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

Qwen3.8 27B requires approximately 55.6 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

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

Qwen3.8 27B is developed by unsloth, a model with 27b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Qwen3.8 27B perform on standard benchmarks?

Qwen3.8 27B has the following published scores: LMSYS ELO 1438. Compare against reference models on this page or on the LLM Explorer leaderboards.

Qwen3.8 27B by unsloth — VRAM 55.6GB

Name: Qwen3.8 27B
Author: unsloth

Qwen3.8 27B is an open-source language model by unsloth. Features: 27b LLM, VRAM: 55.6GB, License: apache-2.0, LLM Explorer Score: 0.44, ELO: 1438.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3.8-27b Qwen3 5 Region:us Safetensors Sharded Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/unsloth/Qwen3.8-27B

Qwen3.8 27B Benchmarks

LMSys ELO 1438 vs 1272 (so35) 13.1%

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Qwen3.8 27B Parameters and Internals

LLM Name	Qwen3.8 27B
Repository 🤗	https://huggingface.co/unsloth/Qwen3.8-27B
Base Model(s)	Qwen/Qwen3.8-27B Qwen/Qwen3.8-27B
Model Size	27b
Required VRAM	55.6 GB
Updated	2026-08-15
Maintainer	unsloth
Model Type	qwen3_5
Model Files	4.0 GB: 1-of-18 3.0 GB: 2-of-18 2.5 GB: 3-of-18 4.0 GB: 4-of-18 2.1 GB: 5-of-18 4.0 GB: 6-of-18 2.1 GB: 7-of-18 4.0 GB: 8-of-18 2.1 GB: 9-of-18 4.0 GB: 10-of-18 2.1 GB: 11-of-18 4.0 GB: 12-of-18 2.1 GB: 13-of-18 4.0 GB: 14-of-18 2.1 GB: 15-of-18 4.0 GB: 16-of-18 2.1 GB: 17-of-18 3.4 GB: 18-of-18
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 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

Model	Likes	Downloads	VRAM
Qwopus3.8 27B Coder Flash 8bit	3	445	29 GB
Qwopus3.8 27B Coder Flash 4bit	2	374	16 GB
Qwopus3.8 27B Coder Flash 6bit	2	332	22 GB

Best Alternatives to Qwen3.8 27B

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	86	3
... 27B 6.3bpw RCO SAR Marlin MTP	256K / 22 GB	84	1
Qwen3.8 27B NPU2	256K / GB	252	4
...toTrust Decider Pro Vision 27B	0K / 55.6 GB	1537390	4526
JEV 27B VL	0K / 55.6 GB	1525286	966
Clef	0K / 54.7 GB	22043	2237
Arete 27B	0K / 54.7 GB	2407	346
Qwen3.6 27B	0K / 55.4 GB	6728138	2197
Qwen3.8 27B	0K / 55.6 GB	2	8753

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