What are the hardware requirements for Llm Jp 3.1 1.8B V02b GGUF?

Llm Jp 3.1 1.8B V02b GGUF requires approximately 3.7 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llm Jp 3.1 1.8B V02b GGUF and how large is it?

Llm Jp 3.1 1.8B V02b GGUF is developed by ago99, a model with 1.8b 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 Llm Jp 3.1 1.8B V02b GGUF?

Llm Jp 3.1 1.8B V02b GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llm Jp 3.1 1.8B V02b GGUF by ago99 — VRAM 3.7GB, 4K context

Name: Llm Jp 3.1 1.8B V02b GGUF
Author: ago99

Llm Jp 3.1 1.8B V02b GGUF is an open-source language model by ago99. Features: 1.8b LLM, VRAM: 3.7GB, Context: 4K, License: apache-2.0, Quantized.

Base model:llm-jp/llm-jp-3.1-1... Base model:quantized:llm-jp/ll... En Endpoints compatible Gguf Ja Japanese Llama Llm-jp Q4 Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/ago99/llm-jp-3.1-1.8b-v02b-GGUF

Llm Jp 3.1 1.8B V02b GGUF Parameters and Internals

LLM Name	Llm Jp 3.1 1.8B V02b GGUF
Repository 🤗	https://huggingface.co/ago99/llm-jp-3.1-1.8b-v02b-GGUF
Base Model(s)	llm-jp/llm-jp-3.1-1.8b llm-jp/llm-jp-3.1-1.8b
Model Size	1.8b
Required VRAM	3.7 GB
Updated	2026-10-06
Maintainer	ago99
Model Type	llama
Model Files	3.0 GB: 1-of-2 0.7 GB: 2-of-2 1.2 GB
Supported Languages	ja en
GGUF Quantization	Yes
Quantization Type	gguf\|q4\|q4_k
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.57.6
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<PAD\|LLM-jp>
Vocabulary Size	99584

Rank the Llm Jp 3.1 1.8B V02b GGUF 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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Note: green Score (e.g. "73.2") means that the model is better than ago99/llm-jp-3.1-1.8b-v02b-GGUF.