What are the hardware requirements for Qwen3 Embedding 0.6B?

Qwen3 Embedding 0.6B 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 Embedding 0.6B and how large is it?

Qwen3 Embedding 0.6B is developed by Qwen, 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 Embedding 0.6B?

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

Qwen3 Embedding 0.6B by Qwen — VRAM 1.2GB, 32K context

Name: Qwen3 Embedding 0.6B
Author: Qwen

Qwen3 Embedding 0.6B is an open-source language model by Qwen. Features: 0.6b LLM, VRAM: 1.2GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.37.

Arxiv:2506.05176 Base model:finetune:qwen/qwen3... Base model:qwen/qwen3-0.6b-bas... Deploy:azure Deploy:sagemaker Endpoints compatible Feature-extraction Qwen3 Region:us Safetensors Sentence-similarity Sentence-transformers Text-embeddings-inference

Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen3-Embedding-0.6B

Qwen3 Embedding 0.6B Parameters and Internals

LLM Name	Qwen3 Embedding 0.6B
Repository 🤗	https://huggingface.co/Qwen/Qwen3-Embedding-0.6B
Base Model(s)	Qwen/Qwen3-0.6B-Base Qwen/Qwen3-0.6B-Base
Model Size	0.6b
Required VRAM	1.2 GB
Updated	2026-08-04
Maintainer	Qwen
Model Type	qwen3
Model Files	1.2 GB
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.51.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151669
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen3 Embedding 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

Quantized Models of the Qwen3 Embedding 0.6B

Model	Likes	Downloads	VRAM
Qwen3 Embedding 0.6B 4bit DWQ	9	13142	0 GB

Best Alternatives to Qwen3 Embedding 0.6B

Best Alternatives	Context / RAM	Downloads	Likes
S1 Mini	40K / 1.5 GB	1136	180
Qwen3 Reranker 0.6B	40K / 1.2 GB	2508313	377
RIFA Edge 0.6B	40K / 1.2 GB	581	0
Meridian Ac Nano	40K / 1.2 GB	493	1
Blake Haiku 1	40K / 1.2 GB	386	0
Tenorio 0.6B	40K / 1.2 GB	251	2
Qwen3 0.6B FP8	40K / 1.1 GB	1581403	62
Quipu 0.6B	40K / 1.2 GB	351	4
Privasis Cleaner 0.6B	40K / 1.2 GB	1171	18
Clary 0.6 0.6B	40K / 1.2 GB	163	1

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