What are the hardware requirements for JEV 27B?

JEV 27B requires approximately 53.9 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed JEV 27B and how large is it?

JEV 27B is developed by autotrust, 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 JEV 27B?

JEV 27B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

JEV 27B by autotrust — VRAM 53.9GB, 256K context

Name: JEV 27B
Author: autotrust

JEV 27B is an open-source language model by autotrust. Features: 27b LLM, VRAM: 53.9GB, Context: 256K, License: apache-2.0, LLM Explorer Score: 0.46.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3.8-27b Blocks-of-experts Calibrated-probabilities Choice Dataset:sargedev/jev-distill-c... Decision-model Dual-head En Endpoints compatible Jev Knowledge-distillation Lora Model-index Noul Qwen3 5 Qwen3 5 text Region:us Safetensors Score Sharded System-one System-two Tensorflow Typed-decisions Vllm

Model Card on HF 🤗: https://huggingface.co/autotrust/JEV-27B

JEV 27B Parameters and Internals

LLM Name	JEV 27B
Repository 🤗	https://huggingface.co/autotrust/JEV-27B
Base Model(s)	Qwen/Qwen3.8-27B Qwen/Qwen3.8-27B
Model Size	27b
Required VRAM	53.9 GB
Updated	2026-10-10
Maintainer	autotrust
Model Type	qwen3_5_text
Model Files	0.0 GB 4.2 GB: 1-of-13 4.2 GB: 2-of-13 4.2 GB: 3-of-13 4.2 GB: 4-of-13 4.2 GB: 5-of-13 4.2 GB: 6-of-13 4.2 GB: 7-of-13 4.2 GB: 8-of-13 4.2 GB: 9-of-13 4.2 GB: 10-of-13 4.2 GB: 11-of-13 4.2 GB: 12-of-13 3.5 GB: 13-of-13
Supported Languages	en
Model Architecture	Qwen3_5ForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	5.16.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	248320
Errors	replace

Rank the JEV 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

Best Alternatives to JEV 27B

Best Alternatives	Context / RAM	Downloads	Likes
Hemmingway 1	256K / 53.8 GB	11181	846
OrcaSAQ 2 27B	256K / 12.3 GB	1330	169
Qwen3.6 27B OBLITERATED	256K / 53.6 GB	15137	184
Darwin 27B RSI	256K / 53.8 GB	459	14
Mnma Qwen3.8 27b Nvfp4	256K / 18.8 GB	527	11
Qwen3.8 27B Code Tools Merged	256K / 53.8 GB	559	3
Sharona Q27B R CodeSecurity V2	256K / 53.8 GB	674	1
Qwen3.8 27B Obliterated E03	256K / 53.6 GB	708	1
...2 Abliterated OptiQ 3.7bpw Mlx	256K / 13.4 GB	6727	14
...wen3.8 P44w75 16.8B Unrepaired	256K / 2.4 GB	929	1

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