OpenAI says it can fill forms, update CRM records, organize calendars, research online, draft documents, analyze scientific data, generate plots, create websites, run frontend QA, install software, and troubleshoot what it sees on screen. That sounds boring until you remember that most work is boring. Most knowledge work is not “write me a poem about databases.”
The chatbot era was about answers. Astra feels like it is about action.
It is opening five tabs, checking a spreadsheet, fixing a doc, finding the missing field in a CRM, comparing two broken dashboards, making a deck presentable, and then writing the follow-up email. If Astra is genuinely good at that, it matters.
Astra scored at roughly 40 minutes per task, compared with and roughly 75 minutes per task. So the claim is not just that it is smarter. The claim is that it gets more done, faster. That is the number businesses will care about.
Astra vs Claude Fable 5.1
This is the comparison everyone actually cares about. This is my take:
Astra is the model I’d reach for when the job involves computer use,
tool use, scientific work, porting large apps, browser automation, 3D reasoning, Blender, game creation, or long multi-step workflows.
Claude Fable 5.1 is still the one I’d trust heavily for clean mergeable code,
frontend design judgment, careful writing, and reasoning-heavy work where it already benchmarks well.
GPT‑6 Astra brings together years of research and big bets across pre-training, reinforcement learning, and alignment. Astra is state-of-the-art on computer use, browsing, software engineering, cybersecurity, science, and professional work. Astra saturates FrontierMath Tier 4 with a 98% score, having already helped solve long–standing open problems in mathematics. Astra also saturates ARC-AGI-3 with a 99.9% score and ExploitBench with a 100% score. It also sets a new frontier on computer and browser use, handling the most demanding professional work with unmatched speed, accuracy, and judgment.
GPT‑6 Astra is rolling out today to a limited set of organizations and over the coming days will become available to all ChatGPT Plus, Pro, Business, and Enterprise users, as well as through the OpenAI API, Microsoft Azure, and AWS Bedrock.
What is GPT-6 Astra?
GPT-6 Astra is OpenAI’s new frontier flagship, succeeding GPT-5.6 Sol as the top model for reasoning, computer use, and agentic work.
OpenAI positions it around three areas:
- State-of-the-art computer use
- A step change in professional work
- A jump in cybersecurity capability that crosses the Critical threshold under its Preparedness Framework.
The most useful benchmark headline for practitioners is OSWorld 2.0, where Astra scores 72.6% in about 40 minutes per task, compared with GPT-5.6 Sol’s 65.7% at roughly 75 minutes.
That combination of higher accuracy and lower wall-clock time is the difference between an agent you babysit and one you can hand a task to.
Astra ships alongside an updated Codex harness that OpenAI says delivers 1.9x faster task completion versus the current GPT-5.6 Sol experience on the Mind2Web benchmark.
It is available as gpt-6-astra in the OpenAI API and through Amazon Bedrock, with a GPT-6 Astra Pro tier for Pro, Business, and Enterprise plans.
What’s New With GPT-6 Astra?
Astra’s changes cluster around agentic execution: using a computer, producing finished professional artifacts, maintaining context across long coding sessions, and staying within authorized boundaries.
Here are the capabilities that stand out.
Produce finished documents, slides, and spreadsheets
Astra is trained to output polished professional artifacts that follow your templates instead of generic first drafts.
It creates documents, presentations, spreadsheets, and analyses that match your writing and visual style, and it pulls only the context that matters into the output rather than padding it with everything it knows.
OpenAI’s own demo has Astra building a slide deck about a fictional model from a handful of template slides, keeping the tone and layout consistent throughout.
For anyone who has spent an hour reformatting an LLM’s markdown dump into a corporate template, that template adherence is the part I’d want to test first.
With Sites in ChatGPT, Astra can create, host, and share websites, web apps, and games directly from a prompt, applying stronger visual judgment to renderings than earlier models.
OSWorld 2.0 and computer use
Astra scores 72.6% on the OSWorld 2.0 offline set, versus 65.7% for GPT-5.6 Sol and 70.2% for Claude Opus 5.
OSWorld measures whether an agent can complete real desktop tasks like navigating apps and manipulating files, so it is the closest proxy to “can this thing actually use a computer for me.”
On ScreenSpot-Pro, which tests grounding UI elements on a screen without tools, Astra hits 92.7% against GPT-5.6 Sol’s 76.9% and Claude Fable 5’s 87.3%.
On Agents’ Last Exam, it reaches 59.3%, ahead of Claude Opus 5’s 55.5% and GPT-5.6 Sol’s 53.6%, while using roughly 65% fewer output tokens than Opus 5.
GPT-6 Astra Pricing and Availability
GPT-6 Astra is rolling out to a limited set of organizations first, then to all ChatGPT Plus, Pro, Business, and Enterprise users over the coming days, plus the OpenAI API and AWS.
Enterprise admins can enable it per workspace, and it is off by default at launch. Pro, Business, and Enterprise plans also get GPT-6 Astra Pro.
For developers, the model is available as gpt-6-astra in the OpenAI API and in Amazon Bedrock.
Standard API pricing is:
- Input: $10 per million tokens
- Output: $50 per million tokens
- Fast mode: up to 2.5x Standard speed at 2x Standard price (roughly $20 input, $100 output per million tokens)
- Separate rates apply to cache reads and writes
For context, that is well above GPT-5.6 Terra’s $2/$12 rates from our earlier coverage, and above Claude Opus 5’s $5/$25.
Astra is priced as a frontier reasoning and automation model, not a bulk-text workhorse.
It supports Zero Data Retention for eligible API customers, and usage is included within existing subscription allowances with the option to buy additional credits.
Drive your computer end-to-end
Astra can operate a computer directly, handling the kind of tedious multi-step work that usually eats up an afternoon.
Some good examples include:
- Filling out a batch of expense forms
- Updating records in a CRM
- Running frontend QA checks on a site you just built
- Installing and troubleshooting software while watching what happens on screen.
On latency simulations on OSWorld 2.0, Astra hits 72.6% at roughly 40 minutes per task versus GPT-5.6 Sol’s 65.7% at roughly 75 minutes, a 47% cut in time per task.
OSWorld 2.0 measures whether a model can actually operate a computer, such as navigating real interfaces, clicking, typing, and completing multi-step tasks the way a human would.
The 47% cut in time per task matters as much as the accuracy gain because agent cost scales with wall-clock time; a model that finishes in 40 minutes instead of 75 is not just faster, it is roughly half the price to run on the same workload.
That being said, independent ARC Prize testing shows Astra’s headline computer-use and reasoning numbers are highly -dependent.
On ARC-AGI-3, the standard stateless harness produced scores from roughly 17% to 63% depending on reasoning tier, while the provider adapter harness that preserves reasoning state reached the marketed ~99.9%.
If you call the model statelessly, expect lower numbers than the launch charts.