Nvidia is building Nemotron 4, an open-weight AI model with at least one trillion parameters set for release as early as this fall, backed by a tripling of cloud spending to $28 billion through 2031.
However, the scale trails Chinese competitors: Moonshot AI's Kimi K3 already has 2.8 trillion parameters and scores around 60 on the Artificial Analysis Intelligence Index, while Nemotron 3 Ultra scores only 38 points, revealing a substantial performance gap.
What happened
Nvidia is developing Nemotron 4, an open-weight model with at least one trillion parameters—double the size of Nemotron 3 Ultra—and has tripled cloud spending on in-house model training to $28 billion through 2031. The earliest possible release would be this fall.
Why it matters
Even at one trillion parameters, Nemotron 4 would only match scales Chinese labs have already reached: Moonshot AI's Kimi K3 has 2.8 trillion parameters, and DeepSeek V4 Pro has 1.6 trillion. On the current Artificial Analysis Intelligence Index, Nemotron 3 Ultra scores 38 points while Kimi K3 scores around 60, showing a significant performance gap despite Nemotron 3 Ultra being the strongest open US model at launch in June.
What to watch
Nvidia is also backing a petition against regulating open models, even as the Trump administration considers targeted bans on Chinese models. Nemotron 4 would pit Nvidia in direct competition with its own major customers like OpenAI, while more companies self-hosting open models could increase GPU sales.
Ask the AI about this article →
Nvidia's investment in Nemotron 4 reflects a strategic pivot into competing with the world's best open-weight models, but the scale trajectory reveals a lag behind Chinese laboratories. At one trillion parameters, Nemotron 4 would reach a milestone that Moonshot AI (with Kimi K3 at 2.8 trillion) and DeepSeek (with V4 Pro at 1.6 trillion) have already surpassed. This gap translates to measurable performance: Nemotron 3 Ultra, which was the strongest open US model at launch in June, now scores 38 points on the Artificial Analysis Intelligence Index compared to Kimi K3's around 60—a substantial differential despite Nemotron 3 Ultra's initial market position.
Nvidia's $28 billion commitment through 2031 signals conviction in the open-model strategy, which aligns with the company's commercial interests: more companies self-hosting open models increases demand for GPUs. However, Nemotron 4 creates a direct competitive conflict with major customers like OpenAI, potentially straining those relationships. Simultaneously, Nvidia has joined a petition opposing regulation of open models, even as the Trump administration weighs targeted bans on Chinese models—a positioning that protects Nvidia's open-model business but also benefits Chinese competitors operating in the same regulatory space.
For example, today's edition would include:
AI-summarized, only the topics you pick — one digest a day via Email, Slack, or Discord.
Free · takes 30 seconds · unsubscribe anytimeWhat is AIToday? →
Ask AI anything about this article. Q&As are published on this page for other readers too.
Israeli startup DataAgent Ltd
Taoyuan is positioning itself as a northern hub for AI data centers (AIDC), citing the Tatan area and an LNG c…
SK Hynix presented a custom HBM concept at SEMICON Taiwan 2026, where compute functions are placed in the base…
The U.S. Department of Defense announced on August 31 that it has deployed ChatGPT Mil, a customized version o…
Nvidia reported earnings that were both remarkable and boring, reflecting its focus on avoiding a consolidated…
Anthropic has agreed to a $35bn cloud-computing contract with Lambda, a Nvidia-backed cloud provider
