H2O-Danube-1.8B Technical Report
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Abstract (arXiv)
We present H2O-Danube, a series of small 1.8B language models consisting of H2O-Danube-1.8B, trained on 1T tokens, and the incremental improved H2O-Danube2-1.8B trained on an additional 2T tokens. Our models exhibit highly competitive metrics across a multitude of benchmarks and, as of the time of this writing, H2O-Danube2-1.8B achieves the top ranking on Open LLM Leaderboard for all models below the 2B parameter range. The models follow core principles of LLama 2 and Mistral, and we leverage and refine various techniques for pre-training large language models. We additionally release chat models trained with supervised fine-tuning followed by direct preference optimization. We make all models openly available under Apache 2.0 license further democratizing LLMs to a wider audience economically.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 34 of its 43 references that are in the map. First posted on arXiv 30 Jan 2024.
Builds on
34 of 43 references.
References · 34
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22 more
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Built on by
Citing papers per year: 2024: 4; 2025: 4; 2026: 1.
9 papers.
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- 2025SelecTKD: Selective Token-Weighted Knowledge Distillation for LLMscited by 22
- 2025Nemotron-Flash: Towards Latency-Optimal Hybrid Small Language Modelscited by 15
- 2025Advantage-Guided Distillation for Preference Alignment in Small Language Modelscited by 5
- 2024ChuXin: 1.6B Technical Reportcited by 0
- 2024OpenBA-V2: Reaching 77.3% High Compression Ratio with Fast Multi-Stage Pruningcited by 0
- 2024HARE: HumAn pRiors, a key to small language model Efficiencycited by 0
- 2026Chain-based Distillation for Effective Initialization of Variable-Sized Small Language Modelscited by 0
- 2026Chain-based Distillation for Effective Initialization of Variable-Sized Small Language Models8 May 2026
- 2025Nemotron-Flash: Towards Latency-Optimal Hybrid Small Language Models24 Nov 2025
- 2025SelecTKD: Selective Token-Weighted Knowledge Distillation for LLMs28 Oct 2025
- 2025DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs10 Mar 2025
- 2025Advantage-Guided Distillation for Preference Alignment in Small Language Models25 Feb 2025
- 2024Hymba: A Hybrid-head Architecture for Small Language Models20 Nov 2024
- 2024HARE: HumAn pRiors, a key to small language model Efficiency17 Jun 2024
- 2024OpenBA-V2: Reaching 77.3% High Compression Ratio with Fast Multi-Stage Pruning9 May 2024
- 2024ChuXin: 1.6B Technical Report8 May 2024
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