GPT-6.1 Sol brings near-Astra capability at about a fifth of the price
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GPT-6.1 Sol: near-Astra intelligence for a fifth of the price. It’s the most cost-efficient model for its performance available today.
GPT-6.1 Sol makes frontier intelligence more affordable, so you can use it for more of the work that matters and developers can build and run applications at scale. Cached input costs just $0.10 per million tokens—95% less than standard input pricing and 50% less than GPT-6 Sol’s cached input pricing.
GPT-6.1 Sol is a significant upgrade over GPT-6 Sol across coding, computer use, and complex professional work—approaching GPT-6 Astra on several benchmarks at substantially lower cost.
GPT-6.1 Sol shows major improvements over GPT-6 Sol in our alignment evaluations, bringing it more in line with GPT-6 Astra. It’s more transparent about its limitations and more reliable at respecting user intent and safety constraints.
Context
OpenAI's GPT-6.1 Sol announcement includes a specific saving for applications that repeatedly send the same material: cached input costs $0.10 per million , 95% below standard input pricing. The company also claims performance approaching Astra on several benchmarks, which the launch thread presents as its own comparison.
Prompt caching allows eligible, unchanged portions at the beginning of a prompt to be reused. Repeated instructions or growing conversation histories can therefore benefit from the lower read price. The size of the saving depends on how much input actually qualifies for reuse.
- token — The chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.
- prompt caching — Reusing the model's processed form of a repeated prompt prefix so subsequent calls skip re-reading it, cutting cost and latency substantially.
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