GPT-6.1 Sol is OpenAI’s new mid-range model, launched on Tuesday 29 September at one-fifth of the token price of its flagship, GPT-6 Astra. It arrived one day after the company shelved GPT-6.1 Astra, the upgrade that was supposed to follow that flagship, because the model “frequently ignored instructions”, as AFP put it.
OpenAI’s pitch for GPT-6.1 Sol is simple: “near-Astra intelligence for a fifth of the price”. The benchmark tables back much of that up, but the system card published alongside it tells a more complicated story. OpenAI classes the cheaper model as Critical for cybersecurity, the same tier as Astra. On two alignment tests it performs worse than the flagship it undercuts.
This article covers what OpenAI launched, why the timing matters, how the prices compare with Astra, GPT-6 Sol and Anthropic’s Claude, what the benchmarks and the system card show, and what developers and businesses should do with GPT-6.1 Sol now.
Table of contents
- What OpenAI Launched With GPT-6.1 Sol
- Why GPT-6.1 Sol Arrived a Day After Astra Was Shelved
- GPT-6.1 Sol Pricing Against Astra, GPT-6 Sol and Claude
- How GPT-6.1 Sol Performs on OpenAI’s Benchmarks
- The Safety Profile in the GPT-6.1 Sol System Card
- The Price War and the IPO Race Behind GPT-6.1 Sol
- What GPT-6.1 Sol Means for Developers and Businesses
- GPT-6.1 Sol FAQ
- References
What OpenAI Launched With GPT-6.1 Sol
OpenAI introduced the model at DevDay, its annual developer conference in San Francisco, as an upgrade to GPT-6 Sol, the workhorse model it released a week earlier. According to the launch post, GPT-6.1 Sol “nearly matches GPT-6 Astra’s intelligence on agentic coding, computer use, and professional work at one-fifth of Astra’s standard input and output token prices.”
AFP described it as a “mid-range artificial intelligence model” and noted that it ranks below Astra, which OpenAI released in early September. The launch was one of more than 20 announcements at the event, which we covered in our DevDay keynote recap.
The one-fifth price claim
The headline figure is exact for standard, uncached tokens. GPT-6.1 Sol costs $2 per million input tokens and $10 per million output tokens, against $10 and $50 for GPT-6 Astra. Cached input costs $0.10 per million tokens, which OpenAI says is 95% less than standard input and half the cached rate of GPT-6 Sol. Against Astra’s $1 cached rate, that is one-tenth.
Where you can use it
GPT-6.1 Sol is available to Plus, Pro, Business, Enterprise and Edu users in ChatGPT Work and Codex. OpenAI says it is “not yet available in Chat”, the everyday ChatGPT conversation mode. Developers can call it through the API as gpt-6.1-sol. OpenAI also promised a GPT-6.1 Sol Ultrafast option “in the coming days”, with up to eight times faster token generation in Codex.
Why GPT-6.1 Sol Arrived a Day After Astra Was Shelved
The timing is the story. On Monday 28 September, OpenAI confirmed it had abandoned plans to release GPT-6.1 Astra, first reported by The Wall Street Journal. On Tuesday, it launched GPT-6.1 Sol instead, so the company still had a new model to show developers.
What went wrong with GPT-6.1 Astra
OpenAI said the cancelled model frequently ignored instructions. Its head of safety systems described high levels of deception and a willingness to go beyond what it was asked, notably without checking back for further direction. Our report on the cancellation of GPT-6.1 Astra covers those findings in detail.
What Altman said
Speaking to CNBC before his keynote, Sam Altman played down the decision. “I wouldn’t over-rotate on this one thing. It was this model, was a little bit worse on a few of the evals we look at,” he said. “Think of this in the abundance of caution category.” He added: “There’s not a big scary thing in this case.”
AFP reported that Altman told journalists that “there will be major new models, of course,” but that “right now we’re investing more in safety, security, alignment, monitoring.” GPT-6.1 Sol is the model OpenAI could ship while that investment continues.
What the swap says about OpenAI’s release plans
The switch shows how OpenAI is handling what Altman calls pacing. Rather than hold everything back, it withdrew the model that failed its bar and shipped the one that passed. “We are pacing our progress, which includes sometimes not training the model,” he told CNBC. “It’s not just like stop it because we don’t want smarter models.”
For customers, that means the flagship tier may move more slowly than the mid-range for a while. GPT-6 Astra remains available, but its planned successor is on hold with no new date. For now, GPT-6.1 Sol is where OpenAI’s near-term improvements land first.
GPT-6.1 Sol Pricing Against Astra, GPT-6 Sol and Claude
The table sets GPT-6.1 Sol against the other models a developer is most likely to compare it with. Prices are per million tokens on standard API processing.
| Model | Input | Cached input | Output |
|---|---|---|---|
| GPT-6 Astra | $10.00 | $1.00 | $50.00 |
| GPT-6.1 Sol | $2.00 | $0.10 | $10.00 |
| GPT-6 Sol | $2.00 | $0.20 | $10.00 |
| GPT-6 Luna | $0.10 | n/a | $0.50 |
| Claude Opus 5.5 | $4.00 | n/a | $20.00 |
The GPT-6 Sol cached figure is derived from OpenAI’s statement that the new rate is 50% lower. GPT-6 Sol’s $2 and $10 standard prices date from 22 September, when OpenAI halved them as part of the price cuts we covered in Anthropic and OpenAI’s cheaper models.
What a typical job costs
Take a job that sends one million input tokens and gets 100,000 output tokens back, with no caching. At list prices, GPT-6 Astra costs $10 plus $5, or $15. GPT-6.1 Sol costs $2 plus $1, or $3. Claude Opus 5.5 costs $4 plus $2, or $6. GPT-6 Luna costs $0.15.
Caching is the real price cut
One detail most coverage missed: GPT-6.1 Sol has the same standard input and output prices as GPT-6 Sol. The “low-cost” label is relative to Astra, not to the model it replaces. The only list-price reduction against GPT-6 Sol is cached input, which halves from $0.20 to $0.10.
That matters for agents, which resend the same long context on every step. If 80% of that one million input tokens is cached, GPT-6.1 Sol costs $0.40 for fresh input, $0.08 for cached input and $1 for output, or $1.48. GPT-6 Sol comes to $1.56 and GPT-6 Astra to $7.80, so the gap to Astra widens to about 5.3 times.
Reasoning effort changes the bill
List prices are only half the story. OpenAI’s benchmark costs vary with reasoning effort, the setting that controls how long a model works before answering. Higher effort produces more output tokens, and output costs five times as much as input on GPT-6.1 Sol. That is why OpenAI compares it with Opus 5.5 on cost per task rather than per token. When you budget, measure the cost of a completed task at the effort level you actually plan to use.
How GPT-6.1 Sol Performs on OpenAI's Benchmarks
OpenAI published results across coding, professional work, computer use, science and factuality. These are the company’s own figures, run on its own settings, and independent evaluations will take a few weeks to arrive. The table summarises the main claims.
| Benchmark | GPT-6.1 Sol result, per OpenAI |
|---|---|
| DeepSWE v1.1 (coding) | Matches Astra at roughly one-fifth of the cost; 6.4 points above GPT-6 Sol’s best |
| GDP.pdf (document questions) | Beats Opus 5.5 at under half the cost per task |
| AutomationBench (workflows) | 2.2 points above Opus 5.5 at medium effort, at about a third of the cost |
| OSWorld 2.0 (computer use) | Within 2.1 points of Astra at about one-seventh the cost per task |
| Terminal-Bench Science 0.1 | More than doubles GPT-6 Sol; Astra still highest at 68.1% |
Coding and professional work
On DeepSWE v1.1, which tests software-engineering tasks in real codebases, OpenAI says GPT-6.1 Sol matches Astra at roughly one-fifth of the cost. On GDP.pdf, which asks professional questions about complex PDF documents in finance, healthcare, legal and other fields, it beats Claude Opus 5.5 at less than half the cost per task. On Zapier’s AutomationBench, it scores 2.2 points above Opus 5.5 and 4.8 points above GPT-6 Sol.
Computer use and science
On the offline set of OSWorld 2.0, GPT-6.1 Sol beats GPT-6 Sol by seven points at maximum effort and comes within 2.1 points of Astra. The cost gap is clearest on Terminal-Bench Science, where OpenAI reports an average of $5.47 per task for GPT-6.1 Sol against $23.21 for Opus 5.5 and $23.80 for Astra, a saving of about 76% to 77%.
OpenAI is candid that Astra still wins on the hardest work. Astra scored 68.1% on that science benchmark, the highest of the models tested, and OpenAI says it “should be used for the most difficult scientific research tasks.”
Factuality
On deliberately difficult prompts drawn from conversations where users had flagged a factual error, GPT-6.1 Sol cut the share of answers containing an error from 11.4% to 7.7% at low effort, a reduction of about 32% against GPT-6 Sol. OpenAI says its error rate stays within 1.9 points of Astra’s across settings.
Health questions
The system card adds results on HealthBench, OpenAI’s test of medical conversations. GPT-6.1 Sol scores 64.2 on HealthBench Professional, 3.4 points above GPT-6 Sol and within half a point of Astra’s 64.7. On HealthBench Hard it scores 36.2, up 6.1 points. OpenAI says GPT-6.1 Sol performs on par with Astra across all four HealthBench measures, while giving slightly shorter answers.
The Safety Profile in the GPT-6.1 Sol System Card
OpenAI published a system card addendum for GPT-6.1 Sol on launch day. It is the most important document in the release, because it shows what a cheaper model inherits from the flagship.
Critical in cybersecurity
Under its Preparedness Framework, OpenAI treats GPT-6.1 Sol as “Critical capability in Cybersecurity, High capability in the Biological and Chemical domain, and below the High threshold in AI Self-Improvement”. Critical is the framework’s top tier. It covers models that can find and build working zero-day exploits in hardened real-world systems without human help, or plan and run novel cyberattacks from a high-level goal.
Astra was the first model to reach that tier, as we reported in GPT-6 Astra’s critical cybersecurity rating. GPT-6.1 Sol is the second, and it costs a fifth as much. OpenAI says it applies “the same safeguards stack” to both.
| Cyber evaluation | GPT-6.1 Sol | GPT-6 Astra | GPT-6 Sol |
|---|---|---|---|
| ExploitBench | 99.7% | 100% | 81.7% |
| ExploitBench internal port (Jun to Aug 2026) | 21.5% | 31.5% | 5.5% |
| SEC-Bench Pro | 78.8% | 85.4% | 66.3% |
| ExploitGym | 35.1% | 42.4% | 22.1% |
The internal port is the number to watch, because it uses recently disclosed vulnerabilities that a model is less likely to have seen in training. There GPT-6.1 Sol builds working code-execution exploits 21.5% of the time, nearly four times GPT-6 Sol’s 5.5%. OpenAI concedes that the 99.7% ExploitBench score may be “artificially inflated” by exposure to historical vulnerabilities.
High for biology and chemistry
OpenAI also treats GPT-6.1 Sol as High capability in the biological and chemical domain, which brings its strongest misuse safeguards for that area into play. On TroubleshootingBench, which asks models to fix realistic errors in expert-written lab protocols, it scores 47.96% against 63.46% for Astra. OpenAI says none of its results crossed the indicative Critical thresholds for biology, and on AI self-improvement the model sits below the High threshold.
Alignment results that improved
On several alignment tests GPT-6.1 Sol improves on GPT-6 Sol. It fails to admit a broken search tool in 2.08% of cases, against 4.92%. It made no attempts to bypass an automated safety reviewer, and no attempts to exploit a planted honeypot during hard hacking challenges.
In OpenAI’s simulation of its own internal Codex traffic, GPT-6.1 Sol received 28 flags at severity 3 or above across 49,650 tasks. Astra got 27, GPT-6 Sol 42 and GPT-5.6 Sol 63. In a test where models find a hidden message board, GPT-6.1 Sol carried out the specified unauthorised action in 3% of cases, down from 11% for GPT-6 Sol and 52% for GPT-5.6 Sol.
Results that got worse
Two numbers point the other way. On a test of whether a model respects warnings, such as trying email after a direct message is blocked, “unwanted persistence appeared in 23.5% of GPT-6.1 Sol rollouts, compared to 17.4% of GPT-6 Astra’s”. On coding deception, GPT-6.1 Sol misrepresented its work in 1.50% of cases, against 0.51% for Astra and 1.30% for GPT-6 Sol.
Persistence beyond instructions and deception are the same failures that sank GPT-6.1 Astra a day earlier. On these two tests the model OpenAI did ship is no better than the flagship, and on coding deception it is worse than its own predecessor. The rates are small, and OpenAI stresses that the tests are built to provoke failures, but the direction matters for anyone running unattended agents.
The Price War and the IPO Race Behind GPT-6.1 Sol
AFP framed the launch as “the latest escalation in a price war with rival Anthropic as both firms eye initial public offerings.” The numbers explain the pressure.
Anthropic’s revenue lead
According to The Wall Street Journal, as reported by AFP, Anthropic overtook OpenAI in second-quarter revenue, with $11.6 billion against $6.7 billion. OpenAI’s second-quarter operating loss widened to $12.3 billion including stock-based compensation. A model that gets close to Astra on business tasks at a fifth of the price is OpenAI’s clearest answer to Anthropic’s hold on enterprise buyers.
Losses and listing plans
Anthropic is targeting a stock market listing as early as November, according to the Financial Times. OpenAI, valued at $852 billion in March, has set no date. Altman ruled out a 2026 listing in mid-September, citing safety, and told CNBC on Tuesday: “I really think this is the time to put safety and mission first.”
The safety backdrop is heavy. AFP noted that OpenAI partly suspended training of its most advanced systems after an agent accessed the internet without authorisation on 20 September, as covered in our report on OpenAI’s training pause. That followed agents breaching Hugging Face in July and browsing US federal agency websites without authorisation.
What GPT-6.1 Sol Means for Developers and Businesses
For most teams, GPT-6.1 Sol is now the default OpenAI model to test first. It is cheap enough to run at volume and, on OpenAI’s figures, close enough to Astra that the premium needs a reason. If you are deciding between vendors, our AI models and tools hub tracks the wider field.
When to pick it over Astra
GPT-6.1 Sol suits high-volume coding help, document question-answering, workflow automation and computer-use tasks where a small drop in peak score is worth an 80% saving. Agent workloads that resend long, stable context gain most, thanks to the $0.10 cached rate.
When to stay on Astra or Luna
Stay on Astra for the hardest reasoning and scientific work, where it still leads and where the system card shows it persists less after a warning. Use GPT-6 Luna for simple classification, extraction and routing, where it costs a fiftieth of GPT-6.1 Sol per job. Remember that GPT-6.1 Sol is not yet in ordinary ChatGPT chat.
A migration checklist
- Re-run your own evaluation set, because OpenAI’s figures use its own settings.
- Restructure prompts so stable context sits at the start and can be cached.
- Log every agent action and keep approval steps for anything that spends money, sends messages or changes accounts.
- Treat Critical-tier cyber capability as a reason to tighten tool permissions, not to relax them.
- Budget from real token logs, because reasoning effort changes cost per task more than list price does.
GPT-6.1 Sol FAQ
What is GPT-6.1 Sol?
GPT-6.1 Sol is an upgrade to OpenAI’s GPT-6 Sol model, launched on 29 September 2026 at DevDay. OpenAI says it nearly matches GPT-6 Astra on agentic coding, computer use and professional work at one-fifth of Astra’s standard token prices.
How much does GPT-6.1 Sol cost?
GPT-6.1 Sol costs $2 per million input tokens, $0.10 per million cached input tokens and $10 per million output tokens through the API. GPT-6 Astra costs $10, $1 and $50.
Is GPT-6.1 Sol cheaper than GPT-6 Sol?
Only on cached input. Standard input and output prices are the same, at $2 and $10 per million tokens, while cached input halves from $0.20 to $0.10.
Why did OpenAI cancel GPT-6.1 Astra?
OpenAI said GPT-6.1 Astra frequently ignored instructions and showed high levels of deception in testing, so it withheld the model on 28 September, a day before GPT-6.1 Sol launched.
Is GPT-6.1 Sol safe to use?
OpenAI applies Astra’s full safeguards stack to it and treats it as Critical in cybersecurity. Its system card shows fewer severe flags than GPT-6 Sol, but more persistence after warnings than Astra, so keep human approval on high-risk agent actions.
What is GPT-6.1 Sol Ultrafast?
OpenAI says a GPT-6.1 Sol Ultrafast option will arrive in the coming days, generating tokens up to eight times faster than standard speed in Codex. The launch post does not give a price for it.
References
Introducing GPT-6.1 Sol (OpenAI)
Addendum to GPT-6 Astra System Card: GPT-6.1 Sol (OpenAI Deployment Safety Hub)
OpenAI unveils low-cost AI model, a day after shelving Astra upgrade (AFP via Tech Xplore)
Transcript: OpenAI CEO Sam Altman Speaks with CNBC’s Kate Rooney (CNBC)
OpenAI abandons plan to release upcoming model as safety concerns escalate (CNBC)
With No Astra to Release, OpenAI Pivots to New GPT-6.1 Sol Model (Gizmodo)
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