that is half on input and half on output. Against the [GPT-5.6 Terra Bedrock rate](https://www.joinhorizon.co/blog/openai-gpt-5-6-luna-terra-bedrock-pricing-2026/) ($2.20 / $13.20 after the July cut), input drops 50% and output drops 58%. AWS says "at least 50% lower" than both. The arithmetic agrees.

**What the launch claims:** on OpenAI's Agents' Last Exam, GPT-6.1 Terra scored **15 percentage points** above GPT-5.6 Terra, performed on par with GPT-6 Astra, and completed tasks **more than three times faster** than Astra and GPT-6.1 Sol. OpenAI also cites gains in visual reasoning, computer use, factuality, and writing. These are OpenAI's numbers, not ours. AWS adds that ChatGPT Work and Codex can be configured to call the model on Bedrock.

**The catch:**

- **Name a profile on bedrock-runtime.** There is no in-Region call there. Use `us.openai.gpt-6.1-terra` or `global.openai.gpt-6.1-terra`. The IAM identity also needs `bedrock:InvokeModel` on the account's default project (`arn:aws:bedrock:{region}:{account-id}:project/default`), not just on the inference profile. A policy copied from a GPT-5.6 lane can fail on that line alone.
- **EU and APAC callers get Global CRIS only.** The US Geo profile covers US and Canada source Regions. Frankfurt, Ireland, Tokyo, Sydney, and the other listed EU and APAC Regions show Global only. São Paulo and Bahrain show nothing. If the lane has a residency requirement, Terra is not an option there yet.
- **Converse rejects documents.** A `document` content block, or an image inside a `toolResult`, returns `ValidationException`. Send files through the Responses API as `input_file`.
- **Features split by API.** Explicit prompt caching is Responses-only. Guardrails and application inference profiles are Converse-only. A lane that needs both Guardrails and explicit caching has to pick one.
- **Quota burns 10× on output**, same as 6.1 Sol. Check tokens-per-minute before moving a long-output agent lane.
- **"On par with Astra" is one agent eval.** It is a reason to put Terra in the Astra bakeoff, not a reason to retire Astra lanes.

Routing: new agent, computer-use, and document-reading lanes start their bakeoff with 6.1 Terra, because it costs half of 6.1 Sol. Keep GPT-5.6 Terra as the prior Terra pin. Keep 6.1 Sol where the coding pass rate still needs it.

---

## Successor: GPT-6.1 Sol (September 29, 2026)

**What AWS changed:** on **September 29, 2026**, [GPT-6.1 Sol became available on Amazon Bedrock](https://aws.amazon.com/about-aws/whats-new/2026/09/openai-gpt-6-1-sol-on-amazon-bedrock/). Per the [model card](https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-6-1-sol.html): text and image input, **1M** context, **131,072** max output tokens. The card lists Standard and Ultrafast. Ultrafast ([October 8, 2026](https://aws.amazon.com/about-aws/whats-new/2026/10/openai-gpt-sol-ultrafast-amazon/)) is the same model: set `"service_tier": "ultrafast"` on the Responses API. Priority and Flex are still unsupported.

| Endpoint | Model ID | APIs |
| --- | --- | --- |
| bedrock-mantle, **us-east-1** | `openai.gpt-6.1-sol` | Responses, Chat Completions (`/openai/v1`) |
| bedrock-runtime, **US Geo CRIS** | `us.openai.gpt-6.1-sol` | Responses, Chat Completions, Converse, Invoke |
| bedrock-runtime, **Global CRIS** | `global.openai.gpt-6.1-sol` | Responses, Chat Completions, Converse, Invoke |

Per 1M tokens, 272K input tokens or fewer, Standard: **$2.20 input, $2.75 cache write, $0.11 cache read, $11.00 output** on Mantle and US Geo, and **$2.00 / $2.50 / $0.10 / $10.00** on Global CRIS. Above 272K input tokens the whole request moves to $4.40 / $16.50 on Mantle and US Geo, and $4.00 / $15.00 on Global CRIS.

Ultrafast costs six times Standard. Short context: **$13.20 / $66.00** on Mantle and US Geo, **$12.00 / $60.00** on Global CRIS. Above 272K input tokens the whole request moves to $26.40 / $99.00 on Mantle and US Geo, and $24.00 / $90.00 on Global CRIS. The October 8 notice names the tier for latency-sensitive coding assistants, interactive agents, and customer-facing experiences. It does not publish a speed multiplier.

**What the launch claims:** OpenAI says GPT-6.1 Sol approaches GPT-6 Astra on demanding evaluations at roughly **one-fifth of the cost** per task. The [ML Blog post](https://aws.amazon.com/blogs/machine-learning/bring-near-astra-intelligence-to-everyday-work-with-gpt-6-1-sol-on-amazon-bedrock/) says it matches Astra on DeepSWE v1.1 and beats the best GPT-6 Sol score by **6.4 percentage points**. These are OpenAI's numbers, not ours.

**The catch:**

- **No direct in-Region call on bedrock-runtime.** Mantle stays `us-east-1`. Global CRIS is `global.openai.gpt-6.1-sol`. The October 8 notice does not say when Global CRIS shipped; the model card lists it.
- **Prompt caching.** The model card lists implicit and explicit prompt caching. Explicit mode needs a prefix of at least 1,024 tokens, TTL 30 minutes, and at most four cache writes per request. Do not budget on cache hits until a test request shows cached tokens in the usage block.
- **Quota burns 10× on output.** Each output token uses 10 tokens of quota. Check the account's token-per-minute quota before moving a long-output coding lane.

Keep GPT-6 Sol as the prior Sol pin. Move a US coding lane to 6.1 only after a frozen-prompt bakeoff on cost per completed task. Keep Astra for the jobs where 6.1 still fails.

---

## What each model is for

AWS and OpenAI describe four GPT-6 jobs:

| Model | Job | Bedrock status |
| --- | --- | --- |
| **GPT-6 Astra** | Hardest end-to-end work: complex reasoning, coding, computer use, research, document creation | GA **September 8, 2026**. [Model card](https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-6-astra.html): `openai.gpt-6-astra`. Mantle in `us-west-2`. Runtime profiles `us.openai.gpt-6-astra` and `global.openai.gpt-6-astra`. Context **1,050,000** tokens. Max output **128,000**. |
| **GPT-6 Sol** | Recurring complex tasks and software development: implement, debug, review, refactor, analyze data, multistep tools | GA **September 22, 2026**. About **half as many factual mistakes** as GPT-5.6 Sol on OpenAI’s internal factuality eval. |
| **GPT-6.1 Terra** | Everyday work between Luna and Sol: drafting, reading technical drawings, investigating codebases, agents that work across business systems | GA **October 26, 2026**. Half the GPT-6.1 Sol rate. Context **1,050,000** tokens. Max output **128,000**. |
| **GPT-6 Luna** | High-volume extraction, summarization, classification, and routing, with **adjustable reasoning effort** | GA **September 22, 2026**. OpenAI reports better factual reliability than the prior Luna; the announcement does not publish a second numeric eval. |

Both Sol and Luna support **up to 1M tokens** of context on Bedrock (AWS). OpenAI’s API docs list a **1,050,000**-token window for `gpt-6-sol`. Treat the Bedrock ceiling as the model card’s number once that card is in front of you. The two figures are close but not identical.

**Opinionated take:** new high-QPS classification, extraction, and routing go to **GPT-6 Luna**. New recurring coding and multistep tool lanes go to **GPT-6 Sol**. The hardest OpenAI jobs go to **GPT-6 Astra**. Keep [GPT-5.6 Terra and Sol](https://www.joinhorizon.co/blog/openai-gpt-5-6-luna-terra-bedrock-pricing-2026/) until a frozen-prompt bakeoff says the GPT-6 lane wins on quality **and** cost per completed task. Keep ZDR-default Claude work on [Opus 5.5](https://www.joinhorizon.co/blog/claude-opus-5-5-aws-bedrock-2026/), not on an OpenAI model, when Guardrails composition and default zero data retention are the requirement.

---

## Model IDs and endpoints

[OpenAI’s Amazon Bedrock guide](https://developers.openai.com/api/docs/guides/amazon-bedrock) (checked September 23, 2026):

| Model | Mantle (in-region) | Runtime geo | Runtime global |
| --- | --- | --- | --- |
| Sol | `openai.gpt-6-sol` in **us-east-1** | `us.openai.gpt-6-sol` | `global.openai.gpt-6-sol` |
| Luna | `openai.gpt-6-luna` in **us-east-1** | `us.openai.gpt-6-luna` | `global.openai.gpt-6-luna` |
| Astra | `openai.gpt-6-astra` in **us-west-2** | `us.openai.gpt-6-astra` | `global.openai.gpt-6-astra` |

Mantle base URL: `https://bedrock-mantle.{region}.api.aws/openai/v1`. Runtime base URL: `https://bedrock-runtime.{region}.amazonaws.com/openai/v1`, and the model name must be the inference profile, not the bare `openai.gpt-6-sol` ID. Hosted web search is Mantle-only. Background mode is Mantle-only and depends on data-retention settings. A region in the URL is not a data-residency guarantee; read the destination regions of the profile.

Context: OpenAI Python SDK, Mantle, `us-east-1`, Bedrock bearer token.

```python
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ['AWS_BEARER_TOKEN_BEDROCK'],
    base_url='https://bedrock-mantle.us-east-1.api.aws/openai/v1',
)

response = client.responses.create(
    model='openai.gpt-6-sol',
    input='Summarize the failure modes in this migration plan and list what you could not confirm.',
)
print(response.output_text)
```

For Runtime in the same region, point `base_url` at `https://bedrock-runtime.us-east-1.amazonaws.com/openai/v1` and set `model` to `us.openai.gpt-6-sol` or `global.openai.gpt-6-sol`. The guide’s older samples still show `openai.gpt-5.6-sol` in `us-east-2`. Changing only the model ID, and leaving the region, is the failure mode.

> **What broke (pattern, not a cited client):** A client that copied the GPT-5.6 Mantle sample, swapped in `openai.gpt-6-sol`, and left `us-east-2` in the base URL. Sol and Luna Mantle availability in the OpenAI guide is **us-east-1**. The call fails closed. Fix the region and the ID together, then confirm the live card.

---

## Prompt caching and a three-model route

AWS says GPT-6 Sol and Luna support **explicit prompt caching** (GPT-6.1 Sol: the model card lists explicit caching with a 1,024-token minimum). Mark stable instructions, tool definitions, policies, and extraction schemas so later calls process the new input. That matters when one request is classified by Luna, investigated by Sol, and escalated to Astra, and each stage can reuse its own cached prefix instead of re-sending the policy pack.

![Diagram of a three-model route on Amazon Bedrock: GPT-6 Luna classifies, GPT-6 Sol investigates, GPT-6 Astra handles escalations, each with its own cache prefix](../../assets/images/blog/openai-gpt-6-sol-luna-amazon-bedrock-2026-architecture.webp)

_Figure: Luna classifies, Sol investigates, Astra takes the escalations. Each model keeps its own cached prefix, because cache identity is per model. [Open the draw.io source](https://www.joinhorizon.co/examples/architecture-blog-2026/openai-gpt-6-sol-luna-amazon-bedrock-2026/architecture.drawio)._

Do not share one cache prefix across the three models. Cache identity is per model. A Luna checkpoint is not a Sol hit.

---

## Prices: what is published, and what is not

AWS says Sol and Luna come at **significantly lower API pricing** than GPT-5.6 and does not print a rate card in the what’s-new post or the ML blog.

OpenAI’s API docs (first-party, not a Bedrock invoice) list, per 1M tokens:

| Model | Input | Cached input | Cache write | Output |
| --- | --- | --- | --- | --- |
| GPT-6 Sol | $2.00 | $0.20 | $2.50 | $10.00 |
| GPT-6 Luna | $0.10 | $0.01 | $0.125 | $0.50 |

Prompts over **272K** input tokens are **2×** input and cache rates and **1.5×** output for the whole request. Regional processing adds **10%**. OpenAI’s Bedrock guide says commercial Bedrock pricing **matches OpenAI direct pricing**, and a region-specific Bedrock service is priced like OpenAI Regional processing. The [Bedrock pricing page](https://aws.amazon.com/bedrock/pricing/) lists GPT-6 Sol and Luna as selectable models. The static extract on September 23, 2026 did not include their dollar rows. **Confirm the selector before you re-forecast.**

> **Update (September 30, 2026):** the [GPT-6 Sol model card](https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-6-sol.html) now lists Bedrock Standard rates: **$2.00 / $10.00** per 1M input/output on Global CRIS and **$2.20 / $11.00** on Mantle and US Geo, with cache reads at $0.20 and $0.22. That matches the OpenAI list plus the 10% regional premium described above.

GPT-6 Astra **does** publish Bedrock Standard-tier rates on its [model card](https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-6-astra.html). Short context (272K input tokens or fewer), per 1M tokens:

| Inference | Input | 30-minute cache write | Cache read | Output |
| --- | --- | --- | --- | --- |
| Global CRIS | $10.00 | $12.50 | $1.00 | $50.00 |
| In-region and geo CRIS | $11.00 | $13.75 | $1.10 | $55.00 |

Long context (more than 272K input tokens) doubles input and cache rates and prices output at 1.5× ($75 global, $82.50 in-region). Priority and Flex are not supported for Astra. The card says in-region prices already include the 10% fee over OpenAI rates.

Previously published GPT-5.6 Bedrock on-demand pins ($0.22 / $1.32 Luna, $5.50 / $33 Sol) stay in our calculators. We are not replacing them with derived GPT-6 rates.

---

## Data controls AWS names

- IAM for access, CloudTrail for every invocation, PrivateLink for VPC-only traffic.
- Inference runs on hardware-isolated infrastructure with **zero-operator access**.
- Inference data is **not used for training**, and you do not opt in to sharing it with OpenAI.
- Classifier-flagged abuse-detection traffic is retained by AWS for **up to 30 days** and processed programmatically. Zero data retention is a request through your account team.

That is a different default from Claude Opus 5.5, where AWS says ZDR is on by default on Bedrock. If the lane’s requirement is ZDR without an account-team exception, do not move it to GPT-6 because the coding eval looks better.

---

## What to do this week

1. Inventory production callers still pinned to `openai.gpt-5.6-luna`, `openai.gpt-5.6-terra`, and `openai.gpt-5.6-sol`.
2. Add Sol and Luna in a non-prod account. Smoke-test Mantle in **us-east-1** and one Runtime profile (`us.` or `global.`).
3. Pick one high-volume lane and one coding lane. Freeze the prompts. Score quality, latency, and cost per completed task against the GPT-5.6 pin.
4. Turn on explicit prompt caching only for prefixes you can prove are identical across requests.
5. Add GPT-6.1 Sol to the coding-lane bakeoff against GPT-6 Sol. Non-US callers can use `global.openai.gpt-6.1-sol`. Ultrafast (`"service_tier": "ultrafast"`) is the latency tier at 6× Standard, not a different model.
6. Put GPT-6.1 Terra into the bakeoff for any lane now on GPT-5.6 Terra or GPT-6.1 Sol. Before the first call, add `bedrock:InvokeModel` on the default project ARN to the caller's IAM policy.
7. Block a production default change until the Bedrock price selector shows a rate you are willing to budget, and until the bakeoff passes.

---

## What this post doesn't cover

- A Bedrock dollar rate for Luna. Sol's Bedrock rates are in the September 30 update above; Luna's were not captured. OpenAI first-party rates are labeled as such above.
- A first-party FactualMinds bakeoff. The “half as many mistakes” figure is OpenAI’s internal factuality eval, not ours.
- A GPT-6.1 Luna. None has shipped as of October 27, 2026. GPT-6 Terra never shipped; GPT-6.1 Terra is the first GPT-6-family Terra.
- A first-party test of GPT-6.1 Terra. The Agents' Last Exam and speed figures are OpenAI's.
- Codex or Managed Agents packaging. See the [April OpenAI-on-Bedrock note](https://www.joinhorizon.co/blog/amazon-bedrock-openai-models-codex-managed-agents/).

---

## Related reading

- [GPT-5.6 Luna and Terra Bedrock Price Cuts (July 2026)](https://www.joinhorizon.co/blog/openai-gpt-5-6-luna-terra-bedrock-pricing-2026/)
- [Claude Opus 5.5 on AWS Bedrock (September 2026)](https://www.joinhorizon.co/blog/claude-opus-5-5-aws-bedrock-2026/)
- [OpenAI Models, Codex, and Managed Agents on Bedrock](https://www.joinhorizon.co/blog/amazon-bedrock-openai-models-codex-managed-agents/)
- [AWS Bedrock vs OpenAI API for Enterprise](https://www.joinhorizon.co/blog/aws-bedrock-vs-openai-api-enterprise/)
- [AWS Bedrock Cost Optimization: Token Budgets and Model Selection](https://www.joinhorizon.co/blog/aws-bedrock-cost-optimization-token-budgets-model-selection/)

## FAQ

### Are GPT-6 Sol and GPT-6 Luna generally available on Amazon Bedrock?
Yes. AWS announced general availability on September 22, 2026. Sol is the daily model for recurring complex tasks and software development. Luna is the efficient model for high-volume summarization, extraction, classification, and routing. Both support up to 1M tokens of context and explicit prompt caching. GPT-6 Astra, GA September 8, 2026, remains the flagship above them.

### What are the Bedrock model IDs for GPT-6 Sol and Luna?
OpenAI’s Amazon Bedrock guide lists Mantle IDs openai.gpt-6-sol and openai.gpt-6-luna in us-east-1. On bedrock-runtime, use the United States profiles us.openai.gpt-6-sol and us.openai.gpt-6-luna, or the global profiles global.openai.gpt-6-sol and global.openai.gpt-6-luna. Copy the ID from the console if the live card differs.

### How much do GPT-6 Sol and Luna cost on Bedrock?
AWS says both are priced significantly lower than their GPT-5.6 predecessors and does not publish dollar rates in the announcement. OpenAI’s API docs list first-party rates of $2/$10 per million tokens for Sol and $0.10/$0.50 for Luna. OpenAI’s Bedrock guide says commercial Bedrock pricing matches OpenAI direct pricing, and that a region-specific Bedrock service is priced like OpenAI Regional processing. Confirm the Bedrock pricing page before you re-forecast. Those first-party numbers are not a Bedrock invoice.

### Should we replace GPT-5.6 Luna and Sol immediately?
No. Route new high-volume lanes to GPT-6 Luna and new recurring complex or coding lanes to GPT-6 Sol only after a frozen-prompt bakeoff. Keep GPT-5.6 Terra and Sol as the prior pins until quality pass rate, latency, and cost per completed task say otherwise. Reserve GPT-6 Astra for the hardest end-to-end jobs.

### What changed with GPT-6.1 Sol (September 29, 2026)?
GPT-6.1 Sol is the Sol upgrade. OpenAI reports it approaches GPT-6 Astra on demanding evaluations at roughly one-fifth of the cost per task, matches Astra on DeepSWE v1.1, and beats the best GPT-6 Sol score by 6.4 points. The Bedrock model card lists 1M context, 131,072 max output tokens, Mantle ID openai.gpt-6.1-sol in us-east-1, US Geo profile us.openai.gpt-6.1-sol, and Global CRIS global.openai.gpt-6.1-sol on bedrock-runtime. Standard short-context rates (272K input tokens or fewer) are $2.20 / $11.00 per 1M tokens on Mantle and US Geo, and $2.00 / $10.00 on Global CRIS. On October 8, 2026 Ultrafast became available: set "service_tier" to "ultrafast" on the Responses API. The card prices Ultrafast at six times Standard ($13.20 / $66.00 on US Geo and Mantle, $12.00 / $60.00 on Global CRIS, short context).

### Can I use GPT-6.1 Sol from outside the United States?
Yes, through Global CRIS. The model card lists global.openai.gpt-6.1-sol on bedrock-runtime, plus us.openai.gpt-6.1-sol and Mantle openai.gpt-6.1-sol in us-east-1. There is still no direct in-Region call on bedrock-runtime. Ultrafast (October 8, 2026) uses the same IDs with service_tier set to ultrafast on the Responses API, at six times the Standard rate.

### What is GPT-6.1 Terra and what does it cost on Bedrock?
GPT-6.1 Terra became generally available on Amazon Bedrock on October 26, 2026. It is the everyday model of the GPT-6 family, between Luna and Sol, with text and image input, a 1,050,000-token context window, and 128,000 max output tokens. The model card lists Mantle ID openai.gpt-6.1-terra in us-east-1, US Geo profile us.openai.gpt-6.1-terra, and Global CRIS global.openai.gpt-6.1-terra on bedrock-runtime. Standard short-context rates (272K input tokens or fewer) are $1.10 input and $5.50 output per 1M tokens on Mantle and US Geo, and $1.00 / $5.00 on Global CRIS. That is half the GPT-6.1 Sol rate. OpenAI reports it scores 15 points above GPT-5.6 Terra on Agents Last Exam, on par with GPT-6 Astra, and finishes tasks more than three times faster than Astra and GPT-6.1 Sol.

### Does GPT-6 on Bedrock train on my prompts?
AWS says inference data is not used for model training, and using GPT-6 Sol or Luna does not require opting in to share data with OpenAI. Classifier-flagged abuse-detection traffic is retained by AWS for up to 30 days. Zero data retention is a request through your AWS account team, not the default described for these models.

---

*Source: https://www.joinhorizon.co/blog/openai-gpt-6-sol-luna-amazon-bedrock-2026/*