OpenAI’s GPT-6 Sol and Luna cut prices in half but barely move the needle on performance

With GPT-6 Sol and Luna, OpenAI adds two cheaper models to its lineup that match their predecessors’ performance at half the token price and aim to rival some of Anthropic’s more expensive models. The biggest change is a 50 percent price cut compared with GPT-5.6 Sol and Luna.

GPT-6 Sol now costs $2 per million input tokens and $10 per million output tokens, while Luna comes in at $0.10 for input and $0.50 for output. OpenAI attributes the lower prices to improvements in caching and inference, saying it’s passing those savings directly to users. That puts its pricing in the same range as cheaper open-weight models. Terra, previously the cheapest model in the lineup, is no longer available.Ad According to OpenAI, Sol is designed for recurring complex tasks such as building new features, reviewing code, debugging, and analyzing data. Luna is meant to handle large volumes of well-defined tasks at low cost, like summarizing documents, extracting information, and answering short questions.Ad Along with cutting token prices, OpenAI says it has improved prompt caching for GPT-6, offering a 90 percent discount on cached input tokens. A new prompt caching dashboard and diagnostics tool are meant to help developers optimize cache usage, and developers can now change reasoning effort and tool availability without invalidating the cache. GPT-6 Sol and Luna’s benchmark advantage comes down to cost OpenAI is positioning the new models primarily on price-to-performance compared with Anthropic’s Claude lineup. On OSWorld 2.0, which tests computer use, OpenAI says GPT-6 delivers results similar to Claude Opus 5 at roughly 80 percent lower cost, though Astra still leads in this category. On AutomationBench, which tests business workflows across 47 tools, GPT-6 Sol at its highest effort level reportedly beats Claude Opus 5 at maximum effort. OpenAI puts Sol’s cost per task at just 9 percent of Opus’s. Luna, meanwhile, improves on its predecessor by 5.4 percentage points while costing 58 percent less.Ad For coding, OpenAI provides results from two benchmarks. FrontierCode 1.1 tests whether AI agents produce code that can actually be integrated into an existing codebase, checking test quality, code style, and compliance with requirements. GPT-6 Sol scores 49.3 percent at maximum effort for $2.14 per task, putting it roughly on par with Claude Fable 5.1, which scores 50.3 percent at maximum effort but costs six times as much at $12.83. Claude Opus 5 reaches 53.4 percent for $4.31 at medium effort, the setting that produced its best result on this test.Ad On DeepSWE v1.1, a benchmark for demanding software engineering tasks over long stretches in real codebases, OpenAI reports 68.8 percent for GPT-6 Sol at maximum effort. That’s within 1.1 percentage points of Claude Fable 5’s best score of 69.9 percent at “xhigh,” while Fable at “max” hits 69.7 percent for $21.63 per task.