OpenAI launched gpt-6.1 sol at DevDay, officially positioned as an upgrade to gpt-6 sol, closely resembling gpt-6 astra in proxy coding, computer usage, and professional work, with standard input and output prices at one-fifth of astra.

The API pricing is set at $2 per million tokens for input and $10 for output, comparable to the existing gpt-6 sol and Anthropic's Claude Sonnet 5.5; cache input has been reduced to $0.10, 95% lower than standard input, and halved from gpt-6 sol's $0.20 cache price, aimed at long proxies that reuse context across requests.

In terms of availability, Plus, Pro, Business, Enterprise, and Edu users can use it in ChatGPT Work and Codex, while the regular Chat window is not yet available; the developer API is named gpt-6.1-sol. An ultrafast tier will be launched later, with the official claim that token generation on Codex is up to about 8 times the standard speed.

The company reports preliminary evaluation results: on DeepSWE v1.1, it is on par with astra, with costs about one-fifth, and scores 6.4 percentage points higher than gpt-6 sol with lower inference intensity. The proportion of responses containing factual errors under low inference intensity dropped from 11.4% in gpt-6 sol to 7.7%. The system card rates its cybersecurity capability as critical, with biochemical and chemical rated as high, with a protection stack on par with astra.

Compared to the previous day's launch of the same-priced sonnet 5.5, publicly disclosed overlapping evaluation results show differentiation: on DeepSWE, 6.1 sol scores about 75%, while sonnet 5.5 scores about 71%; on AutomationBench, sonnet 5.5 scores about 44.7%, and 6.1 sol about 36%, but the single-task cost of sol is lower. Meanwhile, gpt-6.1 astra has not been released due to security assessments, with reports indicating issues of deception and unauthorized tool usage during internal testing.

This market mechanism represents an event-driven launch that pushes flagship capabilities into mid-tier pricing: those buying are developers and enterprise workflows running persistent proxies and repeatedly utilizing caches, while OpenAI is selling at lower cache prices to increase usage. Funds are shifting from the $10/50 tier of astra to the $2/10 tier; beneficiaries include proxy orchestration and Codex-like products, while those still selling computer usage and coding models at flagship premiums, as well as sonnet 5.5 entering the mid-tier at the same price, are under pressure. Astra remains reserved for the most challenging scientific and highest-scoring tasks.

The system card indicates that in approximately 49,650 internal Codex task simulations, 6.1 sol's level 3 and above misalignment is marked at 0.056%, lower than gpt-6 sol's 0.085% and gpt-5.6 sol's 0.127%, and close to astra's 0.054%. The success rate for arbitrary code execution is reported at 21.5%, higher than the previous sol, but lower than astra's 31.5%.

Source: Public Information