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Sol is fast, resourceful, and unusually easy to steer—but Fable still gets the assignments we want to hand off completely.
We missed GPT-5.6 Sol while it was gone.
For about a month, Sol had been everywhere in our work. It kept Dan Shipper at inbox zero and tracked decisions across meetings and Slack that he might otherwise have missed. It kept up with Austin Tedesco as he moved from campaign idea to email to landing page to experiment without making him repeat himself or lose focus. It retrieved files and context for me (Katie Parrott) so quickly that it completely rewired how I work with models day to day.
Then, at the end of June, we lost access while Sol went through government review. Dan said returning to other models—even with Fable available—felt like going back to the Stone Age. Austin compared using GPT-5.5 to “trying to shoot a basketball that’s twice as heavy as the one I’m used to using.” In our Sonnet 5 Vibe Check, we talked about the revolution of rising expectations. Our time without Sol underscored just how quickly you can get used to a higher standard of living—and how much it hurts when that progress rolls back.
GPT-5.6 Sol is a serious step change in model capability for day-to-day knowledge work. It’s fast enough to keep up with you, resourceful enough to find the context it needs to do good work, persistent when the first approach fails, and responsive when you change direction.
For months now, we’ve been tracking a split in the way we work with AI. Sometimes, you want to delegate—give the model an assignment, send it off, and come back to something you can work with. Other times, like when you’re working on a long complex report or a big writing project, you want to collaborate—stay close to the work, see options quickly, and make decisions that guide the outcome as the work evolves. Sol’s mix of speed, intelligence, and steerability make it a delight for that second kind of work.
Fable still gets the biggest, most ambiguous assignments—the ones where planning and making decisions about the work is a large part of the task. Austin uses it for long-running, go-to-market engineering tasks, like setting up new user journeys, testing them end to end as different audience types, and working in a loop to continue to improve the flow. Dan goes to it for benchmarking projects that involve a lot of synthesis, dataset development, and experimentation. But once we’re done delegating and ready to dig in, GPT-5.6 Sol is where we want to spend our time.
New model releases seldom come unaccompanied these days, and today is no exception. In addition to GPT-5.6, OpenAI is merging the ChatGPT and Codex desktop experiences into one unified app. The move appears to be a bid to build a bigger tent for agentic work—one that pulls in more of ChatGPT’s 800 million-plus users.
Our time with the new app experience has been limited, but so far, like Codex before it, it’s an app we want to spend time in. Which is great news, because GPT-5.6 Sol is a model we want to spend time with. Dan’s analogy is that Sol is a Porsche and Fable is a warp drive. Fable can take you across the galaxy, sure. But most of the time, you’re not going to space—you’re just trying to get around town. Sol is the model that lets you travel in style.
More on our experience driving it below.
OpenAI calls Sol its “strongest model yet,” but the evidence it released is concentrated in a particular kind of work: difficult assignments that require an agent to plan, use tools, and keep working. The company says Sol sets a new state of the art on Terminal-Bench 2.1, which tests command-line tasks that require planning, iteration, and tool use. It also reports stronger results than GPT-5.5 on a long-running biology benchmark and the company’s best cybersecurity performance.
A new max reasoning setting gives one Sol agent more time to work, while an ultra mode coordinates several agents on the same assignment. OpenAI is also debuting new model tiers below the Sol tier: Terra is the lower-cost model for everyday work, and Luna is the fastest and least expensive. OpenAI says those names will persist as capability tiers even as the models within them advance.
OpenAI is debuting GPT-5.6 alongside another major product update: merging the ChatGPT and Codex desktop experiences into one app. ChatGPT Work is geared to take on the majority of knowledge work tasks, while Codex gets its own dedicated tab for technical work.
On the pricing front, OpenAI’s three tiers map closely onto Anthropic’s trio of models. Sol costs $5 per million input tokens and $30 per million output tokens, matching Opus 4.8 on input but costing $5 more on output. Terra costs $2.50 and $15, compared with Sonnet 5’s introductory $2 and $10 through August 31; Sonnet then rises to $3 and $15. Luna costs $1 and $6, matching Haiku 4.5 on input and costing $1 more on output.
Sol
$5 input / $30 output
per million tokens
Terra
$2.50 input / $15 output
per million tokens
Luna
$1 input / $6 output
per million tokens
“GPT-5.6 Sol in ChatGPT Codex and Work is obviously the gold standard for knowledge work. I reach for it first as my daily driver for pretty much every task. It’s not Fable-level—I flip back to Fable for my hardest tasks—but for everything else 5.6 is my go-to.”
“Sol is a workhorse model. I trust it more as a collaborator than previous GPT models: It’s thorough and helpful, doesn’t do stupid things, and is creative enough to just get shit done. Fable is still better at complex, long-horizon tasks, but Sol can do about 90 percent of what Fable can do.”
“Sol is the best knowledge-work model I’ve used, inside the best app for knowledge work. It now handles at least 80 percent of my day-to-day tasks and can take on basically anything my brain naturally thinks to try. I still want Fable running in the background for the work I have to push myself to consider possible.”
“Sol has turned into my daily driver. I still prefer Fable's sharp spiky intelligence and use of context but GPT-5.6 is the best and most cost-effective all round model that I would use every day.”
“The combination of 5.6 and Codex has seriously transformed the way I approach work from day to day, and for that alone, I consider this to be a paradigm-shifting model. For writing specifically, I’ve found Sol to be stronger than Claude models at using context like style guides and samples to inform its work, and its speed and ability to take direction make it great for collaborative writing. But truly human-level prose remains an elusive target for frontier models in a way that makes me wonder whether we’ve reached a plateau in what AI is capable of on the writing front.”
“Sol is making me trust GPT models for coding again. It does less random stuff, needs fewer follow-ups, and carries more work end to end than GPT-5.5. I still prefer Fable, and sometimes Opus, partly because Codex hides too much of the process and I don’t always understand how it got there.”
“GPT-5.6 Sol has been my go-to model for the past month—and the most reliable one I’ve used. Since Fable launched, my workflow has settled into a powerful split: Fable acts as the orchestrator, shaping the plan, and Sol executes it. That combination has helped me ship a remarkable amount for Monologue, from major improvements to Notes to building the entire Monologue web app in a day. Sol remains the model I trust most for day-to-day development of Monologue’s native apps.”
“So far, I prefer Sol for knowledge work because it gives me granular control without making me manage every small decision. It can take initiative, ask useful questions, and still let me see where the work is going. Early testing felt truly magical with its abilities compared to 5.5, but a late-testing calculation error gave me whiplash. I've been using Codex as my primary work surface for awhile, so if I can rebuild trust, Sol will be a game-changer for me.”
“Sol is faster and more meticulous than Fable; the GPT model is my new go-to for helping me with spot edits that involve dejargonifying overly technical language or rewriting lines that, even if human-written, sound too much like AI. If I could only pick one model for collaborative work, it would be Sol. That said, Fable has better, dare I say, taste; I trust its judgment more on large architectural decisions and UI design. And I don’t have to pick one model. I can have Fable tell Sol or Opus/Sonnet to execute, or have Sonnet 5 ask Fable to consult on tough problems. I don’t use these models in isolation, and I don’t think others should either.”
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