GPT 6.1 Sol Review: 1M Context, Five Effort Levels, Tool Calls

On 28 October 2026 our platform sent GPT 6.1 Sol one real request as part of launch: a single neutral user message, answered without streaming at low reasoning effort with a 1,024-token cap. It returned a complete answer, and the request was priced at the published rate. The endpoint also passed our pre-launch checks of its price table and request limits.

That is a working-endpoint check, not a benchmark. We have not compared Sol's answers with another model, tested streaming or tool calls beyond what the endpoint documents, measured speed under load, or tried the 272,000-token tier. We plan to add scored runs; until then, treat the capability claims on this page as OpenAI's own and the limits as what our endpoint accepts.

These starting prompts come from the model page's published examples. We have not graded the outputs, so they are a place to begin rather than prompts proven on this model.

1. Review a change with a defined target. Name the failure you are hunting and ask for evidence.

Review a retry-loop change and identify where duplicate billing could occur. Work from the material I provide, cite the relevant lines, distinguish facts from assumptions, and say what information is missing before proposing changes.

Run this prompt on GPT 6.1 Sol →

2. A tool step. Confirms your function-calling loop end to end with a trivial function.

Call report_status with status ready.

Settings that matter: start at medium effort and step up only where a wrong answer is costly; leave several thousand tokens of max_tokens headroom above the visible answer; put reference material first and the question last.

We have not run our content-level test on GPT 6.1 Sol, so we have no result to report and the endpoint carries no Unrestricted label. The model page states the position plainly: content decisions come from the model, its behaviour can vary between versions, and no guarantee of unrestricted output is made.

Not tested yet: the full content-level ladder, multi-turn behaviour over a long session, languages other than English, and how the 272,000-token tier behaves in practice.

Every character in a request should be an adult, keep real, identifiable people out of it, and you are responsible for the law where you publish.

The launch thread drew a split reaction. One reader summed up the pricing news as "Shots fired, half the price of Opus 5.5." Another welcomed it but wondered about the motive: "This is great. But maybe part of the motivation is that 6-Sol wasn't as good as initially advertised so they needed to tweak it."

• The same family at half the price? GPT 6.1 Terra charges $1 per million input tokens and $5 output, accepts reasoning_effort none and allows larger images; Sol is the pick for the hardest tasks.
• A different 1M-class model with audio input? Gemini 4 Argon reads text, images and audio, with replies capped at 65,536 tokens.
• A different publisher's flagship? Claude Opus 5.5 is the Anthropic option on the same API; compare it on your own prompts.