What are the hardware requirements for Xd V2?

Xd V2 requires a context window of 1K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Xd V2 and how large is it?

Xd V2 is developed by jnjj, a model with 13m 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 Xd V2?

Xd V2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Xd V2 by jnjj — 1K context

Name: Xd V2
Author: jnjj

Xd V2 is an open-source language model by jnjj. Features: 13m LLM, Context: 1K, Quantized, LLM Explorer Score: 0.19.

Conversational Deploy:azure Endpoints compatible Gguf Llama Pytorch Quantized Region:us Safetensors Sft Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/jnjj/xd_v2

Xd V2 Parameters and Internals

LLM Name	Xd V2
Repository 🤗	https://huggingface.co/jnjj/xd_v2
Model Size	13m
Required VRAM	0 GB
Updated	2026-08-07
Maintainer	jnjj
Model Type	llama
Model Files	0.1 GB 0.0 GB 0.0 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	LlamaForCausalLM
Context Length	1024
Model Max Length	1024
Transformers Version	4.51.3
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	float32

Rank the Xd 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

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