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Pplx Embed V1 4b Mlx model by agentmish
⭐ 39.9
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Model

Pplx Embed V1 4b Mlx

by agentmish agentmish/pplx-embed-v1-4b-mlx
Free2AITools Nexus Index
39.9
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 18
R: Recency 88
Q: Quality 65
Tech Context
4.02 Params
4.096K Ctx
Vital Performance
377 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 39.9 FNI Score
4.02B Params
4k Context
377 Downloads
8G GPU ~5GB Est. VRAM
Dense PPLXQWEN3MODEL Architecture
Commercial MIT License
Model Information Summary
Entity Passport
Registry ID agentmish/pplx-embed-v1-4b-mlx
License MIT
Provider huggingface
πŸ’Ύ

Compute Threshold

~4.3GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{agentmish_pplx_embed_v1_4b_mlx,
  author = {agentmish},
  title = {Pplx Embed V1 4b Mlx Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/agentmish/pplx-embed-v1-4b-mlx}},
  note = {Accessed via Free2AITools.}
}
APA Style
agentmish. (2026). Pplx Embed V1 4b Mlx [Model]. Free2AITools. https://huggingface.co/agentmish/pplx-embed-v1-4b-mlx

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run pplx-embed-v1-4b-mlx
πŸ€— HF Download
huggingface-cli download agentmish/pplx-embed-v1-4b-mlx
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) 0
Popularity (P) 18
Recency (R) 88
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Pplx Embed V1 4b Mlx: Authority (A:0), Popularity (P:18), Recency (R:88), 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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Deployment reference

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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.
  • ⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

HuggingFace Hub
377Downloads
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--agentmish--pplx-embed-v1-4b-mlx
slug
agentmish--pplx-embed-v1-4b-mlx
source
huggingface
author
agentmish
license
MIT
tags
sentence-transformers, safetensors, qwen3, feature-extraction, sentence-similarity, mteb, custom_code, multilingual, arxiv:2602.11151, license:mit, text-embeddings-inference, endpoints_compatible, region:us, mlx, bidirectional_pplx_qwen3, apple-silicon, perplexity, base_model:perplexity-ai/pplx-embed-v1-4b

βš™οΈ Technical Specs

architecture
PPLXQwen3Model
params billions
4.02
context length
4,096
pipeline tag
feature-extraction
vram gb
4.3
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
377
stars
0
forks
0

Data indexed from public sources. Updated daily.