What are the hardware requirements for RakutenAI 7B?

RakutenAI 7B requires approximately 14.8 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 RakutenAI 7B and how large is it?

RakutenAI 7B is developed by Rakuten, a model with 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 RakutenAI 7B?

RakutenAI 7B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

RakutenAI 7B by Rakuten — VRAM 14.8GB, 32K context

Name: RakutenAI 7B
Author: Rakuten

RakutenAI 7B is an open-source language model by Rakuten. Features: 7b LLM, VRAM: 14.8GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.15.

Arxiv:2403.15484 Base model:finetune:mistralai/... Base model:mistralai/mistral-7... En Endpoints compatible Ja Mistral Pytorch Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Rakuten/RakutenAI-7B

RakutenAI 7B Parameters and Internals

Model Type

text generation

Use Cases

Areas:

Research, Commercial applications

Applications:

Text generation in Japanese and English

Primary Use Cases:

Japanese language understanding

Limitations:

Possible to produce biased, inaccurate, or unsafe outputs

Considerations:

Please exercise caution and judgement while interacting with the model.

Additional Notes

The suite of RakutenAI-7B models is capable of generating human-like text on a wide range of topics.

Supported Languages

Japanese (Proficient), English (Competitive)

Training Details

Methodology:

Retrofitting of pre-trained model weights and vocabulary extension for Japanese

Model Architecture:

Mistral model architecture

Input Output

Accepted Modalities:

text

LLM Name	RakutenAI 7B
Repository 🤗	https://huggingface.co/Rakuten/RakutenAI-7B
Base Model(s)	mistralai/Mistral-7B-v0.1 mistralai/Mistral-7B-v0.1
Model Size	7b
Required VRAM	14.8 GB
Updated	2026-07-26
Maintainer	Rakuten
Model Type	mistral
Model Files	10.0 GB: 1-of-2 4.8 GB: 2-of-2 10.0 GB: 1-of-2 4.8 GB: 2-of-2
Supported Languages	en ja
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.34.0
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	48000
Torch Data Type	bfloat16

Rank the RakutenAI 7B 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 RakutenAI 7B

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	220	20
MegaBeam Mistral 7B 512K	512K / 14.4 GB	8470	54
SpydazWeb AI HumanAI RP	512K / 14.4 GB	16	1
SpydazWeb AI HumanAI 002	512K / 14.4 GB	18	1
...daz Web AI ChatML 512K Project	512K / 14.5 GB	12	0
MegaBeam Mistral 7B 300K	282K / 14.4 GB	3779	16
MegaBeam Mistral 7B 300K	282K / 14.4 GB	8018	17
Hebrew Mistral 7B 200K	256K / 30 GB	23	15
Astral 256K 7B	250K / 14.4 GB	9	0
Astral 256K 7B V2	250K / 14.4 GB	8	0

Note: green Score (e.g. "73.2") means that the model is better than Rakuten/RakutenAI-7B.