What are the hardware requirements for Japanese Mistral 300M Instruction?

Japanese Mistral 300M Instruction requires approximately 1.4 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 Japanese Mistral 300M Instruction and how large is it?

Japanese Mistral 300M Instruction is developed by ce-lery, a model with 300m 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 Japanese Mistral 300M Instruction?

Japanese Mistral 300M Instruction is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Japanese Mistral 300M Instruction by ce-lery — VRAM 1.4GB, 4K context

Name: Japanese Mistral 300M Instruction
Author: ce-lery

Japanese Mistral 300M Instruction is an open-source language model by ce-lery. Features: 300m LLM, VRAM: 1.4GB, Context: 4K, Instruction-Based, LLM Explorer Score: 0.1.

Base model:ce-lery/japanese-mi... Base model:finetune:ce-lery/ja... Endpoints compatible Generated from trainer Instruct Mistral Region:us Safetensors Tensorboard

Model Card on HF 🤗: https://huggingface.co/ce-lery/japanese-mistral-300m-instruction

Japanese Mistral 300M Instruction Parameters and Internals

Training Details

Data Sources:

wikipedia dataset, cc100 dataset, kunishou/databricks-dolly-15k-ja

Model Architecture:

Mistral 300M

LLM Name	Japanese Mistral 300M Instruction
Repository 🤗	https://huggingface.co/ce-lery/japanese-mistral-300m-instruction
Base Model(s)	Japanese Mistral 300M Base ce-lery/japanese-mistral-300m-base
Model Size	300m
Required VRAM	1.4 GB
Updated	2026-07-30
Maintainer	ce-lery
Model Type	mistral
Instruction-Based	Yes
Model Files	1.4 GB 0.0 GB
Model Architecture	MistralForCausalLM
Context Length	4096
Model Max Length	4096
Transformers Version	4.35.2
Tokenizer Class	T5Tokenizer
Padding Token	[PAD]
Vocabulary Size	50257
Torch Data Type	float32

Rank the Japanese Mistral 300M Instruction capabilities

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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 Japanese Mistral 300M Instruction

Best Alternatives	Context / RAM	Downloads	Likes
Lite Oute 1 300M Instruct	4K / 1.2 GB	46	9

Note: green Score (e.g. "73.2") means that the model is better than ce-lery/japanese-mistral-300m-instruction.