What are the hardware requirements for H2o Danube 1.8B Base?

H2o Danube 1.8B Base requires approximately 3.7 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed H2o Danube 1.8B Base and how large is it?

H2o Danube 1.8B Base is developed by h2oai, a model with 1.8b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does H2o Danube 1.8B Base perform on standard benchmarks?

H2o Danube 1.8B Base has the following published scores: MMLU 25.94. Compare against reference models on this page or on the LLM Explorer leaderboards.

H2o Danube 1.8B Base by h2oai — VRAM 3.7GB, 16K context

Name: H2o Danube 1.8B Base
Author: h2oai

H2o Danube 1.8B Base is an open-source language model by h2oai. Features: 1.8b LLM, VRAM: 3.7GB, Context: 16K, License: apache-2.0, LLM Explorer Score: 0.15, Arc: 39.4, HellaSwag: 69.6, MMLU: 25.9, GSM8K: 1.4.

Arxiv:2401.16818 En Endpoints compatible Gpt Mistral Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/h2oai/h2o-danube-1.8b-base

H2o Danube 1.8B Base Parameters and Internals

Model Type

GPT, Large Language Model, Text Generation

Use Cases

Areas:

Research, Commercial Applications

Limitations:

May produce biased, racist, offensive, or otherwise inappropriate content

Considerations:

Use responsibly and ethically.

Additional Notes

This is a pre-trained foundation model requiring fine-tuning for specific tasks.

Supported Languages

English (proficient)

Training Details

Methodology:

We adjust the Llama 2 architecture with sliding window attention from mistral.

Context Length:

16384

Model Architecture:

Llama 2 adapted architecture with sliding window attention.

LLM Name	H2o Danube 1.8B Base
Repository 🤗	https://huggingface.co/h2oai/h2o-danube-1.8b-base
Model Size	1.8b
Required VRAM	3.7 GB
Updated	2026-07-29
Maintainer	h2oai
Model Type	mistral
Model Files	3.7 GB
Supported Languages	en
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	16384
Model Max Length	16384
Transformers Version	4.36.1
Tokenizer Class	LlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the H2o Danube 1.8B Base capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to H2o Danube 1.8B Base

Best Alternatives	Context / RAM	Downloads	Likes
H2o Danube 1.8B Chat	16K / 3.7 GB	267	55
Cypher Mini 1.8B	16K / 3.7 GB	83	2
H2o Danube 1.8B Sft	16K / 3.7 GB	91	11
PixieZehirNano	16K / 3.7 GB	10	0
Cypher CoT 1.8B	16K / 3.7 GB	5	1
...1.8B Chat Sft Merge Fourier V1	16K / 7.3 GB	3	1
H2o Danube2 1.8B Base	8K / 3.7 GB	346	47
H2o Danube2 1.8B Chat	8K / 3.7 GB	222	62
H2o Danube2 1.8B Sft	8K / 3.7 GB	109	6
Binary Clumsy Bear	8K / 7.3 GB	5	0

Note: green Score (e.g. "73.2") means that the model is better than h2oai/h2o-danube-1.8b-base.