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

H2o Danube 1.8B Chat 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 Chat and how large is it?

H2o Danube 1.8B Chat 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 Chat perform on standard benchmarks?

H2o Danube 1.8B Chat has the following published scores: MMLU 33.41. Compare against reference models on this page or on the LLM Explorer leaderboards.

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

Name: H2o Danube 1.8B Chat
Rating: 1.5 (4 reviews)
Author: h2oai

H2o Danube 1.8B Chat is an open-source language model by h2oai. Features: 1.8b LLM, VRAM: 3.7GB, Context: 16K, License: apache-2.0, LLM Explorer Score: 0.16, Arc: 41.1, HellaSwag: 68.1, MMLU: 33.4, GSM8K: 17.4.

Arxiv:2401.16818 Conversational Dataset:argilla/distilabel-mat... Dataset:huggingfaceh4/ultracha... Dataset:huggingfaceh4/ultrafee... Dataset:intel/orca dpo pairs Dataset:meta-math/metamathqa Dataset:open-orca/openorca Dataset:openassistant/oasst2 En Endpoints compatible Gpt H2o-llmstudio Mistral Region:us Safetensors

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

H2o Danube 1.8B Chat Parameters and Internals

Model Type

text-generation, chat

Use Cases

Limitations:

The model may produce incorrect, nonsensical, or irrelevant responses.

Training Details

Data Sources:

HuggingFaceH4/ultrafeedback_binarized, Intel/orca_dpo_pairs, argilla/distilabel-math-preference-dpo, Open-Orca/OpenOrca, OpenAssistant/oasst2, HuggingFaceH4/ultrachat_200k, meta-math/MetaMathQA

Context Length:

16384

Model Architecture:

MistralForCausalLM with Llama 2 modifications

Responsible Ai Considerations

Fairness:

This model may contain biased, racist, offensive, or inappropriate content.

Input Output

Accepted Modalities:

text

Output Format:

text

Performance Tips:

Apply the HF Tokenizer chat template for better results.

LLM Name	H2o Danube 1.8B Chat
Repository 🤗	https://huggingface.co/h2oai/h2o-danube-1.8b-chat
Model Size	1.8b
Required VRAM	3.7 GB
Updated	2026-07-17
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	4.36.2
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the H2o Danube 1.8B Chat 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

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