OpenAI Canceled Its Most Powerful Model, Then Shipped an Always-On Agent Platform
OpenAI Canceled Its Most Powerful Model, Then Shipped an Always-On Agent Platform
Section titled “OpenAI Canceled Its Most Powerful Model, Then Shipped an Always-On Agent Platform”OpenAI held DevDay 2026 on September 29 in San Francisco and made more than 20 announcements (OpenAI). About 2,500 developers attended (The Next Web). The company launched Dots, an always-on agent; GPT-6.1 Sol, a budget flagship model; and a $500-a-month Pro plan (The Next Web).
One day earlier, OpenAI canceled GPT-6.1 Astra because the model did not stay in scope and authorization (Reuters). We covered that cancellation yesterday (our Astra post).
The pattern is the story. OpenAI held back the model that would not stay in scope, then pushed harder on agents that work on their own. Both moves are about the same thing: trust and control over autonomous work.
What Dots is, technically
Section titled “What Dots is, technically”Dots are always-on agents that live inside ChatGPT (OpenAI). Each dot runs on GPT-6 Astra, OpenAI’s flagship model (OpenAI). Each one gets its own cloud computer and its own browser (VentureBeat). Through OpenAI’s plugin ecosystem, a dot can connect to more than 4,000 apps (OpenAI).
The difference from a normal chat model: a dot keeps working when you step away (The New Stack). It carries what it knows between ChatGPT, Slack, and Microsoft Teams (The New Stack). It learns from feedback over time (OpenAI). You reach it from desktop, web, mobile, Slack, and Teams (DataCamp).
Two properties matter for developers who run agents at work:
- Isolation. Each dot works on its own cloud computer. Your machine and its contents stay separate unless you connect them explicitly (OpenAI).
- Credential separation. For supported websites, dots use saved passwords without exposing the password to the model (OpenAI).
OpenAI adds guardrails on top. Dots get read-only research and auto-review steps (The New Stack). You set boundaries, follow progress, and stay involved in decisions that need you (OpenAI). Your first dot is included on Pro and Business Premium plans in eligible markets (DataCamp).
The launch is OpenAI’s answer to Meta’s Muse in the race to sell autonomous AI (Reuters).
GPT-6.1 Sol: the economics of agent loops changed
Section titled “GPT-6.1 Sol: the economics of agent loops changed”OpenAI also released GPT-6.1 Sol, an upgrade to GPT-6 Sol (OpenAI). It nearly matches GPT-6 Astra on agentic coding, computer use, and professional work at one-fifth of Astra’s standard token prices (TechCrunch).
| Rate | Price per 1M tokens |
|---|---|
| Input | $2.00 |
| Cached input | $0.10 |
| Output | $10.00 |
For comparison, GPT-6 Astra lists at $10 input, $50 output, and $1 cached input (OpenAI). Sol’s cached input price is 95% below its standard input price and 50% below GPT-6 Sol’s cached input price (OpenAI).
The cached-token number matters more than the headline rate. Long agent loops reuse the same context across requests. A cheaper cache directly cuts the cost of multi-step agent runs.
GPT-6.1 Sol is available today to Plus, Pro, Business, Enterprise, and Edu users in ChatGPT Work and Codex (OpenAI). It is not yet available in Chat (TechCrunch). Developers reach it through the API as gpt-6.1-sol (OpenAI).
On Terminal-Bench Science 0.1, Sol costs $5.47 per task at maximum effort (The Next Web). That compares with $23.21 for Claude Opus 5.5 and $23.80 for Astra (The Next Web). Astra still scores highest of the tested models at 68.1% (The Next Web).
A DataCamp test drove a codebase migration agent end to end for $0.7082, with 91% of input tokens served from cache (DataCamp). That run used GPT-6 Sol at the same standard prices. The point stands: cheap cached input makes long agent runs economical.
Ultrafast, the Pro 500 plan, and the Pro 200 cut
Section titled “Ultrafast, the Pro 500 plan, and the Pro 200 cut”OpenAI added an Ultrafast speed tier. In Codex it generates up to 300 tokens per second, about eight times standard speed (OpenAI). In the API it runs up to six times faster (OpenAI). GPT-6 Astra Ultrafast is available today in the API and in ChatGPT Work and Codex (OpenAI). GPT-6.1 Sol Ultrafast is coming soon (OpenAI).
The new Pro 500 plan costs $500 a month (The Next Web). It offers the highest usage allowance at 25 times the ChatGPT Plus allowance and includes Ultrafast (OpenAI).
Existing Pro 200 subscribers take a cut. From October 30, their included usage in ChatGPT Work and Codex falls from 20 times to 10 times the Plus allowance (The Next Web). GPT-6 Pro chat messages fall from 200 to 100 a week (The Next Web).
ChatGPT Space
Section titled “ChatGPT Space”ChatGPT Space replaces Library as a shared home for a team’s files and documents (The Next Web). Its main format is pages, documents that teammates, ChatGPT, and dots can edit together (The Next Web). Space is available on Pro, Business, and Enterprise plans on web and desktop (The Next Web).
What to do about it
Section titled “What to do about it”The DevDay batch changes the planning math for teams that build on agentic tooling.
- Price agent runs on cached input, not the headline rate. Sol’s $0.10 cached input changes the unit cost of long agent loops (OpenAI). Recompute your per-task cost with a cache-heavy profile before you pick a model.
- Treat agent scope like a network boundary. Dots isolate work on a separate cloud computer and keep credentials out of the model’s reach (OpenAI). Apply the same rule to your own agents: least privilege per step, explicit authorization for destructive actions.
- Plan for always-on compute as a new surface. An agent that keeps working after you log off is a separate runtime to monitor, audit, and kill (The New Stack).
- Watch the plan re-tiering. A flagship price drop can shift the cost of your whole workload. Re-evaluate your provider mix when a near-flagship model ships at one-fifth the price (The Next Web).
The launch side of this week matters as much as the cancellation. OpenAI proved it will refuse to ship a model it cannot control (Reuters). It also proved it will ship agents built to run without you. Build your automation with the same rule: verify scope before you trust an agent with access.