What are the hardware requirements for Qwopus3.8 27B Flash OQ8e?

Qwopus3.8 27B Flash OQ8e requires approximately 29.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwopus3.8 27B Flash OQ8e and how large is it?

Qwopus3.8 27B Flash OQ8e is developed by chriswessels, 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 OQ8e?

Qwopus3.8 27B Flash OQ8e 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 OQ8e by chriswessels — VRAM 29.5GB

Name: Qwopus3.8 27B Flash OQ8e
Author: chriswessels

Qwopus3.8 27B Flash OQ8e is an open-source language model by chriswessels. Features: 27b LLM, VRAM: 29.5GB, Instruction-Based, LLM Explorer Score: 0.26.

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

Model Card on HF 🤗: https://huggingface.co/chriswessels/Qwopus3.8-27B-Flash-oQ8e

Qwopus3.8 27B Flash OQ8e Parameters and Internals

LLM Name	Qwopus3.8 27B Flash OQ8e
Repository 🤗	https://huggingface.co/chriswessels/Qwopus3.8-27B-Flash-oQ8e
Model Name	/workspace/renji-training/Jackrong/Qwen3.8-27B
Base Model(s)	Jackrong/Qwopus3.8-27B-Flash Jackrong/Qwopus3.8-27B-Flash
Model Size	27b
Required VRAM	29.5 GB
Updated	2026-09-06
Maintainer	chriswessels
Model Type	qwen3_5
Instruction-Based	Yes
Model Files	5.5 GB: 1-of-6 5.1 GB: 2-of-6 5.0 GB: 3-of-6 5.1 GB: 4-of-6 5.0 GB: 5-of-6 3.8 GB: 6-of-6
Supported Languages	en zh es ru ja
Model Architecture	Qwen3_5ForConditionalGeneration
Model Max Length	262144
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Torch Data Type	bfloat16
Errors	replace

Rank the Qwopus3.8 27B Flash OQ8e 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 OQ8e

Best Alternatives	Context / RAM	Downloads	Likes
DiscoveryRSI 27B	0K / 15.2 GB	250	11
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
...sion GAIN V1.1 Fable Mxfp8 Mlx	0K / 28.7 GB	720	2
...en3.8 27B Parapraxis Mxfp8 Mlx	0K / 28.7 GB	206	1
...1 Darker Hero GAIN B Mxfp8 Mlx	0K / 28.7 GB	609	2

Note: green Score (e.g. "73.2") means that the model is better than chriswessels/Qwopus3.8-27B-Flash-oQ8e.