What are the hardware requirements for Qwopus3.8 27B Flash AWQ MTP?

Qwopus3.8 27B Flash AWQ MTP requires approximately 19.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwopus3.8 27B Flash AWQ MTP and how large is it?

Qwopus3.8 27B Flash AWQ MTP is developed by shawnw3i, 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 AWQ MTP?

Qwopus3.8 27B Flash AWQ MTP 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 AWQ MTP by shawnw3i — VRAM 19.1GB

Name: Qwopus3.8 27B Flash AWQ MTP
Author: shawnw3i

Qwopus3.8 27B Flash AWQ MTP is an open-source language model by shawnw3i. Features: 27b LLM, VRAM: 19.1GB, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.28.

27b 4-bit Agent Agentic Awq Base model:jackrong/qwopus3.8-... Base model:quantized:jackrong/... Code-generation Conversational En Endpoints compatible Es Finetuned Function-calling Image-text-to-text Instruct Instruction-tuned Int4 Ja Local-inference Mtp Multimodal Quantized Qwen Qwen3 Qwen3 5 Qwen3 8 Reasoning Region:us Ru Safetensors Sharded Speculative-decoding Tensorflow Tool-use Vision Zh

Model Card on HF 🤗: https://huggingface.co/shawnw3i/Qwopus3.8-27B-Flash-AWQ-MTP

Qwopus3.8 27B Flash AWQ MTP Parameters and Internals

LLM Name	Qwopus3.8 27B Flash AWQ MTP
Repository 🤗	https://huggingface.co/shawnw3i/Qwopus3.8-27B-Flash-AWQ-MTP
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	19.1 GB
Updated	2026-09-12
Maintainer	shawnw3i
Model Type	qwen3_5
Instruction-Based	Yes
Model Files	3.2 GB: 1-of-7 3.2 GB: 2-of-7 3.2 GB: 3-of-7 3.2 GB: 4-of-7 1.3 GB: 5-of-7 2.5 GB: 6-of-7 2.5 GB: 7-of-7 0.8 GB
Supported Languages	en zh es ru ja
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	5.16.1
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Torch Data Type	float16
Errors	replace

Rank the Qwopus3.8 27B Flash AWQ MTP capabilities

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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 AWQ MTP

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.8 27B AWQ INT4	0K / 20.2 GB	110	0
DiscoveryRSI 27B	0K / 15.2 GB	250	11
...easoning Instruct MTP MLX 4bit	0K / 16.6 GB	366	2
Qwen3.8 27B GPTQ INT4 FP8KV	0K / 20.2 GB	6488	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	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 shawnw3i/Qwopus3.8-27B-Flash-AWQ-MTP.