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    Home»Technology»Nvidia shows interest in start-up Reflection AI
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    Nvidia shows interest in start-up Reflection AI

    Editorial teamBy Editorial teamOctober 14, 2026
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    Nvidia is reportedly in talks to either acquire or increase its investment in the open-source start-up Reflection AI.

    This news arrives as the organisation seeks to strengthen its position in open-weight AI models and challenge the lower costs of Chinese rivals.

    Sources told the Financial Times (FT) discussions remain at an early stage and could lead to a full acquisition, further equity investment or a deal covering chips and computing capacity. An acqui-hire, under which Nvidia would recruit staff and license technology, is another option.

    A deal could apparently be reached in the coming weeks, though the terms under discussion remain unclear.

    According to the report, Nvidia has already invested $800 million in Reflection AI, which was valued at $25 billion in a March funding round. Founded in 2024 by former Google DeepMind researchers, the start-up develops AI models and tools for software development.

    Reflection recently launched its first open-weight model, Beam, targeting coding and agentic tasks as it looks to compete with Chinese models such as DeepSeek and Kimi.

    Open-weight models allow businesses and developers to customise AI systems and run them on their own infrastructure, potentially cutting costs compared with closed services such as OpenAI’s ChatGPT and Anthropic’s Claude.

    Although Nvidia has its own Nemotron family of open-weight models, FT said it lacks a frontier-scale model of its own. In an essay published in July, CEO Jensen Huang called for a domestic open-weight “ecosystem” across the US, arguing it was essential for “creating opportunities for innovation and prosperity across the country”. “In fact, openness may be one of the most important paths to AI safety and security,” he argued, adding “relying solely on closed models is not inherently safe” as “they can be breached, misused, or fail in ways that outsiders cannot detect”.

    Source: Mobile World Live

    Image Credit: Nvidia


    Source: Tahawul Tech

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