GPT-6 Sol Description
GPT-6 Sol is a frontier AI model from OpenAI built for professional knowledge work, software development, business automation, computer use, and agentic applications. It brings many of the advances introduced with GPT-6 Astra to a model optimized for greater cost efficiency and higher-volume use. GPT-6 Sol can apply configurable reasoning effort to complex tasks, giving developers and users control over how much computation is used for different workloads. Its coding capabilities support long-horizon software engineering, codebase modification, debugging, testing, and agent-driven development in tools such as Codex. For professional workflows, the model can work across applications and tools to complete multi-step tasks in areas such as sales, marketing, operations, finance, support, and HR. OpenAI also reports improved factuality compared with GPT-5.6 Sol, reducing errors on its internal evaluation of difficult real-world conversations. Computer-use capabilities allow Sol-powered agents to navigate software interfaces and perform extended workflows that require multiple actions and decisions. Enhanced prompt caching provides higher cache-hit rates and discounts on reused input context, making the model better suited to persistent agents and long conversations. GPT-6 Sol is available to developers through the OpenAI API as gpt-6-sol and is also offered in ChatGPT Work and Codex.
Pricing
Output: $10 per 1 million tokens
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GPT-6 Sol Features and Options
GPT-6 Sol User Reviews
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Likelihood to Recommend to Others1 2 3 4 5 6 7 8 9 10
Frontier at a lower cost than Astra Date: Sep 23 2026
Summary: Overall, GPT-6 Sol feels like the practical flagship. It is powerful enough for demanding coding and long-running agents, but affordable enough that I can actually use it as a daily workhorse.
Positive: What I like most is that it gives me a lot of Astra’s capability without feeling like I am burning premium-model money on every task. I have been using it for coding, agent workflows, research, and larger technical projects where I need strong reasoning but still care about speed and cost. Tool support is another big strength. Sol can work with web search, files, code execution, shell access, computer use, MCP, and function calling, so it feels much more useful as an agent model than something that only generates text.
Negative: The only real downside is that when I am dealing with the absolute hardest reasoning problem, I may still step up to Astra. But for most serious day-to-day development and agent work, Sol is the model I would rather run heavily.
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