What are the hardware requirements for Qwen3 0.6B Base?

Qwen3 0.6B Base requires approximately 1.2 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 Qwen3 0.6B Base and how large is it?

Qwen3 0.6B Base is developed by unsloth, 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 Qwen3 0.6B Base?

Qwen3 0.6B Base is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3 0.6B Base by unsloth — VRAM 1.2GB, 32K context

Name: Qwen3 0.6B Base
Author: unsloth

Qwen3 0.6B Base is an open-source language model by unsloth. Features: 0.6b LLM, VRAM: 1.2GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.21.

Arxiv:2505.09388 Base model:finetune:qwen/qwen3... Base model:qwen/qwen3-0.6b-bas... Endpoints compatible Qwen3 Region:us Safetensors Unsloth

Model Card on HF 🤗: https://huggingface.co/unsloth/Qwen3-0.6B-Base

Qwen3 0.6B Base Benchmarks

LLME Score: 0.21139

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Qwen3 0.6B Base (unsloth/Qwen3-0.6B-Base)

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Qwen3 0.6B Base Parameters and Internals

LLM Name	Qwen3 0.6B Base
Repository 🤗	https://huggingface.co/unsloth/Qwen3-0.6B-Base
Base Model(s)	Qwen/Qwen3-0.6B-Base Qwen/Qwen3-0.6B-Base
Model Size	0.6b
Required VRAM	1.2 GB
Updated	2026-06-06
Maintainer	unsloth
Model Type	qwen3
Model Files	1.2 GB
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.53.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Best Alternatives to Qwen3 0.6B Base

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3 Reranker 0.6B	40K / 1.2 GB	2150586	368
Qwen3 0.6B FP8	40K / 1.1 GB	2079903	62
Privasis Cleaner 0.6B	40K / 1.2 GB	352	10
GLM 5.1 Qwen3 0.6B CoNDeNse	40K / 1.5 GB	445	2
Qwen3 0.6B	40K / 1.2 GB	197172	20
Qwen 0.6B ConvFill	40K / 1.2 GB	52	0
Palindrome Sft Qwen3	40K / 2.4 GB	141	0
Palindrome Sft V2 Qwen3	40K / 2.4 GB	81	0
Qwen3 0.6B Cybertown SFT	40K / 1.2 GB	16	0
Evolai Qwen047 V0	40K / 1.5 GB	35	0

Note: green Score (e.g. "73.2") means that the model is better than unsloth/Qwen3-0.6B-Base.

Rank the Qwen3 0.6B Base Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Qwen3 0.6B Base by unsloth

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Qwen3 0.6B Base Benchmarks

Qwen3 0.6B Base Parameters and Internals

Best Alternatives to Qwen3 0.6B Base

Rank the Qwen3 0.6B Base Capabilities

What open-source LLMs or SLMs are you in search of? 54898 in total.