GPT-6 Astra: what it is, what it costs and how it compares
OpenAI released GPT-6 Astra on September 3, 2026, and after shelving GPT-6.1 Astra it remains the company's flagship, even as GPT-6.1 Sol and GPT-6.1 Terra now deliver much of its capability for far less. Here is what it really costs, what independent tests show as of October 27 and when it makes sense for a company.
GPT-6 Astra is OpenAI's most capable model: $10 per million input tokens and $50 per million output tokens, a 1.05 million token context window and, by OpenAI's own assessment, its first model with “Critical” cybersecurity capability. For a company it changes three things: a premium price with surcharges for long prompts and data residency, cyber safeguards that only OpenAI's approval relaxes, and a cost per task you cannot read off the price list.
Our reading on October 27, 2026: Astra still holds the best ARC-AGI-2 and ARC-AGI-3 scores and is the second model on the Artificial Analysis index (57 against 58 for Claude Opus 5.5), but GPT-6.1 Sol scores 55 for a fifth of the cost per task and Opus 5.5 keeps first place on Terminal-Bench 4.0. Use Astra where your tests show a clear gain, which is what our model evaluation at Slash AI Lab measures.
What is GPT-6 Astra, and what can it do?
GPT-6 Astra is the most capable model OpenAI has broadly deployed, released on September 3, 2026. OpenAI's model guide still recommends it as the starting point when you are unsure which to pick, and AWS pitches it for the hardest end-to-end work: complex reasoning, coding, computer use and research. It reads text and images and writes text; there is no voice (Realtime) endpoint, fine-tuning or embeddings.
- Limits. A 1,050,000-token window, at most 922,000 input tokens per request and 128,000 output tokens; its knowledge ends on April 30, 2026.
- Reasoning. Five effort levels, from
lowtomax;nonereturns an error. OpenAI's model page does not document the default, so set it on every route. - Tools. Web search, file search, code interpreter, hosted shell, computer use and MCP servers in the Responses API, some with fees on top (web search: $10 per 1,000 calls).
- Where. OpenAI's API (
gpt-6-astra, a single published snapshot), Codex, Microsoft Foundry since September 3 and Amazon Bedrock since September 8, where AWS commits to keep it until at least September 8, 2027.
What changed since launch
- September 28 and 29. OpenAI shelved GPT-6.1 Astra, whose tests showed more deception and a tendency to act without the user's permission, according to The Wall Street Journal as reported by TechCrunch; launched GPT-6.1 Sol ($2/$10), which it credits with near-Astra intelligence; and presented Dots, always-on agents that run on Astra.
- October 13. Google made Gemini 4 Argon, its most capable model, generally available at $2/$10 until November 30 and $4/$20 from December 1.
- October 26. OpenAI launched GPT-6.1 Terra ($1/$5) for computer use; OpenAI says that at medium effort it matches Astra on Agents' Last Exam at a tenth of the price per token and finishes tasks more than three times faster.
- Astra itself has not changed: same model ID, same prices and same limits as at launch.
How much does GPT-6 Astra cost?
$10 per million input tokens and $50 per million output tokens on the standard tier, with cached input at $1. Five modifiers then move the bill:
| Tier | Input | Cached input | Output | Note |
|---|---|---|---|---|
| Standard, up to 272K input tokens | 10 | 1 | 50 | Cache writes: 12.50 |
| Long prompts, over 272K | 20 | 2 | 75 | Whole request |
| Batch or Flex | 5 | 0.50 | 25 | Half price |
| Fast mode | 20 | 2 | 100 | Formerly called Priority |
| Ultrafast | 60 | 6 | 300 | Up to 6x faster, per OpenAI |
| Regional processing | +10% | +10% | +10% | Data residency |
A worked example with explicit assumptions: one agent step with 12,000 input tokens, 10,000 of them a stable cached prefix, and 2,000 output tokens including reasoning; standard tier, no regional uplift, initial cache write excluded.
| Model | No caching | Cached prefix | 100,000 cached steps |
|---|---|---|---|
| GPT-6 Astra | $0.220 | $0.130 | $13,000 |
| Claude Opus 5.5 | $0.088 | $0.050 | $5,000 |
| GPT-6.1 Sol or Claude Sonnet 5.5 | $0.044 | $0.025 | $2,500 |
| GPT-6.1 Terra | $0.022 | $0.0125 | $1,250 |
Long prompts are the trap: 300,000 input tokens and 2,000 output tokens cost $6.15 on Astra, against $3.10 at the standard rate and $1.24 on Claude Opus 5.5, which has no long-context surcharge. Cost per task can still favor Astra: at maximum effort, Artificial Analysis measures $6.24 per task on its v5.0 index against $10.04 for Opus 5.5, because Astra generates 54 million tokens against 220 million (details in Claude Opus 5.5 vs GPT-6 Astra).
Is GPT-6 Astra the best model right now?
Readings of October 27, 2026; leaderboards change every week.
Not across the board. Astra leads ARC Prize's abstract-reasoning tests but trails Claude Opus 5.5 on the broadest independent index and on coding agents in a terminal, and sits far from the top of Arena's user votes:
| Test | What it measures | GPT-6 Astra | Leader |
|---|---|---|---|
| Artificial Analysis index v5.0 | Nine evaluations of knowledge work, coding, science and general capability | 57 at max effort, second model | Claude Opus 5.5: 58 |
| Terminal-Bench 4.0, official board | Terminal tasks, in each vendor's agent | 58.2% in Codex, tied 3rd with GPT-6.1 Sol | Claude Opus 5.5: 64.8% |
| ARC-AGI-2, ARC Prize | Abstract puzzles, with cost per task | 95.0% at max effort, $1.12 per task | GPT-6 Astra |
| ARC-AGI-3, ARC Prize | Reasoning in interactive environments (standard harness) | 62.7% at max effort | GPT-6 Astra; no Claude Opus 5.5 result |
| Arena, text | User preference in blind conversations | 1476 points, 32nd | Gemini 4 Argon: 1517 |
Three details matter more than ranks. On the v5.0 index, which is not comparable with the early-October version 4.3.2, Astra beats Opus 5.5 at low, medium and high effort (55 against 52 at high) and Opus 5.5 only pulls ahead at xhigh and max. Cheaper models are closing in: GPT-6.1 Sol scores 94.2% on ARC-AGI-2 for $0.25 per task, and on ARC-AGI-3 GPT-6.1 Sol (52.7%) and Gemini 4 Argon (49.8%) come next. And Astra is still slow: about 71 output tokens per second at max effort, against 98 for Opus 5.5 and 91 for GPT-6.1 Terra. How to read these tables: our AI model map.
What does the “Critical” cyber rating mean for security teams?
It means OpenAI judges that Astra, with the right tools and access, can find unknown vulnerabilities and build ways to exploit them, so it ships with stronger cyber safeguards. Plan for refusals, and for an approval process before any offensive use. It is no longer alone: according to its system card, GPT-6.1 Terra also received the “Critical” rating and shares the safeguards of Astra and GPT-6.1 Sol.
The system card gives the evidence: 100% on ExploitBench even at the lowest effort tested (OpenAI flags possible contamination), 99.2% of SRE-Bench reverse-engineering challenges against 68.7% for GPT-5.6 Sol, and previously unknown vulnerabilities found and used in internal tests. Access runs through Daybreak, OpenAI's cyber programs: the access_programs.cyber parameter grants nothing by itself, and on Astra and GPT-6.1 Sol reduced refusals require Daybreak Red approval for the organization plus access enabled for the project. Daybreak Blue alone is not enough.
The monitorability caveat. The card says Astra controls its chain of thought better than GPT-5.6 Sol (60.9% against 16.1% in a controllability test), and the UK AI Security Institute found reasoning summaries missing on up to 80% of long simulated cyber tasks. In its favor, its misaligned outcomes in realistic work were 3.4%, against 18.8% for GPT-5.6 Sol.
Give Astra minimal permissions, human approval before irreversible actions and a log of every tool call: audit what it does, not what it writes while reasoning. The effect on patch cycles is covered in cyber-capable frontier models.
When is Astra worth it against Opus 5.5, GPT-6.1 Sol or GPT-6.1 Terra?
When the task is hard, success matters more than the price per call and your tests show Astra solving it more often. For volume it is rarely the answer: GPT-6.1 Sol and Claude Sonnet 5.5 cost a fifth as much per token, and GPT-6.1 Terra a tenth.
| Job | Start with | Why |
|---|---|---|
| Coding agents in a terminal | Claude Opus 5.5 or Sonnet 5.5; Astra as a challenger | Terminal-Bench 4.0: 64.8% and 61.8% against 58.2% |
| Hard, novel reasoning and planning | GPT-6 Astra at high effort or above; GPT-6.1 Sol if cost matters | Best ARC-AGI-2 and ARC-AGI-3 results |
| Computer use | GPT-6.1 Terra, GPT-6 Astra and Claude Opus 5.5, side by side | OpenAI says Terra matches Astra on Agents' Last Exam at a tenth of the price per token; we found no common independent result |
| Documents over 272,000 tokens | Claude Opus 5.5 or Sonnet 5.5 | No surcharge, against double the input price on Astra |
| Customer service, high-volume chat | GPT-6.1 Terra, GPT-6.1 Sol or Claude Sonnet 5.5 | A tenth to a fifth of the price, and faster output |
Three figures from the Artificial Analysis v5.0 index sum up the trade-off: GPT-6.1 Sol at maximum effort scores 55, two points below Astra, for $1.27 per task against $6.24; GPT-6.1 Terra scores 51 for $0.96; and Claude Opus 5.5 at xhigh effort scores 57 for $6.05. More in our Claude Opus 5.5 analysis.
What changes for companies in Colombia and the EU?
Mostly where your data is processed and what you sign. Astra has no Colombian region and, for EU residency, the clearest route is OpenAI's own API, after approval.
Europe. OpenAI processes Astra in Europe (EEA and Switzerland) if your organization is approved for abuse-monitoring controls, such as zero data retention, and signs a Modified Retention amendment; it costs 10% more, and the Fast and Ultrafast modes are excluded, whereas both support EU residency on GPT-6.1 Sol. Microsoft launched Astra in Foundry with Global and US Data Zone deployments and announced Standard deployments in the EU Data Zone on September 22: confirm the region in your subscription before sending data. In Bedrock's European regions AWS offers only global routing, which it describes as the option for workloads without residency needs.
Data use. By default OpenAI does not train on API data and keeps abuse-monitoring logs for up to 30 days; Microsoft says Foundry prompts and outputs do not train the models either.
Colombia. Sending personal data to Astra is an international transfer or transmission under Law 1581 of 2012, whatever the channel: settle authorizations and processor contracts first, and budget for billing in US dollars. In the EU, general-purpose model duties fall on OpenAI, but if you put an Astra-based chatbot in front of people, Article 50 of the AI Act requires telling them they are dealing with an AI, since August 2, 2026.
Processing region, retention, notice of model changes or retirement and, for security teams, your Daybreak status.
How do you test Astra before committing to it?
Put it against your current model on your own tasks and decide by cost per solved task. Our method (30 fixed prompts per client, five engines per run, Spanish, English and French) is in how we choose a model.
- Pick two or three routes where a stronger model could change the outcome.
- Write real prompts with automatic pass or fail checks, in your clients' languages.
- Run Astra at
medium,highandxhigh, and the same prompts on Claude Opus 5.5, GPT-6.1 Sol and, for computer use or high volume, GPT-6.1 Terra, several times each. - Log success, tokens, latency and refusals, then compute cost per solved task with caching, the 272K rule, regional uplift and tool fees.
- Settle residency, retention and contract terms before any personal data goes in, and re-run the suite at every release (GPT-6.1 Sol arrived 26 days after Astra, GPT-6.1 Terra 53).
Add Astra as a challenger on your hardest route, not as a default. If it wins there by a clear margin, pay for it on that route only.
Key takeaways
- GPT-6 Astra costs $10/$50 per million tokens, unchanged since launch; above 272,000 input tokens the whole request pays $20/$75.
- On October 27, 2026 it leads ARC-AGI-2 and ARC-AGI-3, but Claude Opus 5.5 beats it on the Artificial Analysis v5.0 index (58 against 57) and Terminal-Bench 4.0.
- It is OpenAI's first model rated “Critical” for cyber capability: reduced refusals require Daybreak Red approval for your organization.
- Its reasoning is harder to monitor: audit actions and tool calls, not the chain of thought.
- For volume, GPT-6.1 Sol and Claude Sonnet 5.5 cost a fifth as much and GPT-6.1 Terra a tenth; keep Astra where your tests justify it.
Sources
- GPT-6 Astra: model page
- Models: choosing a model
- GPT-6.1 Sol: model page
- GPT-6.1 Terra: model page
- Reasoning models
- API pricing
- GPT-6 Astra system card (updated September 29, 2026)
- Daybreak: cybersecurity access programs in the API
- Your data: retention, zero data retention and data residency
- Introducing GPT-6.1 Terra
- OpenAI launches GPT-6.1 Terra for precise computer use
- OpenAI launches GPT-6.1 Terra with cheaper computer use and disclosed agentic limits
- OpenAI launches GPT-6.1 Sol, says it nearly matches GPT-6 Astra and costs less
- OpenAI launches dots: always-on GPT-6 Astra agents that work from their own cloud computers
- GPT-6 Astra: frontier intelligence for work, now generally available in Microsoft Foundry
- GPT-6 Astra, Sol and Luna for production AI agents in Microsoft Foundry
- GPT-6 Astra model card
- Pricing
- Gemini Developer API pricing
- Gemini API release notes (Gemini 4 Argon)
- AI model leaderboards (Intelligence Index v5.0)
- GPT-6 Astra: intelligence, performance and price
- Intelligence Index methodology and version history
- Terminal-Bench 4.0 leaderboard
- ARC-AGI leaderboard
- Text leaderboard (updated October 22, 2026)
Editorial note: this analysis reflects the public information available on the review date. Models, prices and rules change fast; every third-party figure links to its source, and our opinions are labeled as such. Spotted an error? Write to contact@slash-digital.io.
The questions we hear often
When was GPT-6 Astra released?
OpenAI released it on September 3, 2026, in stages. It is available in OpenAI's API, in Microsoft Foundry since September 3 and on Amazon Bedrock since September 8. OpenAI shelved its successor, GPT-6.1 Astra, on September 28, and as of October 27 Astra remains its flagship.
How much does GPT-6 Astra cost?
$10 per million input tokens and $50 per million output tokens, with cached input at $1. Above 272,000 input tokens the whole request pays $20 and $75; Batch and Flex cost half, Fast mode double, Ultrafast six times as much, and regional processing adds 10%.
Is GPT-6 Astra better than Claude Opus 5.5?
It depends on the task. On October 27, 2026, Opus 5.5 led the Artificial Analysis v5.0 index (58 against 57) and the official Terminal-Bench 4.0 board (64.8% against 58.2%) at token prices 2.5 times lower; Astra led ARC-AGI-2 and ARC-AGI-3 and cost less per index task ($6.24 against $10.04 at maximum effort). Test both on your own prompts.
Can GPT-6 Astra be used for penetration testing?
Only within OpenAI's safeguards. Reduced refusals on Astra require Daybreak Red approval for your organization and access enabled for the project; Daybreak Blue approval alone does not authorize them.
Can GPT-6 Astra process data in the EU?
Yes, through OpenAI's regional processing in Europe (EEA and Switzerland), after approval for abuse-monitoring controls and a Modified Retention amendment, at a 10% premium. Astra's Fast and Ultrafast modes are not available with EU residency.
More analysis to read next
The AI model map, October 2026
Claude Opus 5.5 and Sonnet 5.5, GPT-6 Astra, Gemini 4 Argon, Grok 4.7, Muse Spark: who leads in October 2026, what each price tier costs and what to test.
ModelsReasoning models: when paying for thinking pays off
Thinking costs tokens and seconds. How Anthropic, OpenAI and Google expose effort, where it pays, where it doesn't, and how to tune it by cost per solved task.
ModelsClaude Opus 5.5: what changes for businesses
Launched September 22, 2026: cheaper than Opus 5, Fable 5.1-level results per Anthropic. Pricing, benchmarks, breaking changes and when to use it.
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