
Arcee AI is a U.S. open-weight model lab building the Apache-2.0 Trinity foundation model family.
arcee.aiCrawled Oct 14, 2026
The guide covers installing and configuring tools for Hermes Agent powered by Trinity-Large-Thinking, as well as launching the assistant.
Arcee partners with Hugging Face to make the Hub the exclusive home for all models, datasets, and agent traces.
Latest articles, case studies and updates from Arcee AI.
A community credit grant for developers, researchers, and open source builders working with Trinity models.
Press coverage and announcements from Arcee AI.
Arcee is an open intelligence lab based in the U.S. Our models are open-weight, transparent, customizable, and built to run wherever you need them.
Arcee AI raises an undisclosed Series B that values the open-weight model developer at more than $1 billion. Vista Equity Partners, Cambium Capital and Emergence Capital lead the round, with participation from investors including Microsoft’s M12, Hitachi and Wipro; a source cited by Fortune says it totals at least $150 million. Arcee plans to train a new generation of Trinity models and expand its Genesis-Science-1 work with the U.S. Department of Energy and 17 national laboratories.
Sep 2026 · SiliconAngleNews article
Arcee AI raises a Series B at a $1 billion pre-money valuation after spending about $20 million to train four open-weight models. Vista Equity Partners, Cambium Capital, and Emergence Capital lead the round, which a source says totals at least $150 million; Arcee does not disclose the amount. The company plans to invest in new models and products and expand its partnership with the U.S. Department of Energy.
Sep 2026 · FortuneNews article
Arcee CTO Lucas Atkins argues that Chinese open-weight AI models are not inherently dangerous when enterprises run them in their own environments. He says model providers cannot access those deployments, and organizations can inspect available source code, conduct security testing, and tailor models before use. Arcee also benefits from Chinese models by studying and building on their work, Atkins says.
Jul 2026 · TechCrunchNews article
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