What are the hardware requirements for H2o Danube3 500M Base?

H2o Danube3 500M Base requires approximately 1 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed H2o Danube3 500M Base and how large is it?

H2o Danube3 500M Base is developed by h2oai, a model with 500m parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate H2o Danube3 500M Base?

H2o Danube3 500M Base is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

H2o Danube3 500M Base by h2oai — VRAM 1GB, 8K context

Name: H2o Danube3 500M Base
Author: h2oai

H2o Danube3 500M Base is an open-source language model by h2oai. Features: 500m LLM, VRAM: 1GB, Context: 8K, License: apache-2.0, LLM Explorer Score: 0.14.

Arxiv:2407.09276 En Endpoints compatible Gpt H2o-llmstudio Llama Onnx Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/h2oai/h2o-danube3-500m-base

H2o Danube3 500M Base Parameters and Internals

Model Type

text generation

Training Details

Context Length:

8192

Model Architecture:

Adjustments of the Llama 2 architecture, using the Mistral tokenizer with a vocabulary size of 32,000.

Input Output

Accepted Modalities:

text

Performance Tips:

Quantization and sharding options available for optimization.

LLM Name	H2o Danube3 500M Base
Repository 🤗	https://huggingface.co/h2oai/h2o-danube3-500m-base
Model Size	500m
Required VRAM	1 GB
Updated	2026-08-08
Maintainer	h2oai
Model Type	llama
Model Files	1.0 GB
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.42.3
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the H2o Danube3 500M 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 Danube3 500M Base

Best Alternatives	Context / RAM	Downloads	Likes
Carbon 500M	8K / 1 GB	921	24
H2o Danube3 500M Chat	8K / 1 GB	56465	42
Acheron D	8K / 1 GB	6	0
Acheron C	8K / 1 GB	5	0
Acheron	8K / 1 GB	6	0
Text Arco	8K / 1 GB	11	0
Arco Plus	8K / 1.6 GB	9	7
Danube Reasoner	8K / 1 GB	6	0
Clite 500M	8K / 1 GB	5	3
Massive	8K / 1 GB	20	0

Note: green Score (e.g. "73.2") means that the model is better than h2oai/h2o-danube3-500m-base.