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Qwen3.6 27b Mxfp4 Mtp model by OsaurusAI
⭐ 39.2
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Model

Qwen3.6 27b Mxfp4 Mtp

by OsaurusAI osaurusai/qwen3.6-27b-mxfp4-mtp
Free2AITools Nexus Index
39.2
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 2
R: Recency 81
Q: Quality 65
Tech Context
4.73 Params
32.768K Ctx
Vital Performance
15 DL / 30D
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 39.2 FNI Score
4.73B Params
32k Context
15 Downloads
8G GPU ~6GB Est. VRAM
Dense QWEN3_5FORCONDITIONALGENERATION Architecture
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID osaurusai/qwen3.6-27b-mxfp4-mtp
License Apache-2.0
Provider huggingface
πŸ’Ύ

Compute Threshold

~6GB VRAM

Interactive
Estimate fit
β–Ό

* Static estimation for 4-Bit Quantization.

πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{osaurusai_qwen3_6_27b_mxfp4_mtp,
  author = {OsaurusAI},
  title = {Qwen3.6 27b Mxfp4 Mtp Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/OsaurusAI/Qwen3.6-27B-MXFP4-MTP}},
  note = {Accessed via Free2AITools.}
}
APA Style
OsaurusAI. (2026). Qwen3.6 27b Mxfp4 Mtp [Model]. Free2AITools. https://huggingface.co/OsaurusAI/Qwen3.6-27B-MXFP4-MTP

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ¦™ Ollama Run
ollama run qwen3.6-27b-mxfp4-mtp
πŸ€— HF Download
huggingface-cli download osaurusai/qwen3.6-27b-mxfp4-mtp

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) 2
Recency (R) 81
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Qwen3.6 27b Mxfp4 Mtp: Authority (A:0), Popularity (P:2), Recency (R:81), 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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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
15Downloads
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--osaurusai--qwen3.6-27b-mxfp4-mtp
slug
osaurusai--qwen3.6-27b-mxfp4-mtp
source
huggingface
author
OsaurusAI
license
Apache-2.0
tags
mlx, safetensors, qwen3_5, qwen, dense, hybrid-attention, gated-deltanet, apple-silicon, quantized, mxfp4, vision, multimodal, video, multi-token-prediction, speculative-decoding, jang, osaurus, image-text-to-text, conversational, base_model:qwen/qwen3.6-27b, base_model:quantized:qwen/qwen3.6-27b, license:apache-2.0, region:us

βš™οΈ Technical Specs

architecture
Qwen3_5ForConditionalGeneration
params billions
4.73
context length
32,768
pipeline tag
image-text-to-text
vram gb
6
vram is estimated
true
vram formula
VRAM β‰ˆ (params * 0.75) + 2GB (KV) + 0.5GB (OS)

πŸ“Š Engagement & Metrics

downloads
15

Data indexed from public sources. Updated daily.