🧠
Deepseek V4 Flash Mlx 2.8bit Exp model by inferencerlabs
⭐ 37.5
🧠
Model

Deepseek V4 Flash Mlx 2.8bit Exp

by inferencerlabs hf-model--inferencerlabs--deepseek-v4-flash-mlx-2.8bit-exp
Free2AITools Nexus Index
37.5 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 0
R: Recency 100
Q: Quality 50
Tech Context
2.8 Params
4.096K Ctx
Vital Performance
6.6K DL / 30D
0.0%
Source →
Audited 37.5 FNI Score
Tiny 2.8B Params
4k Context
6.6K Downloads
8G GPU ~4GB Est. VRAM
Dense DEEPSEEKV4FORCAUSALLM Architecture
Model Information Summary
Entity Passport
Registry ID hf-model--inferencerlabs--deepseek-v4-flash-mlx-2.8bit-exp
Provider huggingface
💾

Compute Threshold

~3.4GB VRAM

Interactive
Analyze Hardware
â–ŧ

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__inferencerlabs__deepseek_v4_flash_mlx_2.8bit_exp,
  author = {inferencerlabs},
  title = {Deepseek V4 Flash Mlx 2.8bit Exp Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/inferencerlabs/DeepSeek-V4-Flash-MLX-2.8bit-EXP}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
inferencerlabs. (2026). Deepseek V4 Flash Mlx 2.8bit Exp [Model]. Free2AITools. https://huggingface.co/inferencerlabs/DeepSeek-V4-Flash-MLX-2.8bit-EXP

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

đŸĻ™ Ollama Run
ollama run deepseek-v4-flash-mlx-2.8bit-exp
🤗 HF Download
huggingface-cli download inferencerlabs/deepseek-v4-flash-mlx-2.8bit-exp

⚖ī¸ Free2AITools Nexus Index V2.0

Methodology Index Protocol
Semantic (S) 50
Authority (A) 0
Popularity (P) 0
Recency (R) 100
Quality (Q) 50

đŸ’Ŧ Index Insight

FNI V2.0 for Deepseek V4 Flash Mlx 2.8bit Exp: Semantic (S:50), Authority (A:0), Popularity (P:0), Recency (R:100), 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

⚠ī¸ 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

  • â€ĸ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • â€ĸ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • â€ĸ 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
6.6KDownloads
Hub Discussions
🤗 Data Source: Hugging Face ↗
🔄 Daily sync (03:00 UTC)

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

📊 FNI Methodology 📚 Knowledge Baseℹī¸ Verify with original source

🛡ī¸ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id
hf-model--inferencerlabs--deepseek-v4-flash-mlx-2.8bit-exp
slug
inferencerlabs--deepseek-v4-flash-mlx-2.8bit-exp
source
huggingface
author
inferencerlabs
license
tags
mlx, deepseek_v4, quantized, text-generation, conversational, en, base_model:deepseek-ai/deepseek-v4-flash, region:us

⚙ī¸ Technical Specs

architecture
DeepseekV4ForCausalLM
params billions
2.8
context length
4,096
pipeline tag
text-generation
vram gb
3.4
vram is estimated
true
vram formula
VRAM ≈ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads
6,626
stars
0
forks
null

Data indexed from public sources. Updated daily.