🧠
Qwen3.6 27b Magicquant Mtp Gguf model by magiccodingman
⭐ 55
🧠
Model

Qwen3.6 27b Magicquant Mtp Gguf

by magiccodingman magiccodingman/qwen3.6-27b-magicquant-mtp-gguf
Free2AITools Nexus Index
55.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 39
P: Popularity 43
R: Recency 97
Q: Quality 65
Tech Context
27 Params
32.768K Ctx
Vital Performance
8.9K DL / 30D
Source β†’

Task categories from upstream metadata

πŸ’¬Chat & Dialogue
Low FNI signal 55 FNI Score
27B Params
32k Context
8.9K Downloads
24G GPU ~23GB Est. VRAM
Dense QWEN3_5FORCONDITIONALGENERATION Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID magiccodingman/qwen3.6-27b-magicquant-mtp-gguf
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~22.8GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{magiccodingman_qwen3_6_27b_magicquant_mtp_gguf,
  author = {magiccodingman},
  title = {Qwen3.6 27b Magicquant Mtp Gguf Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/magiccodingman/Qwen3.6-27B-MagicQuant-MTP-GGUF}},
  note = {Accessed via Free2AITools.}
}
APA Style
magiccodingman. (2026). Qwen3.6 27b Magicquant Mtp Gguf [Model]. Free2AITools. https://huggingface.co/magiccodingman/Qwen3.6-27B-MagicQuant-MTP-GGUF

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run qwen3.6-27b-magicquant-mtp-gguf
πŸ€— HF Download
huggingface-cli download magiccodingman/qwen3.6-27b-magicquant-mtp-gguf

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 39
Popularity (P) 43
Recency (R) 97
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Qwen3.6 27b Magicquant Mtp Gguf: Authority (A:39), Popularity (P:43), Recency (R:97), 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
---

πŸš€ What's Next?

πŸ“Š

Models in this category

Browse models in the same category

⚑

Deployment reference

Understand deployment options

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
8.9KDownloads
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--magiccodingman--qwen3.6-27b-magicquant-mtp-gguf
slug
magiccodingman--qwen3.6-27b-magicquant-mtp-gguf
source
huggingface
author
magiccodingman
license
Apache-2.0
tags
safetensors, gguf, qwen3_5, text-generation, magicquant, conversational, mtp, base_model:qwen/qwen3.6-27b, base_model:quantized:qwen/qwen3.6-27b, license:apache-2.0, endpoints_compatible, region:us, imatrix

βš™οΈ Technical Specs

architecture
Qwen3_5ForConditionalGeneration
params billions
27
context length
32,768
pipeline tag
text-generation
vram gb
22.8
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
8,886
stars
null
forks
null

Data indexed from public sources. Updated daily.