What are the hardware requirements for DeepSeek V3.2 Speciale 4bit?

DeepSeek V3.2 Speciale 4bit requires approximately 194.4 GB of VRAM and supports a context window of 160K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed DeepSeek V3.2 Speciale 4bit and how large is it?

DeepSeek V3.2 Speciale 4bit is developed by mlx-community, a model with 671.9b 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 V3.2 Speciale 4bit?

DeepSeek V3.2 Speciale 4bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

DeepSeek V3.2 Speciale 4bit by mlx-community — VRAM 194.4GB, 160K context

Name: DeepSeek V3.2 Speciale 4bit
Author: mlx-community

DeepSeek V3.2 Speciale 4bit is an open-source language model by mlx-community. Features: 671.9b LLM, VRAM: 194.4GB, Context: 160K, License: mit, Quantized, LLM Explorer Score: 0.22.

4-bit 4bit Base model:deepseek-ai/deepsee... Base model:finetune:deepseek-a... Deepseek v32 Mlx Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mlx-community/DeepSeek-V3.2-Speciale-4bit

DeepSeek V3.2 Speciale 4bit Parameters and Internals

LLM Name	DeepSeek V3.2 Speciale 4bit
Repository 🤗	https://huggingface.co/mlx-community/DeepSeek-V3.2-Speciale-4bit
Base Model(s)	deepseek-ai/DeepSeek-V3.2-Speciale deepseek-ai/DeepSeek-V3.2-Speciale
Model Size	671.9b
Required VRAM	194.4 GB
Updated	2026-08-10
Maintainer	mlx-community
Model Type	deepseek_v32
Model Files	3.8 GB: 1-of-88 4.4 GB: 2-of-88 4.2 GB: 3-of-88 4.4 GB: 4-of-88 4.4 GB: 5-of-88 4.2 GB: 6-of-88 4.4 GB: 7-of-88 4.4 GB: 8-of-88 4.2 GB: 9-of-88 4.4 GB: 10-of-88 4.4 GB: 11-of-88 4.2 GB: 12-of-88 4.4 GB: 13-of-88 4.4 GB: 14-of-88 4.2 GB: 15-of-88 4.4 GB: 16-of-88 4.4 GB: 17-of-88 4.2 GB: 18-of-88 4.4 GB: 19-of-88 4.4 GB: 20-of-88 4.2 GB: 21-of-88 4.4 GB: 22-of-88 4.4 GB: 23-of-88 4.2 GB: 24-of-88 4.4 GB: 25-of-88 4.4 GB: 26-of-88 4.2 GB: 27-of-88 4.4 GB: 28-of-88 4.4 GB: 29-of-88 4.2 GB: 30-of-88 4.4 GB: 31-of-88 4.4 GB: 32-of-88 4.2 GB: 33-of-88 4.4 GB: 34-of-88 4.4 GB: 35-of-88 4.2 GB: 36-of-88 4.4 GB: 37-of-88 4.4 GB: 38-of-88 4.2 GB: 39-of-88 4.4 GB: 40-of-88 4.4 GB: 41-of-88 4.2 GB: 42-of-88 4.4 GB: 43-of-88 4.4 GB: 44-of-88 4.2 GB: 45-of-88
Quantization Type	4bit
Model Architecture	DeepseekV32ForCausalLM
License	mit
Context Length	163840
Model Max Length	163840
Transformers Version	4.44.2
Vocabulary Size	129280
Torch Data Type	bfloat16

Rank the DeepSeek V3.2 Speciale 4bit 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 V3.2 Speciale 4bit

Best Alternatives	Context / RAM	Downloads	Likes
DeepSeek V3.2 4bit	160K / 198.8 GB	846	7
DeepSeek V3.2 Mlx 5bit	160K / 241.6 GB	98	2
DeepSeek V3.2 Bf16	160K / 258.9 GB	59	1

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/DeepSeek-V3.2-Speciale-4bit.