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OpenAI Raises 11 Billion Dollars at a 1.25 Trillion Dollar Valuation, and the Market Is Blinking

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  • OpenAI Raises 11 Billion Dollars at a 1.25 Trillion Dollar Valuation, and the Market Is Blinking
Photograph of OpenAI CEO Sam Altman seated on stage during a TED talk.

OpenAI has reportedly raised 11 billion dollars so far in a new funding round that values the company at 1.25 trillion dollars, Bloomberg reported on Friday, in a story carried by TechCrunch on November 6. The round has not closed yet. It is expected to close in the coming weeks and could total about 20 billion dollars, according to a source familiar with the matter. TechCrunch said it had reached out to OpenAI for comment. Even at a trillion-dollar-plus valuation, the striking part of the report is not the size of the number. It is the direction it moved.

In late September, Bloomberg reported that OpenAI was looking to raise 30 billion dollars in this round. The current figures fall well short of that target, and separate reporting on Friday said OpenAI had lowered its proposed valuation to 1.25 trillion dollars from 1.4 trillion dollars and cut its fundraising goals by about 10 billion dollars. Its chief rival is seeing the same repricing. Bloomberg also reported on Friday that potential buyers of shares in Anthropic's upcoming public offering are eyeing a substantially lower valuation than the company had targeted, with some buyers seeing it as low as 1.1 trillion dollars, compared with the 2 trillion dollars investors were said to expect roughly a month ago.

New spending data helps explain the blink. A report from Ramp, also covered by TechCrunch on November 6, found that business spending on AI tokens grew only 1.5 percent across August and September, after growing 42 percent in July, even as token volumes kept rising. Ramp's lead economist, Ara Kharazian, pointed to price competition rather than weak demand. OpenAI halved API prices for GPT-6 Sol and GPT-6 Luna in September, and Anthropic has cut prices for Fable 5.1 and Opus 5.5, a move the company said in a recent filing reduced revenue growth by about 600 million dollars. Median firms spend only 12 to 15 dollars per employee per month on AI, Ramp found, while the top 10 percent spend 600 to 1,000 dollars. Spending did re-accelerate in October, rising 8.9 percent from September 23 to October 23, but the hypergrowth assumption is clearly under pressure.

The politics have shifted at the same time. TechCrunch noted that the Democratic landslide in this week's United States midterm elections, and strongly negative voter sentiment around data centers, has caused jitters across the market, with further regulatory challenges expected. OpenAI had previously suggested it would go public this year, then delayed those plans, and an initial public offering is now expected at some point next year. None of this amounts to a collapse. A company raising 11 billion dollars at a 1.25 trillion dollar valuation is still operating at a scale no software business has reached before. What has changed is that investors are now asking what the revenue underneath that valuation actually does next.

For people building with AI, this is mostly good news, and it should be used. A buyer's market means the price war is real, routing work to cheaper models pays, and no business case should be built on today's list price or on the assumption that a single provider's growth curve justifies lock-in. The labs still need enormous amounts of capital for compute, and they will keep competing for developers while they raise it. The practical move is the unglamorous one: measure cost per completed task, keep a second provider integrated, and let the trillion-dollar argument happen between the labs and their investors.

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Mistral Opens the Weights on Le Chonk: A Trillion Parameters You Can Actually Own

Mistral released the downloadable weights for Mistral Large 4 on Thursday, October 29, turning an API-only preview launched October 6 into something enterprises and governments can own. The model, nicknamed Le Chonk, is a 1.05 trillion parameter mixture-of-experts system with about 52 billion active parameters, a 1 million token context window, and native multimodal input. The weights are on Hugging Face, can be served with vLLM or SGLang, and are also available through the Mistral API, OpenRouter, Microsoft Foundry with private Azure deployment, and Nvidia-hosted endpoints.

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Canada Buys a Stake in Cohere as Sovereign AI Gets a 7 Billion Dollar Round

Photograph of Cohere CEO Aidan Gomez speaking on stage.

Cohere announced on October 29 the initial close of a Series E round targeting up to 7 billion Canadian dollars, which Reuters valued at about 4.49 billion US dollars, at a 35.7 billion Canadian dollar valuation. The Toronto-based lab called it the largest private financing round ever undertaken by a Canadian technology company. Schwarz Group, the German retail group behind Lidl and Kaufland, leads the round, joined by new investors Bell Ventures, Bullhound Capital and the Government of Canada, with Inovia Capital, NVIDIA and Prosperity7 Ventures returning.

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DeepSeek and Moonshot Reportedly Trained Their Latest Models on OpenAI's GPT-6 Astra Outputs

Aerial photograph of the building housing DeepSeek's headquarters.

Chinese developers DeepSeek and Moonshot AI relied heavily on outputs from OpenAI's GPT-6 Astra to train their latest models, The Information reported on Wednesday, according to Reuters, citing people with direct knowledge of the matter. The models named are Moonshot's Kimi K3.1 Pro, released last week, and DeepSeek's upgraded V4.1-Flash 1017, launched on October 17. None of the three companies immediately responded to Reuters requests for comment, so for now this is a well-sourced report, not an admitted fact, and it should be read that way.

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