What are the hardware requirements for XDAN L1 Chat RL V1.3.0bpw H6 EXL2?

XDAN L1 Chat RL V1.3.0bpw H6 EXL2 requires approximately 3 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed XDAN L1 Chat RL V1.3.0bpw H6 EXL2 and how large is it?

XDAN L1 Chat RL V1.3.0bpw H6 EXL2 is developed by LoneStriker. 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 XDAN L1 Chat RL V1.3.0bpw H6 EXL2?

XDAN L1 Chat RL V1.3.0bpw H6 EXL2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

XDAN L1 Chat RL V1.3.0bpw H6 EXL2 by LoneStriker — VRAM 3GB, 32K context

Name: XDAN L1 Chat RL V1.3.0bpw H6 EXL2
Author: LoneStriker

XDAN L1 Chat RL V1.3.0bpw H6 EXL2 is an open-source language model by LoneStriker. Features: LLM, VRAM: 3GB, Context: 32K, License: cc-by-4.0, Quantized, LLM Explorer Score: 0.1.

Dataset:intel/orca dpo pairs Dataset:open-orca/openorca Dpo En Endpoints compatible Exl2 Mistral Openorca Quantized Region:us Safetensors Self-think Xdan-ai

Model Card on HF 🤗: https://huggingface.co/LoneStriker/xDAN-L1-Chat-RL-v1-3.0bpw-h6-exl2

XDAN L1 Chat RL V1.3.0bpw H6 EXL2 Parameters and Internals

Model Type

Text generation, Humanalities, Coding, Writing

Supported Languages

en (High proficiency)

Training Details

Data Sources:

Open-Orca/OpenOrca, Intel/orca_dpo_pairs, Privately Crafted Dataset

Input Output

Input Format:

Prompt Template (Alpaca)

Accepted Modalities:

Text

Output Format:

Text response

Performance Tips:

Expert in worldly knowledge, skilled in employing a probing questioning strategy, and carefully considers each step before providing answers.

LLM Name	XDAN L1 Chat RL V1.3.0bpw H6 EXL2
Repository 🤗	https://huggingface.co/LoneStriker/xDAN-L1-Chat-RL-v1-3.0bpw-h6-exl2
Required VRAM	3 GB
Updated	2026-06-04
Maintainer	LoneStriker
Model Type	mistral
Model Files	3.0 GB
Supported Languages	en
Quantization Type	exl2
Model Architecture	MistralForCausalLM
License	cc-by-4.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	float32

Rank the XDAN L1 Chat RL V1.3.0bpw H6 EXL2 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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NemoMix Unleashed EXL2 4bpw	1000K / 7.3 GB	5	9
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...0.88 07.02 RP DPO Merged 16bit	32K / 14.4 GB	6	0
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Chargen V2 8bpw EXL2	32K / 7.4 GB	1	1
...tral PairRM DPO 8.0bpw H8 EXL2	32K / 7.4 GB	7	2
HamSter 0.2 8.0bpw H8 EXL2	32K / 7.4 GB	3	1

Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/xDAN-L1-Chat-RL-v1-3.0bpw-h6-exl2.