What are the hardware requirements for Qwen3.8 27B Cold Fusion GAIN V1.1 NM DAU NEO MAX MTP GGUF?

Qwen3.8 27B Cold Fusion GAIN V1.1 NM DAU NEO MAX MTP GGUF requires approximately 0.9 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Where can I download or evaluate Qwen3.8 27B Cold Fusion GAIN V1.1 NM DAU NEO MAX MTP GGUF?

Qwen3.8 27B Cold Fusion GAIN V1.1 NM DAU NEO MAX MTP GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.8 27B Cold Fusion GAIN V1.1 NM DAU NEO MAX MTP GGUF by DavidAU — VRAM 0.9GB

Name: Qwen3.8 27B Cold Fusion GAIN V1.1 NM DAU NEO MAX MTP GGUF
Author: DavidAU

Qwen3.8 27B Cold Fusion GAIN V1.1 NM DAU NEO MAX MTP GGUF is an open-source language model by DavidAU. Features: 27b LLM, VRAM: 0.9GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.51.

All genres All use cases Base model:davidau/qwen3.8-27b... Base model:quantized:davidau/q... Bfloat16 Coder Cold-fusion Conversational Creative Creative writing Dataset:davidau/polar-strict-d... Dataset:davidau/reasoning-stri... En Endpoints compatible Fiction Finetuned Gain training Gguf Image-text-to-text Imatrix Mtp gguf quants Multi-stage tuned Q6 Quantized Qwen3.8 Qwen3 5 Reasoning Region:us Regular gguf quants Roleplaying Story Thinking Unsloth Writing Zh

Model Card on HF 🤗: https://huggingface.co/DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1-NM-DAU-NEO-MAX-MTP-GGUF

Qwen3.8 27B Cold Fusion GAIN V1.1 NM DAU NEO MAX MTP GGUF Parameters and Internals

LLM Name	Qwen3.8 27B Cold Fusion GAIN V1.1 NM DAU NEO MAX MTP GGUF
Repository 🤗	https://huggingface.co/DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1-NM-DAU-NEO-MAX-MTP-GGUF
Base Model(s)	DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1 DavidAU/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1
Model Size	27b
Required VRAM	0.9 GB
Updated	2026-08-19
Maintainer	DavidAU
Model Type	qwen3_5
Model Files	11.7 GB 14.1 GB 17.3 GB 16.6 GB 15.3 GB 22.4 GB 12.1 GB 14.5 GB 17.8 GB 17.0 GB 18.5 GB 17.5 GB 21.2 GB 20.6 GB 24.0 GB 30.2 GB 18.0 GB 17.1 GB 20.7 GB 20.2 GB 23.6 GB 29.8 GB 0.9 GB 0.9 GB 1.8 GB
Supported Languages	en zh
GGUF Quantization	Yes
Quantization Type	gguf\|q6\|q4_k\|q5_k
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Transformers Version	5.8.0.dev0

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