What are the hardware requirements for Qwen2 1.5B Instruct GGUF?

Qwen2 1.5B Instruct GGUF requires approximately 0.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen2 1.5B Instruct GGUF and how large is it?

Qwen2 1.5B Instruct GGUF is developed by MaziyarPanahi, 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 1.5B Instruct GGUF?

Qwen2 1.5B Instruct GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2 1.5B Instruct GGUF by MaziyarPanahi — VRAM 0.4GB

Name: Qwen2 1.5B Instruct GGUF
Author: MaziyarPanahi

Qwen2 1.5B Instruct GGUF is an open-source language model by MaziyarPanahi. Features: 1.5b LLM, VRAM: 0.4GB, Quantized, Instruction-Based, LLM Explorer Score: 0.13.

2-bit 3-bit 4-bit 5-bit 6-bit 8-bit Base model:quantized:qwen/qwen... Base model:qwen/qwen2-1.5b-ins... Conversational Gguf Instruct Llama Llama-3 Mistral Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/MaziyarPanahi/Qwen2-1.5B-Instruct-GGUF

Qwen2 1.5B Instruct GGUF Parameters and Internals

Model Type

text-generation

Additional Notes

Quantized by MaziyarPanahi into GGUF format, which replaces the outdated GGML format.

LLM Name	Qwen2 1.5B Instruct GGUF
Repository 🤗	https://huggingface.co/MaziyarPanahi/Qwen2-1.5B-Instruct-GGUF
Model Name	Qwen2-1.5B-Instruct-GGUF
Model Creator	Qwen
Base Model(s)	Qwen/Qwen2-1.5B-Instruct Qwen/Qwen2-1.5B-Instruct
Model Size	1.5b
Required VRAM	0.4 GB
Updated	2026-07-20
Maintainer	MaziyarPanahi
Model Type	mistral
Instruction-Based	Yes
Model Files	0.5 GB 0.4 GB 0.6 GB 0.7 GB 0.9 GB 0.7 GB 0.9 GB 0.8 GB 0.8 GB 1.0 GB 0.9 GB 1.1 GB 1.1 GB 1.3 GB 1.6 GB 3.1 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel

Rank the Qwen2 1.5B Instruct GGUF 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 1.5B Instruct GGUF

Best Alternatives	Context / RAM	Downloads	Likes
MoeinGTS1.5 1.5B	0K / 1 GB	113	1
Jenna V3 Qwen2 1.5 GGUF Q4	0K / 1 GB	29	0
Jenna V3 Qwen2 1.5 GGUF	0K / 3.1 GB	24	1
...wen2.5 Coder 1.5B Instruct SFT	0K / 0 GB	6	0

Note: green Score (e.g. "73.2") means that the model is better than MaziyarPanahi/Qwen2-1.5B-Instruct-GGUF.