What are the hardware requirements for Qwen2.5 32B Instruct 4bit?

Qwen2.5 32B Instruct 4bit requires approximately 18.5 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 Qwen2.5 32B Instruct 4bit and how large is it?

Qwen2.5 32B Instruct 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 Qwen2.5 32B Instruct 4bit?

Qwen2.5 32B Instruct 4bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 32B Instruct 4bit by mlx-community — VRAM 18.5GB, 32K context

Name: Qwen2.5 32B Instruct 4bit
Author: mlx-community

Qwen2.5 32B Instruct 4bit is an open-source language model by mlx-community. Features: 32b LLM, VRAM: 18.5GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.16.

4bit Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-32b Chat Conversational En Instruct Mlx Quantized Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mlx-community/Qwen2.5-32B-Instruct-4bit

Qwen2.5 32B Instruct 4bit Parameters and Internals

LLM Name	Qwen2.5 32B Instruct 4bit
Repository 🤗	https://huggingface.co/mlx-community/Qwen2.5-32B-Instruct-4bit
Base Model(s)	Qwen/Qwen2.5-32B Qwen/Qwen2.5-32B
Model Size	32b
Required VRAM	18.5 GB
Updated	2026-08-06
Maintainer	mlx-community
Model Type	qwen2
Instruction-Based	Yes
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	en
Quantization Type	4bit
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.43.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 32B Instruct 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 Qwen2.5 32B Instruct 4bit

Best Alternatives	Context / RAM	Downloads	Likes
EVA Instruct 32B EXL2 4.0	128K / 17.7 GB	4	3
....5 Coder 32B Instruct Bnb 4bit	32K / 19.2 GB	5519	6
...wen2.5 Coder 32B Instruct 3bit	32K / 14.3 GB	144	4
Qwen 32B Incorrect Trivia 2	32K / 65.8 GB	12	0
Qwen2.5 32B Instruct Bnb 4bit	32K / 19.2 GB	49427	15
...wen2.5 Coder 32B Instruct 4bit	32K / 18.5 GB	2357	12
Cogito R1	32K / 65.8 GB	8	5
...wen2.5 Coder 32B Instruct 8bit	32K / 34.9 GB	934	14
Qwen2.5 32B Instruct 8bit	32K / 34.9 GB	979	7
...truct Gptqmodel 4bit Vortex V1	32K / 21.3 GB	83	16

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/Qwen2.5-32B-Instruct-4bit.