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Model

Qwen3.8 Whittle Moe 27b A17.8b Gguf All Quants

Name: Qwen3.8 Whittle Moe 27b A17.8b Gguf All Quants
Author: scima

by scima scima/qwen3.8-whittle-moe-27b-a17.8b-gguf-all-quants

Free2AITools Nexus Index

46.3

S: Semantic 50

Query-time baseline · scored live at search

A: Authority 29

P: Popularity 0

R: Recency 99

Q: Quality 65

Tech Context

27 Params

4.096K Ctx

Vital Performance —

Source →

Task categories from upstream metadata

💬Chat & Dialogue

Technical Constraints

Experimental / High Latency

Low FNI signal 46.3 FNI Score

27B Params

4k Context

0 Downloads

24G GPU ~22GB Est. VRAM

Commercial APACHE License

Model Information Summary
Entity Passport
Registry ID	scima/qwen3.8-whittle-moe-27b-a17.8b-gguf-all-quants
License	Apache-2.0
Provider	huggingface

💾

Compute Threshold

~21.6GB VRAM

Interactive

Estimate fit

VRAM Estimator (heuristic estimate)

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* Static estimation for 4-Bit Quantization.

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Cite this model

Academic & Research Attribution

BibTeX

@misc{scima_qwen3_8_whittle_moe_27b_a17_8b_gguf_all_quants,
  author = {scima},
  title = {Qwen3.8 Whittle Moe 27b A17.8b Gguf All Quants Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/scima/Qwen3.8-Whittle-MoE-27B-A17.8B-GGUF-all-quants}},
  note = {Accessed via Free2AITools.}
}

APA Style

scima. (2026). Qwen3.8 Whittle Moe 27b A17.8b Gguf All Quants [Model]. Free2AITools. https://huggingface.co/scima/Qwen3.8-Whittle-MoE-27B-A17.8B-GGUF-all-quants

🔬Technical Deep Dive

Full Specifications [+]

Quick Commands

🦙 Ollama Run

ollama run qwen3.8-whittle-moe-27b-a17.8b-gguf-all-quants

🤗 HF Download

huggingface-cli download scima/qwen3.8-whittle-moe-27b-a17.8b-gguf-all-quants

⚖️ Free2AITools Nexus Index V2.0

Methodology How FNI works

Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 29

Popularity (P) 0

Recency (R) 99

Quality (Q) 65

💬 Index Insight

FNI V2.0 for Qwen3.8 Whittle Moe 27b A17.8b Gguf All Quants: Authority (A:29), Popularity (P:0), Recency (R:99), 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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⚠️ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

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📝 Limitations & Considerations

• Benchmark scores may vary based on evaluation methodology and hardware configuration.
• VRAM requirements are estimates; actual usage depends on quantization and batch size.
• FNI scores are relative rankings and may change as new models are added.

🤗 Data Source: Hugging Face ↗

🔄 Updated daily

Source summary: Based on Hugging Face metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹ️ Verify with original source

🛡️ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id: hf-model--scima--qwen3.8-whittle-moe-27b-a17.8b-gguf-all-quants
slug: scima--qwen3.8-whittle-moe-27b-a17.8b-gguf-all-quants
source: huggingface
author: scima
license: Apache-2.0
tags: gguf, text-generation, base_model:logic65/qwen3.8-whittle-moe-27b-a17.8b, license:apache-2.0, endpoints_compatible, region:us, conversational

⚙️ Technical Specs

params billions: 27
context length: 4,096
pipeline tag: text-generation
vram gb: 21.6
vram is estimated: true
vram formula: VRAM ≈ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)

📊 Engagement & Metrics

downloads: 0

Data indexed from public sources. Updated daily.