What are the hardware requirements for Hana 0.1 Fast?

Hana 0.1 Fast requires approximately 16.1 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Hana 0.1 Fast and how large is it?

Hana 0.1 Fast is developed by dwmk, a model with 0.5b 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 Hana 0.1 Fast?

Hana 0.1 Fast is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Hana 0.1 Fast by dwmk — VRAM 16.1GB, 32K context

Name: Hana 0.1 Fast
Author: dwmk

Hana 0.1 Fast is an open-source language model by dwmk. Features: 0.5b LLM, VRAM: 16.1GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.34.

Assistant Base model:adapter:qwen/qwen2.... Base model:qwen/qwen2.5-0.5b Conversational En Endpoints compatible Gguf Lora Peft Quantized Qwen2 Region:us Roleplay Safetensors Sharded Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/dwmk/Hana-0.1-Fast

Hana 0.1 Fast Parameters and Internals

LLM Name	Hana 0.1 Fast
Repository 🤗	https://huggingface.co/dwmk/Hana-0.1-Fast
Base Model(s)	Qwen/Qwen2.5-0.5B Qwen/Qwen2.5-0.5B
Model Size	0.5b
Required VRAM	16.1 GB
Updated	2026-10-15
Maintainer	dwmk
Model Type	qwen2
Model Files	3.2 GB 4.0 GB 0.3 GB 5.0 GB: 1-of-4 5.0 GB: 2-of-4 4.9 GB: 3-of-4 1.2 GB: 4-of-4
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|finetune_right_pad_id\|>
Vocabulary Size	151936
Torch Data Type	bfloat16

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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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