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Qwen3.5 0.8b 6bit model by NexVeridian
⭐ 31.2
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Model

Qwen3.5 0.8b 6bit

by NexVeridian nexveridian/qwen3.5-0.8b-6bit
Free2AITools Nexus Index
31.2
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 9
R: Recency 71
Q: Quality 65
Tech Context
0.16B Params
32.768K Ctx
Vital Performance
119 DL / 30D
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue

Technical Constraints

Experimental / High Latency
Low FNI signal 31.2 FNI Score
Tiny 0.16B Params
32k Context
119 Downloads
8G GPU ~3GB Est. VRAM
Dense QWEN3_5FORCONDITIONALGENERATION Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID nexveridian/qwen3.5-0.8b-6bit
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~2.6GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{nexveridian_qwen3_5_0_8b_6bit,
  author = {NexVeridian},
  title = {Qwen3.5 0.8b 6bit Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/NexVeridian/Qwen3.5-0.8B-6bit}},
  note = {Accessed via Free2AITools.}
}
APA Style
NexVeridian. (2026). Qwen3.5 0.8b 6bit [Model]. Free2AITools. https://huggingface.co/NexVeridian/Qwen3.5-0.8B-6bit

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run qwen3.5-0.8b-6bit
πŸ€— HF Download
huggingface-cli download nexveridian/qwen3.5-0.8b-6bit

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) 9
Recency (R) 71
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Qwen3.5 0.8b 6bit: Authority (A:0), Popularity (P:9), Recency (R:71), 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.

Social Proof

HuggingFace Hub
119Downloads
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--nexveridian--qwen3.5-0.8b-6bit
slug
nexveridian--qwen3.5-0.8b-6bit
source
huggingface
author
NexVeridian
license
Apache-2.0
tags
mlx, safetensors, qwen3_5, text-generation, conversational, base_model:qwen/qwen3.5-0.8b, base_model:quantized:qwen/qwen3.5-0.8b, license:apache-2.0, 6-bit, region:us

βš™οΈ Technical Specs

architecture
Qwen3_5ForConditionalGeneration
params billions
0.16
context length
32,768
pipeline tag
text-generation
vram gb
2.6
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
119
stars
0
forks
0

Data indexed from public sources. Updated daily.