What are the hardware requirements for Llm Jp 3 3.7B Instruct?

Llm Jp 3 3.7B Instruct requires approximately 7.6 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 3.7B Instruct and how large is it?

Llm Jp 3 3.7B Instruct is developed by mlx-community, a model with 3.7b 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 3.7B Instruct?

Llm Jp 3 3.7B Instruct is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llm Jp 3 3.7B Instruct by mlx-community — VRAM 7.6GB, 4K context

Name: Llm Jp 3 3.7B Instruct
Author: mlx-community

Llm Jp 3 3.7B Instruct is an open-source language model by mlx-community. Features: 3.7b LLM, VRAM: 7.6GB, Context: 4K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.14.

Conversational En Instruct Ja Llama Mlx Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mlx-community/llm-jp-3-3.7b-instruct

Llm Jp 3 3.7B Instruct Parameters and Internals

Model Type

text-generation

Additional Notes

The model was converted to MLX format.

Supported Languages

languages_supported (Japanese), level (unknown)

Input Output

Input Format:

text

Accepted Modalities:

text

Output Format:

text

LLM Name	Llm Jp 3 3.7B Instruct
Repository 🤗	https://huggingface.co/mlx-community/llm-jp-3-3.7b-instruct
Model Size	3.7b
Required VRAM	7.6 GB
Updated	2026-07-09
Maintainer	mlx-community
Model Type	llama
Instruction-Based	Yes
Model Files	5.4 GB: 1-of-2 2.2 GB: 2-of-2
Supported Languages	en ja
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.40.2
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<PAD\|LLM-jp>
Vocabulary Size	99584
Torch Data Type	bfloat16

Rank the Llm Jp 3 3.7B Instruct 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 Llm Jp 3 3.7B Instruct

Best Alternatives	Context / RAM	Downloads	Likes
SJT 3.7B	4K / 8.2 GB	9	0
....0 Computer Crime Act Instruct	4K / 13.7 GB	9	0
Llm Jp 3 3.7B Instruct	4K / 7.6 GB	1020	13
...3 3.7B Instruct EZO Humanities	4K / 7.6 GB	33	6

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/llm-jp-3-3.7b-instruct.