What are the hardware requirements for Qwopus3.8 27B Flash INT4 W4A16?

Qwopus3.8 27B Flash INT4 W4A16 requires approximately 18.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwopus3.8 27B Flash INT4 W4A16 and how large is it?

Qwopus3.8 27B Flash INT4 W4A16 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 Qwopus3.8 27B Flash INT4 W4A16?

Qwopus3.8 27B Flash INT4 W4A16 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwopus3.8 27B Flash INT4 W4A16 by JC1DA — VRAM 18.4GB

Name: Qwopus3.8 27B Flash INT4 W4A16
Author: JC1DA

Qwopus3.8 27B Flash INT4 W4A16 is an open-source language model by JC1DA. Features: 27b LLM, VRAM: 18.4GB, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.26.

27b 4-bit Agent Agentic Auto-round Base model:jackrong/qwopus3.8-... Base model:quantized:jackrong/... Code-generation Conversational En Endpoints compatible Es Finetuned Function-calling Gptq Image-text-to-text Instruct Instruction-tuned Ja Local-inference Mtp Quantized Qwen Qwen3 Qwen3 5 Qwen3 8 Reasoning Region:us Ru Safetensors Sharded Speculative-decoding Tensorflow Tool-use W4a16 Zh

Model Card on HF 🤗: https://huggingface.co/JC1DA/Qwopus3.8-27B-Flash-INT4-W4A16

Qwopus3.8 27B Flash INT4 W4A16 Parameters and Internals

LLM Name	Qwopus3.8 27B Flash INT4 W4A16
Repository 🤗	https://huggingface.co/JC1DA/Qwopus3.8-27B-Flash-INT4-W4A16
Model Name	/workspace/renji-training/Jackrong/Qwen3.8-27B
Base Model(s)	Qwen/Qwen3.8-27B Jackrong/Qwopus3.8-27B-Flash Qwen/Qwen3.8-27B Jackrong/Qwopus3.8-27B-Flash
Model Size	27b
Required VRAM	18.4 GB
Updated	2026-09-06
Maintainer	JC1DA
Model Type	qwen3_5
Instruction-Based	Yes
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
Supported Languages	en zh es ru ja
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	5.9.0
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Qwopus3.8 27B Flash INT4 W4A16 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 Qwopus3.8 27B Flash INT4 W4A16

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.8 27B GPTQ INT4 FP8KV	0K / 20.2 GB	6488	2
DiscoveryRSI 27B	0K / 15.2 GB	250	11
...easoning Instruct MTP MLX 4bit	0K / 16.6 GB	366	2
Tmax 27B	0K / 53.8 GB	4630	26
...V2 Tulu Commitpackft Compelete	0K / 55.6 GB	124	1
...27B USS Collective Qx64 Hi Mlx	0K / 21 GB	417	2
Qwopus3.8 27B Flash AWQ MTP	0K / 19.1 GB	591	1
Qwopus3.8 27B Flash	0K / 55.6 GB	234	19
...en3.8 27B MindMeld Qx64 Hi Mlx	0K / 21 GB	346	1
Qwopus3.8 27B Flash V2	0K / 55.6 GB	126	17

Note: green Score (e.g. "73.2") means that the model is better than JC1DA/Qwopus3.8-27B-Flash-INT4-W4A16.