What are the hardware requirements for Qwen3.8 27B Cold Fusion GAIN V1.1 INT4 Autoround?

Qwen3.8 27B Cold Fusion GAIN V1.1 INT4 Autoround requires approximately 18.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.8 27B Cold Fusion GAIN V1.1 INT4 Autoround and how large is it?

Qwen3.8 27B Cold Fusion GAIN V1.1 INT4 Autoround is developed by JC1DA, a model with 27b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Qwen3.8 27B Cold Fusion GAIN V1.1 INT4 Autoround?

Qwen3.8 27B Cold Fusion GAIN V1.1 INT4 Autoround 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 INT4 Autoround by JC1DA — VRAM 18.4GB

Name: Qwen3.8 27B Cold Fusion GAIN V1.1 INT4 Autoround
Author: JC1DA

Qwen3.8 27B Cold Fusion GAIN V1.1 INT4 Autoround is an open-source language model by JC1DA. Features: 27b LLM, VRAM: 18.4GB, License: apache-2.0, LLM Explorer Score: 0.32.

4-bit Auto-round Base model:davidau/qwen3.8-27b... Base model:quantized:davidau/q... Conversational Endpoints compatible Gptq Image-text-to-text Inference Multimodal Quantized Qwen3 5 Region:us Safetensors Sharded Tensorflow W4a16

Model Card on HF 🤗: https://huggingface.co/JC1DA/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1-INT4-Autoround

Qwen3.8 27B Cold Fusion GAIN V1.1 INT4 Autoround Parameters and Internals

LLM Name	Qwen3.8 27B Cold Fusion GAIN V1.1 INT4 Autoround
Repository 🤗	https://huggingface.co/JC1DA/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1-INT4-Autoround
Model Name	/mnt/x/Qwen3.8-27B
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	18.4 GB
Updated	2026-08-26
Maintainer	JC1DA
Model Type	qwen3_5
Model Files	2.1 GB: 1-of-10 2.1 GB: 2-of-10 2.1 GB: 3-of-10 2.1 GB: 4-of-10 2.1 GB: 5-of-10 2.1 GB: 6-of-10 0.8 GB: 7-of-10 2.5 GB: 8-of-10 0.0 GB: 9-of-10 2.5 GB: 10-of-10 0.8 GB
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	5.9.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Qwen3.8 27B Cold Fusion GAIN V1.1 INT4 Autoround capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to Qwen3.8 27B Cold Fusion GAIN V1.1 INT4 Autoround

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.8 27B MLX	0K / 16 GB	1411	18
Qwen3.8 27B FP8	0K / 0.4 GB	123157	416
Qwen3.8 27B	0K / 55.6 GB	2727	21
Qwen3.6 27B	0K / 55.4 GB	6728138	2197
Qwen3.8 27B	0K / 55.6 GB	2	8753
Qwen3.6 27B NVFP4	0K / 22 GB	1887525	419
Qwen3.6 27B FP8	0K / 0.4 GB	7740472	342
ThinkingCap Qwen3.6 27B	0K / 54.7 GB	35947	614
Qwen3.5 27B	0K / 55.2 GB	2536294	1028
Qwen3.5 27B	0K / 55.2 GB	8115	16

Note: green Score (e.g. "73.2") means that the model is better than JC1DA/Qwen3.8-27B-Cold-Fusion-GAIN-V1.1-INT4-Autoround.