🧠

Model

Qwen3 Embedding 8b Mxfp8

Name: Qwen3 Embedding 8b Mxfp8
Author: Mlx Community

by Mlx Community hf-model--mlx-community--qwen3-embedding-8b-mxfp8

Free2AITools Nexus Index

39.3 Top 100%

S: Semantic 50

A: Authority 0

P: Popularity 26

R: Recency 86

Q: Quality 50

Tech Context

8 Params

32.768K Ctx

Vital Performance

1.3K DL / 30D

0.0%

Source →

Audited 39.3 FNI Score

8B Params

32k Context

1.3K Downloads

24G GPU ~9GB Est. VRAM

Dense QWEN3FORCAUSALLM Architecture

Commercial APACHE License

Model Information Summary
Entity Passport
Registry ID	hf-model--mlx-community--qwen3-embedding-8b-mxfp8
License	Apache-2.0
Provider	huggingface

💾

Compute Threshold

~8.5GB VRAM

Interactive

Analyze Hardware

Hardware Compatibility Test

▼

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX

@misc{hf_model__mlx_community__qwen3_embedding_8b_mxfp8,
  author = {Mlx Community},
  title = {Qwen3 Embedding 8b Mxfp8 Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/mlx-community/Qwen3-Embedding-8B-mxfp8}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}

APA Style

Mlx Community. (2026). Qwen3 Embedding 8b Mxfp8 [Model]. Free2AITools. https://huggingface.co/mlx-community/Qwen3-Embedding-8B-mxfp8

🔬Technical Deep Dive

Full Specifications [+]

Quick Commands

🦙 Ollama Run

ollama run qwen3-embedding-8b-mxfp8

🤗 HF Download

huggingface-cli download mlx-community/qwen3-embedding-8b-mxfp8

📦 Install Lib

pip install -U transformers

⚖️ Free2AITools Nexus Index V2.0

Methodology Index Protocol

Semantic (S) 50

Authority (A) 0

Popularity (P) 26

Recency (R) 86

Quality (Q) 50

💬 Index Insight

FNI V2.0 for Qwen3 Embedding 8b Mxfp8: Semantic (S:50), Authority (A:0), Popularity (P:26), Recency (R:86), Quality (Q:50).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit

Unbiased Data Node Refresh: VFS Live

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🚀 What's Next?

📊

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⚡

Deployment Guide

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Technical Deep Dive

mlx-community/Qwen3-Embedding-8B-mxfp8

The Model mlx-community/Qwen3-Embedding-8B-mxfp8 was converted to MLX format from Qwen/Qwen3-Embedding-8B using mlx-embeddings version 0.0.3.

Use with mlx

bash

pip install mlx-embeddings

python

from mlx_embeddings import load, generate
import mlx.core as mx

model, tokenizer = load("mlx-community/Qwen3-Embedding-8B-mxfp8")

# For text embeddings
output = generate(model, processor, texts=["I like grapes", "I like fruits"])
embeddings = output.text_embeds  # Normalized embeddings

# Compute dot product between normalized embeddings
similarity_matrix = mx.matmul(embeddings, embeddings.T)

print("Similarity matrix between texts:")
print(similarity_matrix)

⚠️ 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 →

📝 Limitations & Considerations

• Benchmark scores may vary based on evaluation methodology and hardware configuration.
• VRAM requirements are estimates; actual usage depends on quantization and batch size.
• FNI scores are relative rankings and may change as new models are added.
⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub

1.3KDownloads

Hub Discussions

🤗 Data Source: Hugging Face ↗

🔄 Daily sync (03:00 UTC)

AI Summary: Based on Hugging Face metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹ️ Verify with original source

🛡️ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id: hf-model--mlx-community--qwen3-embedding-8b-mxfp8
slug: mlx-community--qwen3-embedding-8b-mxfp8
source: huggingface
author: Mlx Community
license: Apache-2.0
tags: sentence-transformers, safetensors, qwen3, text-generation, transformers, sentence-similarity, feature-extraction, text-embeddings-inference, mlx, base_model:qwen/qwen3-8b-base, base_model:finetune:qwen/qwen3-8b-base, license:apache-2.0, endpoints_compatible, region:us

⚙️ Technical Specs

architecture: Qwen3ForCausalLM
params billions: 8
context length: 32,768
pipeline tag: feature-extraction
vram gb: 8.5
vram is estimated: true
vram formula: VRAM ≈ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads: 1,274
stars: 0
forks: 0

Data indexed from public sources. Updated daily.