NVIDIA splurges $26 billion to build AI models, directly challenging OpenAI.

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NVIDIA announced it will invest $26 billion over the next five years to develop open-source AI large models. The world’s largest AI chip manufacturer is officially transforming into a frontier model laboratory, directly challenging the market position of OpenAI, Anthropic, and DeepSeek.

According to financial documents for 2025 and executive interviews obtained by WIRED on the 11th, this massive investment has been confirmed by the company's management. Meanwhile, NVIDIA released its strongest open-source model to date, Nemotron 3 Super, on Wednesday, claiming it outperforms OpenAI’s open-source model GPT-OSS in several benchmarks.

The impact of this move on the market cannot be underestimated. NVIDIA's chips have always been the industry standard for training large AI models, and its open-source models are specifically optimized for its own hardware, helping to further consolidate its dominance in the AI computing power market.

From a macro perspective, this investment marks a profound shift in NVIDIA’s strategic focus—from simply supplying hardware and software stacks to evolving into a full-stack AI enterprise capable of directly competing with top AI laboratories.

Nemotron 3 Super: Performance Metrics Rival Top Models

NVIDIA's latest Nemotron 3 Super boasts 128 billion parameters, putting it on par with the largest version of OpenAI’s GPT-OSS. NVIDIA claims that, in the Artificial Intelligence Index comprehensive score, Nemotron 3 Super received 37 points, while GPT-OSS only scored 33—although the company also acknowledges that some Chinese models scored even higher.

Additionally, NVIDIA stated that Nemotron 3 Super participated in a new benchmark called PinchBench, which specifically evaluates a model’s control over OpenClaw, with Nemotron 3 Super ranking first in this test.

On the technical side, NVIDIA has disclosed various innovative methods used to train the model, covering architecture and training techniques that enhance reasoning ability, long-context processing, and reinforcement learning response ability. NVIDIA’s Vice President of Deep Learning Research, Bryan Catanzaro, stated: "NVIDIA is placing much more emphasis on open-source model development than ever before, and we're making significant progress."

Catanzaro also revealed that NVIDIA recently completed pre-training for a model with 550 billion parameters. Since launching the first Nemotron model in November 2023, NVIDIA has successively released specialized models for vertical fields such as robotics, climate modeling, and protein folding.

Strategic Logic: Dual Engines of Hardware and Models

NVIDIA's move is not merely about model competition, but also a deep strategic layout tied to its hardware roadmap. NVIDIA’s Vice President of Generative AI Software Enterprise Business, Kari Briski, stated that the company's future AI models will not just serve chip development, but will also optimize the overall architecture of supercomputing-level data centers. "We build these models to stretch our systems—not just to test computing power, but also storage and networking, thereby building the hardware architecture roadmap," she said.

The open-source strategy also has far-reaching business implications for NVIDIA. Upon release, NVIDIA’s models disclose weights and technical details, making it easier for startups and researchers to modify and innovate based on their technology. This helps form a developer network around NVIDIA’s hardware ecosystem, further strengthening the market stickiness of its chips.

Catanzaro stated: "Helping the ecosystem grow is in our interest." He joined NVIDIA in 2011 and led the historic transformation of the company from gaming graphics cards to AI chips.

Industry Professionals Highly Value Its Strategic Significance

The research community has responded positively to NVIDIA’s initiative. AI2 AI researcher and ATOM project leader Nathan Lambert says he is a "die-hard supporter of Nemotron," and calls on the US government to also provide funding support for open-source models.

Andy Konwinski, founder of the nonprofit Laude Institute focused on advancing AI openness and a computer scientist, characterized NVIDIA’s investment as a milestone signal. "They are at the intersection of many open and closed AI projects," Konwinski said. "This is an unprecedented statement of their belief in openness."

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