What are the hardware requirements for Qwen2.5 1.5B Instruct 4bit?

Qwen2.5 1.5B Instruct 4bit requires approximately 0.9 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 1.5B Instruct 4bit and how large is it?

Qwen2.5 1.5B Instruct 4bit is developed by mlx-community, a model with 1.5b 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 1.5B Instruct 4bit?

Qwen2.5 1.5B 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 1.5B Instruct 4bit by mlx-community — VRAM 0.9GB, 32K context

Name: Qwen2.5 1.5B Instruct 4bit
Author: mlx-community

Qwen2.5 1.5B Instruct 4bit is an open-source language model by mlx-community. Features: 1.5b LLM, VRAM: 0.9GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.18.

4bit Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-1.5b Chat Conversational En Instruct Mlx Quantized Qwen2 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/mlx-community/Qwen2.5-1.5B-Instruct-4bit

Qwen2.5 1.5B Instruct 4bit Parameters and Internals

LLM Name	Qwen2.5 1.5B Instruct 4bit
Repository 🤗	https://huggingface.co/mlx-community/Qwen2.5-1.5B-Instruct-4bit
Base Model(s)	Qwen/Qwen2.5-1.5B Qwen/Qwen2.5-1.5B
Model Size	1.5b
Required VRAM	0.9 GB
Updated	2026-08-01
Maintainer	mlx-community
Model Type	qwen2
Instruction-Based	Yes
Model Files	0.9 GB
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	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 1.5B 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 1.5B Instruct 4bit

Best Alternatives	Context / RAM	Downloads
Qwen25 1.5B Alpaca Id Sft	32K / 3.1 GB	2038
Qwen2.5 1.5B Instruct Legal Id	32K / 3.1 GB	1425
Legal Chatbot Qwen2.5 1.5B Id	32K / 3.1 GB	250
Legal Chatbot Llama3 Finetuned	32K / 3.1 GB	389
Legal Chatbot Llama3 Finetuned	32K / 3.1 GB	297
Legal Qwen2.5 1.5B Sft	32K / 3.1 GB	1031
Legal Chatbot Qwen2.5 1.5B Sft	32K / 3.1 GB	871
....5B Instruct Legal Chatbot Sft	32K / 3.1 GB	592
Qwen2.5 1.5B Legal Sft	32K / 3.1 GB	677
Legal Chatbot Qwen2.5 1.5B Sft	32K / 3.1 GB	506

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/Qwen2.5-1.5B-Instruct-4bit.