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Qwen3 Embedding 0.6b Gguf model by mradermacher
⭐ 41.2
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Model

Qwen3 Embedding 0.6b Gguf

by mradermacher mradermacher/qwen3-embedding-0.6b-gguf
Free2AITools Nexus Index
41.2
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 29
P: Popularity 31
R: Recency 77
Q: Quality 65
Tech Context
0.6B Params
4.096K Ctx
Vital Performance
1.8K DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 41.2 FNI Score
Tiny 0.6B Params
4k Context
1.8K Downloads
8G GPU ~2GB Est. VRAM
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID mradermacher/qwen3-embedding-0.6b-gguf
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~1.8GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{mradermacher_qwen3_embedding_0_6b_gguf,
  author = {mradermacher},
  title = {Qwen3 Embedding 0.6b Gguf Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/mradermacher/Qwen3-Embedding-0.6B-GGUF}},
  note = {Accessed via Free2AITools.}
}
APA Style
mradermacher. (2026). Qwen3 Embedding 0.6b Gguf [Model]. Free2AITools. https://huggingface.co/mradermacher/Qwen3-Embedding-0.6B-GGUF

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run qwen3-embedding-0.6b-gguf
πŸ€— HF Download
huggingface-cli download mradermacher/qwen3-embedding-0.6b-gguf
πŸ“¦ Install Lib
pip install -U transformers

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 29
Popularity (P) 31
Recency (R) 77
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Qwen3 Embedding 0.6b Gguf: Authority (A:29), Popularity (P:31), Recency (R:77), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data
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Technical Deep Dive

⚠️ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source β†’

πŸ“ Limitations & Considerations

  • β€’ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • β€’ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • β€’ FNI scores are relative rankings and may change as new models are added.

Social Proof

HuggingFace Hub
1.8KDownloads
Hub Discussions
πŸ€— Data Source: Hugging Face β†—
πŸ”„ Updated daily

Source summary: Based on Hugging Face metadata. Not a recommendation.

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
hf-model--mradermacher--qwen3-embedding-0.6b-gguf
slug
mradermacher--qwen3-embedding-0.6b-gguf
source
huggingface
author
mradermacher
license
Apache-2.0
tags
transformers, gguf, sentence-transformers, sentence-similarity, feature-extraction, text-embeddings-inference, en, base_model:qwen/qwen3-embedding-0.6b, base_model:quantized:qwen/qwen3-embedding-0.6b, license:apache-2.0, endpoints_compatible, region:us, conversational

βš™οΈ Technical Specs

params billions
0.6
context length
4,096
pipeline tag
feature-extraction
vram gb
1.8
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
1,836

Data indexed from public sources. Updated daily.