OpenAI’s New GPT-6.1 Terra and Anthropic’s Financial Reveal: Key Industry Updates

• OpenAI released GPT-6.1 Terra, a fast, lower-cost alternative to GPT-6 Astra, now available on all paid Work and Codex plans.
• Three new scientific findings from an OpenAI internal model cover harmonic analysis, complexity theory, and quantum field theory, pending independent verification.
• Microsoft is offering voluntary buyouts to approximately 60,000 employees, with decisions due by early December.
• Anthropic’s pre-IPO filing shows $16B in revenue for the first half of 2026, a 1,300% year-over-year increase.
• Claude now generates roughly 90% of the code for Claude Code, with daily merges jumping from 2,500 to over 30,000 between May and September.

OpenAI has unveiled three significant scientific discoveries derived from an internal model. These findings span multiple disciplines: harmonic analysis in mathematics, complexity theory in computer science, and quantum field theory in physics. While these results represent substantial progress, they are currently awaiting independent verification by the broader scientific community.

In addition to these theoretical advances, OpenAI introduced GPT-6.1 Terra. This new model serves as a faster and more economical alternative to its flagship GPT-6 Astra. It is specifically optimized for computer-use tasks, allowing users to interact with software interfaces more efficiently. The model is immediately accessible to all subscribers on paid Work and Codex plans.

Microsoft has announced voluntary buyout packages for roughly 60,000 employees, representing approximately a quarter of its total workforce. These packages are designed to support departing staff with tenure-based pay, continued stock vesting, and temporary healthcare coverage. Employees have until early December to accept these offers.

This restructuring follows Microsoft’s disclosure of $116 billion in spending for fiscal 2026. The majority of this capital was directed toward property and equipment, primarily for the construction and expansion of data centers. This strategic investment underscores the company’s commitment to infrastructure growth despite workforce adjustments.

Anthropic has filed its pre-IPO paperwork, marking the first time the lab’s financials have been publicly disclosed. The filing reveals that the company generated $16 billion in revenue during the first half of 2026, a 1,300% increase compared to the same period last year. To address concerns about cash burn, Anthropic reported holding $131 billion in cash reserves.

The company’s operating loss decreased significantly to $693 million, down from $2 billion a year earlier. While the net loss was reported at $81 billion, this figure was largely driven by a $72 billion accounting adjustment rather than core business operations. However, future obligations remain substantial, with approximately $800 billion in commitments for future compute agreements.

On an operational level, Anthropic engineer Addy Osmani and two colleagues detailed how the lab manages its development workflow. Claude now writes about 90% of the code for Claude Code. This automation has allowed daily merges to surge from 2,500 in May to over 30,000 in September. The primary shift involves AI handling the bulk of code reviews, which frees human engineers to focus on high-risk changes.

The filing also highlights that for every employee, Anthropic generates $6.6 million in trailing-twelve-month revenue. Analysts at SemiAnalysis describe this as one of the most efficient business scale-ups in history. The S-1 document includes nearly 100 pages of risk factors, ranging from competition to concerns about authoritarian abuse and AI safety.

Anthropic’s shares are expected to begin trading during the week of November 16. This event will allow public investors to assess the company’s valuation for the first time. The market’s reaction—whether buying, selling, or holding—will likely influence sentiment across the entire AI sector. Visualizations of these financials in six charts are available for further analysis.

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