The baton of open source AI models has been passed on between several companies over the years since ChatGPT debuted in late 2022, from Meta with its Llama family to Chinese labs like Qwen and z.ai. But lately, Chinese companies have started pivoting back towards proprietary models even as some U.S. labs like Cursor and Nvidia release their own variants of the Chinese models, leaving a question mark about who will originate this branch of technology going forward. One answer: Arcee, a San Francisco based lab, which this week released AI Trinity-Large-Thinking—a 399-billion parameter text-only reasoning model released under the uncompromisingly open Apache 2.0 license, allowing for full customizability and commercial usage by anyone from indie developers to large enterprises. The release [...]
For much of 2025, the frontier of open-weight language models has been defined not in Silicon Valley or New York City, but in Beijing and Hangzhou.Chinese research labs including Alibaba's Qwen, [...]
San Francisco-based AI lab Arcee made waves last year for being one of the only U.S. companies to train large language models (LLMs) from scratch and release them under open or partially open source l [...]
Even as concern and skepticism grows over U.S. AI startup OpenAI's buildout strategy and high spending commitments, Chinese open source AI providers are escalating their competition and one has e [...]
Enterprises looking to move more of their agentic AI workloads to open weights models they can customize, control and run on-premises or in virtual private clouds have a strong new contender to consid [...]
US start-up Arcee AI spent roughly half its total venture capital to train Trinity-Large-Thinking, an open reasoning model with 400 billion parameters designed to take on Claude Opus in agent tasks.&l [...]
Baidu Inc., China's largest search engine company, released a new artificial intelligence model on Monday that its developers claim outperforms competitors from Google and OpenAI on several visio [...]
Across 107 enterprises, AI infrastructure spending is accelerating well ahead of the ability to see or steer its economics. Most organizations run their AI on a familiar base of hyperscalers and model [...]
Watch out, DeepSeek and Qwen! There's a new king of open source large language models (LLMs), especially when it comes to something enterprises are increasingly valuing: agentic tool use — that [...]
Across 101 enterprises, the infrastructure that feeds AI agents their business context is being built faster than it can be trusted. Retrieval-augmented generation is already the default context sourc [...]