🧠
Qwen3 Coder Next 8bit model by NexVeridian
⭐ 48.9
🧠
Model

Qwen3 Coder Next 8bit

by NexVeridian hf-model--nexveridian--qwen3-coder-next-8bit
Nexus Index
48.9 Top 100%
S: Semantic 50
A: Authority 0
P: Popularity 75
R: Recency 90
Q: Quality 65
Tech Context
8 Params
4.096K Ctx
Vital Performance
353.3K DL / 30D
0.0%
Source →
Audited 48.9 FNI Score
8B Params
4k Context
Hot 353.3K Downloads
8G GPU ~8GB Est. VRAM
Model Information Summary
Entity Passport
Registry ID hf-model--nexveridian--qwen3-coder-next-8bit
Provider huggingface_deepspec
💾

Compute Threshold

~7.3GB VRAM

Interactive
Analyze Hardware
â–ŧ

* Static estimation for 4-Bit Quantization.

📜

Cite this model

Academic & Research Attribution

BibTeX 
@misc{hf_model__nexveridian__qwen3_coder_next_8bit,
  author = {NexVeridian},
  title = {Qwen3 Coder Next 8bit Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/nexveridian/qwen3-coder-next-8bit}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}
APA Style
NexVeridian. (2026). Qwen3 Coder Next 8bit [Model]. Free2AITools. https://huggingface.co/nexveridian/qwen3-coder-next-8bit

đŸ”ŦTechnical Deep Dive

Full Specifications [+]

Quick Commands

đŸĻ™ Ollama Run
ollama run qwen3-coder-next-8bit
🤗 HF Download
huggingface-cli download nexveridian/qwen3-coder-next-8bit

⚖ī¸ Nexus Index V2.0

Methodology Index Protocol
48.9
TOP 100% SYSTEM IMPACT
Semantic (S) 50
Authority (A) 0
Popularity (P) 75
Recency (R) 90
Quality (Q) 65

đŸ’Ŧ Index Insight

FNI V2.0 for Qwen3 Coder Next 8bit: Semantic (S:50), Authority (A:0), Popularity (P:75), Recency (R:90), Quality (Q:65).

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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📈

Compare Benchmarks

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⚡

Deployment Guide

Understand deployment options

Technical Deep Dive

NexVeridian/Qwen3-Coder-Next-8bit

This model NexVeridian/Qwen3-Coder-Next-8bit was converted to MLX format from Qwen/Qwen3-Coder-Next using mlx-lm version 0.30.8.

Use with mlx

bash 
pip install mlx-lm
python 
from mlx_lm import load, generate

model, tokenizer = load("NexVeridian/Qwen3-Coder-Next-8bit")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True, return_dict=False,
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)

⚠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
353.3KDownloads
Hub Discussions
đŸ“ĻData Source: huggingface_deepspec
🔄 Daily sync (03:00 UTC)

AI Summary: Based on huggingface_deepspec 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--nexveridian--qwen3-coder-next-8bit
slug
nexveridian--qwen3-coder-next-8bit
source
huggingface_deepspec
author
NexVeridian
license
tags
qwen, 26.9B, text-generation, mlx, safetensors, qwen3_next, conversational, base_model:qwen/qwen3-coder-next, base_model:quantized:qwen/qwen3-coder-next, license:apache-2.0, 8-bit, region:us

⚙ī¸ Technical Specs

architecture
null
params billions
8
context length
4,096
pipeline tag
text-generation
vram gb
7.3
vram is estimated
true
vram formula
VRAM ≈ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads
353,290
stars
0
forks
0

Data indexed from public sources. Updated daily.