What are the hardware requirements for Osmosis Structure 0.6B?

Osmosis Structure 0.6B requires approximately 0.4 GB of VRAM and supports a context window of 40K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Osmosis Structure 0.6B and how large is it?

Osmosis Structure 0.6B is developed by osmosis-ai, a model with 0.6b 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 Osmosis Structure 0.6B?

Osmosis Structure 0.6B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Osmosis Structure 0.6B by osmosis-ai — VRAM 0.4GB, 40K context

Name: Osmosis Structure 0.6B
Author: osmosis-ai

Osmosis Structure 0.6B is an open-source language model by osmosis-ai. Features: 0.6b LLM, VRAM: 0.4GB, Context: 40K, License: apache-2.0, Quantized, LLM Explorer Score: 0.23.

Endpoints compatible Gguf Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/osmosis-ai/Osmosis-Structure-0.6B

Osmosis Structure 0.6B Parameters and Internals

LLM Name	Osmosis Structure 0.6B
Repository 🤗	https://huggingface.co/osmosis-ai/Osmosis-Structure-0.6B
Model Size	0.6b
Required VRAM	0.4 GB
Updated	2026-07-23
Maintainer	osmosis-ai
Model Type	qwen3
Model Files	1.2 GB 0.4 GB 0.4 GB 0.5 GB 0.6 GB 2.4 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	40960
Model Max Length	40960
Transformers Version	4.52.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	float32
Errors	replace

Rank the Osmosis Structure 0.6B 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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Note: green Score (e.g. "73.2") means that the model is better than osmosis-ai/Osmosis-Structure-0.6B.