Specs built for long tool-using tasks
OpenAI’s API page lists a 1,050,000-token context window and a maximum output of 128,000 tokens. GPT‑6.1 Sol supports tool calling through Responses API, including computer use, web search, code interpreter, file search and MCP.
OpenAI positions Sol as a lower-cost option for complex coding, computer use and professional work with performance near GPT‑6 Astra. That is a company comparison, not a promise each prompt matches Astra. Sources: https://developers.openai.com/api/docs/models/gpt-6.1-sol and https://deploymentsafety.openai.com/gpt-6-1-sol/respecting-auto-review
The listed price is $2 in and $10 out
At standard rates for prompts up to 272,000 input tokens, OpenAI lists $2 per million uncached input tokens and $10 per million output tokens. Cached input is $0.10 per million; cache writes are $2.50. Fast mode costs twice standard rates.
Above 272,000 input tokens, OpenAI says input and cache prices double and output is 1.5 times standard pricing for the full request. That threshold matters when using the unusually large context window.
Compare it on complete workflows
Long context can reduce the need to split work across requests. Tool support lets an agent read files, run code, search the web or operate a computer.
Compare Sol with Astra on the tasks you actually run: result quality, tool calls, latency and total token cost. OpenAI’s docs recommend task-level comparison; a context figure alone cannot show whether a model finishes reliably.
Source published September 29, 2026. Coverage is based on the maker’s announcement and demonstration.