What are the hardware requirements for Kev 9B?

Kev 9B requires approximately 0.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Kev 9B and how large is it?

Kev 9B is developed by jaredpalmer, a model with 9b 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 Kev 9B?

Kev 9B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Kev 9B by jaredpalmer — VRAM 0.2GB

Name: Kev 9B
Author: jaredpalmer

Kev 9B is an open-source language model by jaredpalmer. Features: 9b LLM, VRAM: 0.2GB, License: apache-2.0, LLM Explorer Score: 0.41.

Adapter Base model:adapter:qwen/qwen3.... Base model:qwen/qwen3.5-9b-bas... Calibration Dataset:bigcode/commitpackft Dataset:cogcomp/trec Dataset:davidheineman/consumer... Dataset:fancyzhx/ag news Dataset:fancyzhx/dbpedia 14 Dataset:google/boolq Dataset:legacy-datasets/bankin... Dataset:nvidia/aegis-ai-conten... Dataset:nyu-mll/multi nli Dataset:setfit/amazon reviews ... Dataset:setfit/sst5 Dataset:stanfordnlp/imdb Dataset:yelp/yelp review full Decision-model En Finetuned Lora Model-index Multiple-choice Peft Qwen3.5 Region:us Safetensors Typesafe

Model Card on HF 🤗: https://huggingface.co/jaredpalmer/kev-9b

Kev 9B Parameters and Internals

LLM Name	Kev 9B
Repository 🤗	https://huggingface.co/jaredpalmer/kev-9b
Base Model(s)	Qwen/Qwen3.5-9B-Base Qwen/Qwen3.5-9B-Base
Model Size	9b
Required VRAM	0.2 GB
Updated	2026-10-03
Maintainer	jaredpalmer
Model Files	0.2 GB 0.0 GB
Supported Languages	en
Model Architecture	Adapter
License	apache-2.0
Model Max Length	262144
Is Biased	none
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	in_proj_b\|in_proj_qkv\|gate_proj\|v_proj\|o_proj\|k_proj\|up_proj\|in_proj_z\|in_proj_a\|out_proj\|down_proj\|q_proj
LoRA Alpha	32
LoRA Dropout	0.05
R Param	16
Errors	replace

Rank the Kev 9B 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

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