丹麦团队开源了10亿参数的Mimir v1，只用合规数据就追上4B模型，丹麦语还是第一。
DFM Mimir v1是丹麦基础模型团队发布的10亿参数语言模型，基于HRM架构从零训练。该模型仅使用许可的后训练数据，混合了161个数据集进行训练。在20个英语、数学与代码及丹麦语基准上，Mimir v1超过HRM-Text 1B，并可与Qwen 3.5 4B和Gemma 4 E2B竞争。它在丹麦语任务上刷新了最先进水平，模型现已在Hugging Face Hub开放下载。
DFM Mimir v1: An Open HRM Delivering Frontier Performance at 1B Parameters Using Only Permissible Post-Training Data
Current large language model development relies on massive, often non-permissible datasets, creating a high barrier for researchers committed to open-source and ethically sourced data. We introduce Mimir v1, a 1-billion-parameter language model based on the Hierarchical Reasoning Model (HRM) architecture, that is trained from scratch and delivers highly competitive performance for English and sets a new state of the art for Danish using only permissible post-training data. Trained on a mixture of 161 datasets, Mimir v1 outperforms the original HRM-Text 1B and competes with larger frontier models like Qwen 3.5 4B and Gemma 4 E2B, tested across 20 benchmarks for English, Math & Code and Danish. The model is available on the Hugging Face Hub: https://huggingface.co/danish-foundation-models/DFM-Mimir
- NVIDIA AI08-12 21:47原文