According to 1M AI News monitoring, the U.S. AI model company Arcee has released Trinity-Large-Thinking, an open-source reasoning model designed for long-duration Agent tasks. The model uses a Sparse Mixture of Experts (MoE) architecture, with a total of 400B parameters and only 13B activated parameters. It is released under the Apache 2.0 license for open-weight downloads on Hugging Face.
Unlike its predecessor Trinity-Large-Preview (pure instruction fine-tuning), Trinity-Large-Thinking performs reasoning thoughts before answering. It also shows improvements in multi-round tool calling, long-context coherence, and instruction-following ability. The core design goal is to maintain stable output during long-duration Agent loops.
On PinchBench, an Agent capability benchmark developed by Kilo, it scores 91.9, ranking second, only behind Opus 4.6’s 93.3. On the Agent task benchmark Tau2-Airline, it scores 88.0—the highest among all compared models. However, its performance on general reasoning benchmarks is average: it scores 76.3 on GPQA-D, below Kimi-K2.5 (86.9) and Opus 4.6 (89.2); it scores 83.4 on MMLU-Pro, also placing at the bottom. According to Arcee’s official description, this model is “the strongest open-source model outside China in many dimensions.”
Arcee API pricing is $0.90 per million tokens output. Arcee says it is about 96% cheaper than Opus 4.6. The model is also launched simultaneously on the AI model routing platform OpenRouter, where it has been available for free use in OpenClaw for the first 5 days. Since the end of January, the predecessor Preview has already served more than 3.37 trillion tokens on OpenRouter. It is the #1 open-source model by U.S. usage recorded on OpenClaw, and the #4 in the world. Preview will continue to be offered free on OpenRouter.
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