Anthropic released Opus 5.5, an update to its flagship coding and knowledge-work model, while OpenAI released GPT-6 Sol and Luna, updates to its mid-tier and smaller efficiency-focused models. Anthropic says Opus 5.5 cuts token pricing by 20%, cuts cache-read costs by 60%, and runs over 30% faster than its predecessor, while benchmarks from Anthropic show it modestly outperforming OpenAI's recently released GPT-6 Astra on coding tasks.
Anthropic released Opus 5.5, an update to Claude aimed at enterprise tasks like coding, financial analysis and business work, claiming better agentic coding benchmarks than GPT-6 Astra and reduced token pricing compared to Opus 5. OpenAI simultaneously released GPT-6 Sol and GPT-6 Luna, cheaper successors to GPT-5.6 that the company says cut factual errors roughly in half and match rival Fable 5.1's coding performance at lower cost.
OpenAI launched GPT-6 Sol and GPT-6 Luna, follow-ups to its 5.6 models and companions to the recently released GPT-6 Astra, aimed at giving businesses and developers Astra-level capability at lower cost with higher usage limits. Anthropic simultaneously released Claude Opus 5.5, which it says matches Fable 5.1's performance while cutting costs nearly 40% compared to Opus 5, and calls its most aligned model yet.
OpenAI has rolled out two new GPT-6 tier models, Sol and Luna, to Codex and ChatGPT Work following its earlier release of the flagship GPT-6 Astra model this month. Both models use fewer tokens than their GPT-5.6 equivalents, with Sol aimed at complex coding and agentic tasks and Luna suited to high-volume, focused work. The rollout covers Plus, Pro, Business, Enterprise and Edu accounts, with Free and Go users able to access Luna via the desktop app, though Enterprise admins must enable access.
OpenAI has updated its smaller GPT-6 models, Sol and Luna, following this month's launch of the flagship GPT-6 Astra. The company says API access to the new Sol and Luna models costs half as much as the previous 5.6 series, citing gains in caching and inference, and claims GPT-6 Sol makes roughly half as many factual mistakes as its predecessor while also reducing coding errors.
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