What are the hardware requirements for ArrowSmartPlus 3.6B Instant Sft JHSVer?

ArrowSmartPlus 3.6B Instant Sft JHSVer requires approximately 14.3 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed ArrowSmartPlus 3.6B Instant Sft JHSVer and how large is it?

ArrowSmartPlus 3.6B Instant Sft JHSVer is developed by DataPilot, a model with 3.6b 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 ArrowSmartPlus 3.6B Instant Sft JHSVer?

ArrowSmartPlus 3.6B Instant Sft JHSVer is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

ArrowSmartPlus 3.6B Instant Sft JHSVer by DataPilot — VRAM 14.3GB, 2K context

Name: ArrowSmartPlus 3.6B Instant Sft JHSVer
Author: DataPilot

ArrowSmartPlus 3.6B Instant Sft JHSVer is an open-source language model by DataPilot. Features: 3.6b LLM, VRAM: 14.3GB, Context: 2K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.12.

Gpt neox Instruct Ja Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/DataPilot/ArrowSmartPlus_3.6B_instant_sft_JHSVer

ArrowSmartPlus 3.6B Instant Sft JHSVer Benchmarks

LLME Score: 0.12176

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

ArrowSmartPlus 3.6B Instant Sft JHSVer (DataPilot/ArrowSmartPlus_3.6B_instant_sft_JHSVer)

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ArrowSmartPlus 3.6B Instant Sft JHSVer Parameters and Internals

Model Type

text generation

Supported Languages

Japanese (Native)

Training Details

Data Sources:

ウィキブック

Methodology:

Fine-tuning

Input Output

Output Format:

Text

LLM Name	ArrowSmartPlus 3.6B Instant Sft JHSVer
Repository 🤗	https://huggingface.co/DataPilot/ArrowSmartPlus_3.6B_instant_sft_JHSVer
Model Size	3.6b
Required VRAM	14.3 GB
Updated	2026-04-27
Maintainer	DataPilot
Model Type	gpt_neox
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-3 5.0 GB: 2-of-3 4.4 GB: 3-of-3
Supported Languages	ja
Model Architecture	GPTNeoXForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	4.38.2
Tokenizer Class	T5Tokenizer
Padding Token	</s>
Vocabulary Size	51200
Torch Data Type	float32

Best Alternatives to ArrowSmartPlus 3.6B Instant Sft JHSVer

Best Alternatives	Context / RAM	Downloads	Likes
...rrowSmartPlus 3.6B Instruction	2K / 14.3 GB	5	1
... GPT Neox 3.6B Instruction Sft	2K / 7.4 GB	9602	105
... Large Lm 3.6B Instruction Sft	2K / 7.2 GB	853	27
...T Neox 3.6B Instruction Sft V2	2K / 7.4 GB	1915	26
... GPT Neox 3.6B Instruction Ppo	2K / 7.4 GB	1047	75
...tion Sft 8bit 1g Actorder True	2K / 2.8 GB	8	2
...n Sft 4bit 128g Actorder False	2K / 2.1 GB	7	2

Note: green Score (e.g. "73.2") means that the model is better than DataPilot/ArrowSmartPlus_3.6B_instant_sft_JHSVer.

Rank the ArrowSmartPlus 3.6B Instant Sft JHSVer Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Release v20260328a

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ArrowSmartPlus 3.6B Instant Sft JHSVer by DataPilot

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ArrowSmartPlus 3.6B Instant Sft JHSVer Benchmarks

ArrowSmartPlus 3.6B Instant Sft JHSVer Parameters and Internals

Best Alternatives to ArrowSmartPlus 3.6B Instant Sft JHSVer

Rank the ArrowSmartPlus 3.6B Instant Sft JHSVer Capabilities

What open-source LLMs or SLMs are you in search of? 53972 in total.