What are the hardware requirements for Qwen3.8 27B Opus Distill V2?

Qwen3.8 27B Opus Distill V2 requires approximately 53.8 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.8 27B Opus Distill V2 and how large is it?

Qwen3.8 27B Opus Distill V2 is developed by barozp, 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 Opus Distill V2?

Qwen3.8 27B Opus Distill V2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.8 27B Opus Distill V2 by barozp — VRAM 53.8GB

Name: Qwen3.8 27B Opus Distill V2
Author: barozp

Qwen3.8 27B Opus Distill V2 is an open-source language model by barozp. Features: 27b LLM, VRAM: 53.8GB, License: apache-2.0, LLM Explorer Score: 0.27.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3.8-27b Conversational Endpoints compatible Image-text-to-text Lora Mtp Opus-distill Qwen Qwen3 5 Reasoning Region:us Safetensors Sharded Tensorflow V2 Vision

Model Card on HF 🤗: https://huggingface.co/barozp/Qwen3.8-27B-Opus-Distill-v2

Qwen3.8 27B Opus Distill V2 Parameters and Internals

LLM Name	Qwen3.8 27B Opus Distill V2
Repository 🤗	https://huggingface.co/barozp/Qwen3.8-27B-Opus-Distill-v2
Base Model(s)	Qwen/Qwen3.8-27B Qwen/Qwen3.8-27B
Model Size	27b
Required VRAM	53.8 GB
Updated	2026-08-19
Maintainer	barozp
Model Type	qwen3_5
Model Files	49.8 GB: 1-of-2 4.0 GB: 2-of-2 1.8 GB
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	5.8.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Qwen3.8 27B Opus Distill V2 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

Quantized Models of the Qwen3.8 27B Opus Distill V2

Model	Likes	Downloads	VRAM
...27B Opus Distill V2 MTPLX 4bit	1	80	15 GB

Best Alternatives to Qwen3.8 27B Opus Distill V2

Best Alternatives	Context / RAM	Downloads	Likes
...wopus3.8 27B Flash Mlx OQ4e 1M	1024K / 16.9 GB	211	1
Agens Pilot	1024K / 54.7 GB	81	3
Qwen3.8 27B NPU2	256K / GB	252	4
JEV 27B VL	0K / 55.6 GB	1525286	966
Clef	0K / 54.7 GB	9513	1835
Qwen3.6 27B	0K / 55.4 GB	6728138	2197
Qwen3.8 27B	0K / 55.6 GB	2	8753
Qwen3.8 27B	0K / 55.6 GB	2727	21
Qwen3.8 27B MLX	0K / 16 GB	1411	18
Qwen3.8 27B FP8	0K / 0.4 GB	123157	416

Note: green Score (e.g. "73.2") means that the model is better than barozp/Qwen3.8-27B-Opus-Distill-v2.