- OpenAI launched GPT-6 Sol and GPT-6 Luna at half the price with double accuracy
- GPT-6 Sol makes half as many errors as GPT-5.6 Sol, Luna costs a hundredth of it
- Models target low-cost professional work, automation, coding, and computer-use tasks
OpenAI unveiled its new AI models GPT-6 Sol and GPT-6 Luna, which are retailing for half the price but are twice as accurate, according to a blog post from the company on Wednesday.
The firm claimed in the blog post that GPT-6 Sol makes half as many mistakes as its predecessor GPT-5.6 Sol, with GPT Luna matching it at a hundredth of its cost. These new AI models were created to serve as low-cost options for professional work, computer-use tasks, automation and coding, as per the firm.
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This is in contrast to GPT-6 Astra, a large language model that the company released on Sept. 3. Astra is a faster model that was designed with the goal for it to handle more complicated and strenuous tasks.
This focus on cheaper and more efficient models comes as AI firms are prioritising cost reduction in their AI models.
GPT-6 Sol costs are at $2 per million input tokens and $10 per million output tokens, which is a 50% reduction from GPT-5.6 Sol's promotional price points.
Similarly, GPT-6 Luna will cost $0.10 per million input tokens and $0.50 per million output tokens.
The company uses similar methods to those that were implemented to train Astra to do the same for Sol and Luna, which includes enhancement of their alignment, reasoning, factual accuracy, coding and computer use.
"Improvements in caching and inference let us serve these models at lower cost, and we're passing those savings directly on to users and customers," the blog said.
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The company has been emphasising upon alignment after Anthropic's Chief Executive Officer (CEO) Dario Amodei penned a blog calling for pumping the brakes on AI advancement resulting from competition between various AI firms, advocating for more guardrails and caution in the matter.
OpenAI's Sam Altman echoed the call within hours, pledging to match Anthropic's move to give independent evaluators employee-like access to its systems.
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