&imwidth=800&imheight=600&format=webp&quality=medium "OpenAI launches GPT-6.1 Sol: Near-Astra AI performance at one-fifth the price")
OpenAI has launched GPT-6.1 Sol, a new AI model positioned between GPT-6 Sol and the company’s flagship GPT-6 Astra. OpenAI says GPT-6.1 Sol can approach Astra’s performance on agentic coding, computer use and professional work at roughly one-fifth of Astra’s standard input and output token prices.
The model arrives as developers increasingly use AI agents to handle longer, multi-step tasks. For them, the cost of repeatedly sending context to a model can become a major expense. GPT-6.1 Sol is designed to address that problem while improving on the earlier GPT-6 Sol.
GPT-6.1 Sol pricing: How much does it cost?
OpenAI lists GPT-6.1 Sol at $2 per million input tokens, $10 per million output tokens and just $0.10 per million cached input tokens through its API. Cached input is 95% cheaper than standard input and 50% cheaper than GPT-6 Sol’s cached input price, according to OpenAI. That pricing could be particularly important for AI agents that reuse information across multiple requests.
The model is available through the API as gpt-6.1-sol. OpenAI says GPT-6.1 Sol is also available in ChatGPT Work and Codex for Plus, Pro, Business, Enterprise and Edu users, although it is not yet available in regular Chat.
How close is it to GPT-6 Astra?
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OpenAI says GPT-6.1 Sol delivers substantial improvements over GPT-6 Sol across complex professional tasks. On the DeepSWE v1.1 software-engineering benchmark, OpenAI says Sol matches GPT-6 Astra while costing roughly one-fifth as much. For computer-use tasks, GPT-6.1 Sol comes within 2.1 percentage points of Astra’s score on the cited OSWorld 2.0 evaluation, at roughly one-seventh of the cost per task. There is still a clear reason to use Astra for the hardest workloads. OpenAI says GPT-6 Astra recorded the highest score among the models tested on Terminal-Bench Science 0.1, at 68.1%.
Why this matters for AI agents
The bigger story is not simply another model launch. It is the economics of AI agents. Agents can perform multi-step tasks involving code, documents, websites and business software. Running these workflows repeatedly can require large amounts of model inference. GPT-6.1 Sol is aimed at making those workloads cheaper without giving up too much capability. OpenAI also says the model improves factuality and alignment compared with GPT-6 Sol. On its difficult factuality evaluation, the share of responses containing a factual error fell from 11.4% with GPT-6 Sol to 7.7% with GPT-6.1 Sol at low reasoning effort. OpenAI cautions that these tests are deliberately difficult and are not representative of typical usage.
OpenAI says an Ultrafast version is also coming to Codex, with up to eight times faster token generation than standard speed. For developers, the message is straightforward: more capable AI does not necessarily have to mean dramatically higher inference costs.
