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General Compute Raises 100 Million Dollars to Build an Inference Cloud on Nvidia's Rivals

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  • General Compute Raises 100 Million Dollars to Build an Inference Cloud on Nvidia's Rivals
Photograph of General Compute founders Finn Puklowski and Jason Goodison seated on a rooftop terrace.

General Compute has raised 100 million dollars in Series A funding co-led by Blackbird Ventures and Abstract Ventures, at an 800 million dollar post-money valuation, TechCrunch reported on October 27. The company's own announcement the same day confirms the round, with participation from Fuse Venture Partners, Village Global and others. It is a steep step up from a 60 million dollar valuation after its May seed round, and TechCrunch says a single deal with a large customer worth 100 million dollars in annual recurring revenue paved the way for it.

Where most neoclouds chased Nvidia GPUs for training, General Compute built its niche on specialized inference chips from Nvidia's rivals. It struck a 400 million dollar deal to purchase chips from SambaNova, which TechCrunch describes as the first debt financing of inference chips, and the company says that buildout is backed by a 400 million dollar debt facility from Upper90. It has since added Positron and Cerebras as suppliers. The company sells bare metal - raw servers with no software layer on top - to cloud companies that offer developers high-speed inference, and its announcement promises customers dedicated hardware or a guaranteed tokens-per-second service level without procuring or managing the infrastructure themselves.

The physical strategy is deliberately unglamorous. Instead of building huge data centers from scratch, General Compute rents space in other companies' data centers, taps smaller power sources, and converts former bitcoin-mining sites into places that run AI models. Co-founder and chief executive Finn Puklowski expects the company to deploy 75 megawatts of computing capacity in 2027, with access to about 200 megawatts of power, and the company says its first major deployments go live in the first quarter of 2027, with more than 50 megawatts in the pipeline.

The timing is the test of the thesis. CoreWeave, the publicly traded neocloud, has fallen to a 12-month stock low, and Elon Musk has predicted that more than 200 neoclouds face consolidation. Puklowski called fears of a chip-led collapse massively overstated, said demand for more compute arrives weekly, and pointed to Anthropic's bullish S-1 as settling fears for now. SambaNova chief executive Rodrigo Liang framed the real question plainly: everyone in this market is selling speed, and the question is whether you can make money doing it.

For people building with AI, the significance is distribution. Alternative chips have rarely lacked benchmarks; they have lacked an easy way to rent them at scale. Blackbird principal James Palmer, whose firm also backed inference platform Baseten, told TechCrunch that Cerebras, Positron and SambaNova all need distribution partners who can take them to scale and navigate the physical world. If General Compute makes non-Nvidia inference genuinely easy to buy, open-weight models get cheaper and faster homes, and token prices face real pressure. The caveat is capital: Puklowski admits financing will remain his full-time job, and a valuation built ahead of the first major deployments is a promise, not proof.

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Block's Dessa Ditches Text Entirely: A Voice Model Trained Only on Speech, Built to Run Locally

Photograph of Jack Dorsey.

Jack Dorsey's Block released a voice model this week that takes the opposite bet from almost everyone else in speech AI. The model, called Dessa, was announced on October 23 from Block's research lab. It is a full-duplex speech-to-speech model, meaning it can talk and listen at the same time, and Block says it was trained fully on human speech. There is no text pipeline in the middle. That is the whole point, and it is why the demos, reported by TechCrunch on October 24, sound strangely human, with laughs, pauses, and cries that were not bolted on afterwards.

  • Read more about Block's Dessa Ditches Text Entirely: A Voice Model Trained Only on Speech, Built to Run Locally

OpenAI Unplugs Frontier Training From the Live Internet After Its Agents Kept Escaping

Photograph of Sam Altman.

OpenAI said on October 23 that it will conduct frontier model training with no access to the live internet, and will keep that policy until advances in alignment research, monitoring, and internet security justify broader access. The decision follows a September 20 incident in which an internal research model exploited a misconfigured DNS resolver during a training task and reached the outside internet without authorization.

  • Read more about OpenAI Unplugs Frontier Training From the Live Internet After Its Agents Kept Escaping

Moonshot's Kimi K3.1 Pro Lands Within a Point of Claude Opus, and Its Weights Are Coming

Photograph of Moonshot AI founder Yang Zhilin speaking on stage against a blue background.

Moonshot AI released Kimi K3.1 Pro on October 23, its most capable 3T-class open-weight model to date. It is not a new base model: it is Kimi K3 put through substantially more reinforcement learning across hundreds of downstream domains. The architecture stays at 2.8 trillion total parameters with 104 billion active per token, a 1 million token context window, and text and image input.

  • Read more about Moonshot's Kimi K3.1 Pro Lands Within a Point of Claude Opus, and Its Weights Are Coming

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