What are the hardware requirements for DeepSeek R1 Distill Qwen 32B Japanese 4bit?

DeepSeek R1 Distill Qwen 32B Japanese 4bit requires approximately 18.5 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 32B Japanese 4bit and how large is it?

DeepSeek R1 Distill Qwen 32B Japanese 4bit is developed by mlx-community, a model with 32b 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 32B Japanese 4bit?

DeepSeek R1 Distill Qwen 32B Japanese 4bit 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 32B Japanese 4bit by mlx-community — VRAM 18.5GB, 128K context

Name: DeepSeek R1 Distill Qwen 32B Japanese 4bit
Author: mlx-community

DeepSeek R1 Distill Qwen 32B Japanese 4bit is an open-source language model by mlx-community. Features: 32b LLM, VRAM: 18.5GB, Context: 128K, License: mit, Quantized, LLM Explorer Score: 0.16.

4-bit 4bit Base model:cyberagent/deepseek... Base model:quantized:cyberagen... Conversational Ja Japanese Mlx Quantized Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mlx-community/DeepSeek-R1-Distill-Qwen-32B-Japanese-4bit

DeepSeek R1 Distill Qwen 32B Japanese 4bit Parameters and Internals

LLM Name	DeepSeek R1 Distill Qwen 32B Japanese 4bit
Repository 🤗	https://huggingface.co/mlx-community/DeepSeek-R1-Distill-Qwen-32B-Japanese-4bit
Base Model(s)	...k R1 Distill Qwen 32B Japanese cyberagent/DeepSeek-R1-Distill-Qwen-32B-Japanese
Model Size	32b
Required VRAM	18.5 GB
Updated	2026-07-08
Maintainer	mlx-community
Model Type	qwen2
Model Files	5.4 GB: 1-of-4 5.3 GB: 2-of-4 5.4 GB: 3-of-4 2.4 GB: 4-of-4
Supported Languages	ja
Quantization Type	4bit
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 32B Japanese 4bit 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 DeepSeek R1 Distill Qwen 32B Japanese 4bit

Best Alternatives	Context / RAM	Downloads	Likes
...Logic Mix 3 32B Mlx OptiQ 5bit	128K / 22.3 GB	41	1
...pSeek R1 Distill Qwen 32B 4bit	128K / 18.5 GB	7795	51
Hydraulic Deepseek 16bit	128K / 65.8 GB	52	0
...k R1 Distill Qwen 32B Bnb 4bit	128K / 19.2 GB	2717	29
...till Qwen 32B Abliterated 4bit	128K / 18.5 GB	888	7
QwQ 32B Unsloth Bnb 4bit	128K / 22.5 GB	179	47
...ogito V1 Preview Qwen 32B 4bit	128K / 18.5 GB	43	5
...T1 Flash Lightest 32B Mlx 4Bit	128K / 18.5 GB	231	8
QwQ 32B 4bit	128K / 18.5 GB	132	38
QwQ 32B Bnb 4bit	128K / 19.2 GB	157	4

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/DeepSeek-R1-Distill-Qwen-32B-Japanese-4bit.