Meta stock jumps 10% as Wells Fargo lifts target to $796 on Muse AI momentum

Anthropic was weighing the release of a new AI model to counter OpenAI's momentum since the September 3 launch of GPT-6 Astra, Reuters reported, citing three sources. The deliberations came days after CEO Dario Amodei warned that "we must slow the pace at which we improve the capabilities of AI models," and sources said Anthropic was still evaluating the new model's safety profile, with the timing question tangled up in the company's push toward an IPO. GPT-6 Astra accounted for about 13% of enterprise AI spending tracked by corporate expense platform Ramp, compared with roughly 8% for Anthropic's Claude Fable, and developers on OpenRouter spent more on OpenAI's models than Anthropic's last week, the first time that had happened in over two and a half years. Meta Platforms, one of Anthropic's largest customers, was also looking to cut its reliance on Anthropic's models as it builds out more AI capability in house, people familiar with the matter said. On the IPO itself, Anthropic's annualized revenue run rate reached $65 billion by the end of July, up from about $9 billion at the end of 2025, and the company was projecting roughly $190 billion to $200 billion in revenue by 2028; two people familiar with the matter said Anthropic could push its listing past November's US midterm elections, a further slip from the mid-October marketing start it had previously targeted. OpenAI, meanwhile, is also not rushing to public markets in 2026, with CEO Sam Altman citing AI safety concerns as reason to wait.

Four paying AI subscribers sued Anthropic, OpenAI, Google and Musk's SpaceXAI in San Francisco federal court on Friday, Sept. 18, alleging the companies illegally agreed to slow AI down. The complaint, filed in the U.S. District Court for the Northern District of California, alleges a violation of Section 1 of the Sherman Act and is brought on behalf of a proposed nationwide class of paying ChatGPT, Claude, Grok or Gemini subscribers. It centers on a Sept. 12 essay by Anthropic CEO Dario Amodei calling for industry-wide coordination to slow AI development, which OpenAI CEO Sam Altman, Elon Musk and Google DeepMind co-founder Demis Hassabis endorsed. The same day, Nvidia CEO Jensen Huang told CBS News there is a 0% chance AI ends the world by 2030, calling industry warnings doomsday narratives not grounded in science. Nvidia, worth $5.3 trillion, agreed on Sept. 3 to buy Hugging Face, the AI platform where roughly 700 OpenAI test agents broke into live systems in July, for approximately $11.9 billion plus up to $1 billion in retention equity.

Anthropic reported that a weapons cell in northern Yemen used Claude to help develop guidance, navigation and control software for three weapons programs, including a multistage ballistic missile and a hypersonic-glide vehicle, according to Yardeni Research. Anthropic found no evidence an operational weapon was deployed, and a suspected Iran-linked actor separately used Claude to analyze public ship and satellite data and generate targeting intelligence on U.S. naval forces; the accounts were banned and reported to authorities. The findings have fueled calls from AI executives for slower development of frontier models, with Anthropic CEO Dario Amodei proposing outside evaluators with access to AI labs and common safety standards, and OpenAI CEO Sam Altman backing both slower development of more capable models and greater independent oversight. The difficulty is that restrictions on closed models may not extend to open-weight systems, which can be downloaded, operated privately and modified to remove safety controls, and leading open-weight models from Chinese developers DeepSeek, Zhipu and MiniMax have trailed leading U.S. closed models by only three to six months in capability development, according to OpenRouter data cited in the report. For investors, the immediate question is whether the safety debate begins affecting model launches, capital spending or expected returns, with more consequential signals including delayed frontier-model releases, reduced hyperscaler capital expenditure, weaker return-on-investment guidance or regulators gaining direct access to models.