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Qwen3 Embedding 0.6b Onnx Int4 model by electroglyph
⭐ 31.7
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Model

Qwen3 Embedding 0.6b Onnx Int4

by electroglyph electroglyph/qwen3-embedding-0.6b-onnx-int4
Free2AITools Nexus Index
31.7
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 33
P: Popularity 8
R: Recency 41
Q: Quality 65
Tech Context
0.6B Params
32.768K Ctx
Vital Performance
97 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 31.7 FNI Score
Tiny 0.6B Params
32k Context
97 Downloads
8G GPU ~3GB Est. VRAM
Dense QWEN3FORCAUSALLM Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID electroglyph/qwen3-embedding-0.6b-onnx-int4
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~3GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{electroglyph_qwen3_embedding_0_6b_onnx_int4,
  author = {electroglyph},
  title = {Qwen3 Embedding 0.6b Onnx Int4 Model},
  year = {2025},
  howpublished = {\url{https://huggingface.co/electroglyph/Qwen3-Embedding-0.6B-onnx-int4}},
  note = {Accessed via Free2AITools.}
}
APA Style
electroglyph. (2025). Qwen3 Embedding 0.6b Onnx Int4 [Model]. Free2AITools. https://huggingface.co/electroglyph/Qwen3-Embedding-0.6B-onnx-int4

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run qwen3-embedding-0.6b-onnx-int4
πŸ€— HF Download
huggingface-cli download electroglyph/qwen3-embedding-0.6b-onnx-int4
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) 33
Popularity (P) 8
Recency (R) 41
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Qwen3 Embedding 0.6b Onnx Int4: Authority (A:33), Popularity (P:8), Recency (R:41), 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
97Downloads
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--electroglyph--qwen3-embedding-0.6b-onnx-int4
slug
electroglyph--qwen3-embedding-0.6b-onnx-int4
source
huggingface
author
electroglyph
license
Apache-2.0
tags
sentence-transformers, onnx, qwen3, text-generation, transformers, sentence-similarity, feature-extraction, base_model:qwen/qwen3-0.6b-base, base_model:quantized:qwen/qwen3-0.6b-base, license:apache-2.0, text-embeddings-inference, endpoints_compatible, region:us

βš™οΈ Technical Specs

architecture
Qwen3ForCausalLM
params billions
0.6
context length
32,768
pipeline tag
feature-extraction
vram gb
3
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
97
stars
0
forks
0

Data indexed from public sources. Updated daily.