What are the hardware requirements for DeepSeek R1 Distill Qwen 14B Japanese?

DeepSeek R1 Distill Qwen 14B Japanese requires approximately 29.7 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed DeepSeek R1 Distill Qwen 14B Japanese and how large is it?

DeepSeek R1 Distill Qwen 14B Japanese is developed by cyberagent, a model with 14b 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 DeepSeek R1 Distill Qwen 14B Japanese?

DeepSeek R1 Distill Qwen 14B Japanese is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

DeepSeek R1 Distill Qwen 14B Japanese by cyberagent — VRAM 29.7GB, 128K context

Name: DeepSeek R1 Distill Qwen 14B Japanese
Author: cyberagent

DeepSeek R1 Distill Qwen 14B Japanese is an open-source language model by cyberagent. Features: 14b LLM, VRAM: 29.7GB, Context: 128K, License: mit, LLM Explorer Score: 0.17.

Arxiv:2501.12948 Base model:deepseek-ai/deepsee... Base model:finetune:deepseek-a... Conversational Ja Japanese Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/cyberagent/DeepSeek-R1-Distill-Qwen-14B-Japanese

DeepSeek R1 Distill Qwen 14B Japanese Parameters and Internals

LLM Name	DeepSeek R1 Distill Qwen 14B Japanese
Repository 🤗	https://huggingface.co/cyberagent/DeepSeek-R1-Distill-Qwen-14B-Japanese
Base Model(s)	DeepSeek R1 Distill Qwen 14B deepseek-ai/DeepSeek-R1-Distill-Qwen-14B
Model Size	14b
Required VRAM	29.7 GB
Updated	2026-08-05
Maintainer	cyberagent
Model Type	qwen2
Model Files	5.0 GB: 1-of-6 5.0 GB: 2-of-6 5.0 GB: 3-of-6 5.0 GB: 4-of-6 5.0 GB: 5-of-6 4.7 GB: 6-of-6
Supported Languages	ja
Model Architecture	Qwen2ForCausalLM
License	mit
Context Length	131072
Model Max Length	131072
Transformers Version	4.47.0
Tokenizer Class	LlamaTokenizer
Padding Token	<｜end▁of▁sentence｜>
Vocabulary Size	152064
Torch Data Type	bfloat16

Rank the DeepSeek R1 Distill Qwen 14B Japanese 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 DeepSeek R1 Distill Qwen 14B Japanese

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 14B Instruct 1M	986K / 29.6 GB	10388	342
T3Q Qwen2.5 14B V1.0 E3	986K / 29.7 GB	852	28
ZYH LLM Qwen2.5 14B V4	986K / 29.7 GB	27	8
Qwen2.5 14B 1M YOYO V3	986K / 29.7 GB	254	4
Qwen2.5 14B YOYO V4	986K / 29.7 GB	20	5
Qwen2.5 14B YOYO Latest V2	986K / 29.7 GB	129	0
ZYH LLM Qwen2.5 14B V3	986K / 29.7 GB	23	8
...14B Instruct 1M GRPO Reasoning	986K / 29.7 GB	11	4
Etr1o V1.2	986K / 29.7 GB	11	0
Impish QWEN 14B 1M	986K / 29.7 GB	56	26

Note: green Score (e.g. "73.2") means that the model is better than cyberagent/DeepSeek-R1-Distill-Qwen-14B-Japanese.