Cheaper near-frontier models make it tempting to send more context on every call. For anything personal, that is the wrong place to spend the savings.
OpenAI announced GPT-6.1 Sol at DevDay on 2 October. Its API page lists $2.00 per million input tokens, $0.10 for cached input and $10.00 for output, with a 1,050,000-token context window. Prompts over 272K input tokens are billed at double the input rate and 1.5x output for the whole request. OpenAI says the model gives near-Astra intelligence at a fifth of Astra's price. That comparison is OpenAI's own claim about its own product, and I haven't seen an independent benchmark of it, so treat it as marketing until someone you trust has run it on your workload.
The same event added computer use to the Agents API, so an agent can operate software through its interface, available through the API and in Codex and ChatGPT Work on Pro 500 and Enterprise plans.
Here is what I think a small team should take from it. When the per-token price drops, the first instinct is to spend the savings on more context: send the whole history, the whole document, the whole account. The model can take a million tokens, so why not use them.
