Arcee AI Trinity Mini and Nano – US based open weight models
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Re: Arcee AI Trinity Mini and Nano – US based open weight models
#2Half the dataset being synthetic is interesting. I wonder what that actually means. They say that Datology needed 2048 H100s to generate the synthetic data. Does that mean they were generating data using other open weight LLMs? Seems like that would undermine the integrity of a "US based" dataset.
Re: Arcee AI Trinity Mini and Nano – US based open weight models
#3If the performance is comparable to Qwen3 in practice that's quite impressive. Half the dataset being synthetic is interesting. I wonder what that actually means. They say that Datology needed 2048 H100s to generate the synthetic data. Does that mean they were generating data using other open weight LLMs? Seems like that would undermine the integrity of a "US based" dataset.
Re: Arcee AI Trinity Mini and Nano – US based open weight models
#4If the performance is comparable to Qwen3 in practice that's quite impressive. Half the dataset being synthetic is interesting. I wonder what that actually means. They say that Datology needed 2048 H100s to generate the synthetic data. Does that mean they were generating data using other open weight LLMs? Seems like that would undermine the integrity of a "US based" dataset.
Why would that undermine its integrity? AFAICT there are a selection of "open" US-based LLMs to choose from: Google's Gemma, Microsoft's Phi, Meta's LLAMA, and OpenAI's GPT-OSS. With Phi licensed under MIT and GPT-OSS under Apache 2.
Presumably they wouldn't be training on synthetic data produced by anything less than a open frontier model and those are almost exclusively Chinese