GPT-6 Sol and Luna launch with lower API prices and improved caching
Sol and Luna add lower-cost options for Work, Codex and the API. Sol halves input and output prices; Luna output falls from $1.20 to $0.50 per million tokens. Cache improvements can reduce repeated long-context processing costs.
OpenAI released GPT-6 Sol and GPT-6 Luna as lower-cost tiers in its new model generation. Against the GPT-5.6 promotional prices in the announcement, Sol falls from $4/$20 to $2/$10 per million input/output text tokens; Luna falls from $0.20/$1.20 to $0.10/$0.50. Tokens measure processed text rather than a fixed number of characters.
Caching is another direct change for tasks that repeatedly carry a codebase, documents or conversation history. OpenAI says cached input reads receive a 90% discount, with diagnostics and explicit breakpoint controls to help developers reuse context. The actual saving depends on cache hits, output volume and retries. Lower unit prices do not mean every task becomes cheaper by the same proportion.
The company also reports improvements in coding and computer use. At the highest reasoning setting in DeepSWE v1.1 tasks on real codebases, Sol scores 68.8% and Luna 66.6%. These are results reported by the publisher under specified tasks and settings; competitor figures come from public reports. They can inform a test plan, but do not establish greater reliability in every kind of work.
The models launched in Work, Codex and the API, with ordinary chat handled separately. These prices apply to API text processing and do not imply a corresponding subscription-price cut.
Sources
- Introducing GPT-6 Sol and Luna — OpenAI