What are the hardware requirements for Xenith 3B?

Xenith 3B requires approximately 7.6 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Xenith 3B and how large is it?

Xenith 3B is developed by XeroCodes, a model with 3b 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 Xenith 3B?

Xenith 3B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Xenith 3B by XeroCodes — VRAM 7.6GB

Name: Xenith 3B
Author: XeroCodes

Xenith 3B is an open-source language model by XeroCodes. Features: 3b LLM, VRAM: 7.6GB, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.14.

Adapter Base model:adapter:microsoft/p... Base model:microsoft/phi-3-min... Conversational Dataset:alignmentlab-ai/alpaca... En Finetuned Instruct Lora Mistral Peft Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/XeroCodes/xenith-3b

Xenith 3B Parameters and Internals

Model Type

text generation, transformer-based LLM

Additional Notes

The model is fine-tuned to enhance performance on tasks requiring complex reasoning and multi-step problem-solving.

Supported Languages

en (high)

Training Details

Data Sources:

AlignmentLab-AI/alpaca-cot-collection

Training Time:

10 epochs

Hardware Used:

2x NVIDIA L4 GPUs

Model Architecture:

Transformer-based LLM

LLM Name	Xenith 3B
Repository 🤗	https://huggingface.co/XeroCodes/xenith-3b
Base Model(s)	Phi 3 Mini 4K Instruct microsoft/Phi-3-mini-4k-instruct
Model Size	3b
Required VRAM	7.6 GB
Updated	2026-06-24
Maintainer	XeroCodes
Instruction-Based	Yes
Model Files	0.1 GB 5.0 GB: 1-of-2 2.6 GB: 2-of-2
Supported Languages	en
Model Architecture	Adapter
License	apache-2.0
Model Max Length	4096
Is Biased	none
Tokenizer Class	LlamaTokenizer
Padding Token	<\|placeholder6\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	k_proj\|v_proj\|q_proj\|gate_proj\|o_proj\|up_proj\|down_proj
LoRA Alpha	16
LoRA Dropout	0
R Param	16

Rank the Xenith 3B 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 Xenith 3B

Best Alternatives	Context / RAM	Downloads	Likes
...Mental Support Qwen2.5 3B Lora	0K / 0.1 GB	21	0
Qwen25 3B Korean Pii Qlora2	0K / 0.1 GB	12	0
Llama3 Code Lora	0K / 0.1 GB	13	2
Nomi 1.1	0K / 6.5 GB	6	3
Cc Coder	0K / 0.1 GB	24	0
OpenRP3B Llama3.2	0K / 0.1 GB	6	1
Trained Quant 4bit	0K / 0 GB	7	0

Note: green Score (e.g. "73.2") means that the model is better than XeroCodes/xenith-3b.