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A new Epoch AI report by Emberson and Roodman finds that the price of achieving a given level of AI performance has dropped roughly 47% per quarter over the past three years, a 13-fold annual decline. The report cites OpenAI's o3, which cost about $0.30 per question to score 75% on GPQA Diamond in January 2025, compared with a much newer model reaching similar scores for a fraction of a cent by mid-2026.
OpenAI will provide Ukraine's government with free access to its Daybreak AI cyber defence system, aimed at protecting civilian infrastructure such as hospitals and power plants from cyber-attacks. The deal also gives Ukraine access to OpenAI's GPT 5.6 Sol model, and comes after CERT-UA recorded nearly 6,000 cyber-attacks against the country in 2025.
An analysis argues that the cost of running machine learning models is dropping by orders of magnitude annually, driven by GPU efficiency gains that double roughly every two years—a pace not seen since early Moore's Law. The piece distinguishes proprietary models like GPT-6 Astra from open-weight models such as GLM-5.3-flash, noting that hosted and locally-run versions improve at different rates, with per-token pricing for frontier models not falling as consistently as costs for smaller models.
OpenAI launched GPT-6 Sol and GPT-6 Luna, positioned as cheaper, more accurate successors to GPT-5.6 Sol and Luna, with API costs cut by 50%. OpenAI says GPT-6 Sol outperforms Claude Opus 5 at roughly 9% of its cost and matches Claude Fable 5.1 on coding tasks at lower cost, while making about half as many errors as its predecessor. Both models are rolling out today in ChatGPT Work and Codex for Pro, Plus, Business, Enterprise, and Edu users, with Luna also available to Free and Go plan users in the desktop app.
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 added two new GPT-6 tiers, Sol and Luna, cutting API prices by 50% versus GPT-5.6 promotional rates, with Sol built for complex coding tasks and Luna aimed at high-volume document work. Anthropic released Claude Opus 5.5, a more token-efficient model it says costs about 40% less to run than Opus 5.
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.
Researcher Carter Leffer submitted a decryption of the German Army Enigma message MVUEH, sent 10 July 1941 and logged by an SS-Totenkopf radio unit, which had remained unbroken since 2005. The AI-assisted break, using OpenAI's GPT-6 Astra, revealed a completely different key setup—including a different wheel order—than other messages from that day, yet produced plaintext nearly identical to a previously solved message, Nr. 173 (SIPVX). Analysis of the newly recovered key also uncovered transcription errors in the original ciphertext and pinpointed the exact letter at which the Enigma machine's left wheel turned over.
A new Ornn Data paper argues that NVIDIA's older Ampere-generation GPUs, particularly the A100, remain economically useful far longer than assumed because open-weight models can be run cheaply on them. The analysis found that self-hosted open-weight models like gpt-oss-120b produce output more cheaply on A100 chips than on newer H100 hardware, and that A100 rental prices have stayed unusually stable over a five-year contract period compared to Hopper and Blackwell chips.