What are the hardware requirements for Qwen1.5 0.5B Chat SFT MCQA AWQ?

Qwen1.5 0.5B Chat SFT MCQA AWQ requires approximately 0.8 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 Qwen1.5 0.5B Chat SFT MCQA AWQ and how large is it?

Qwen1.5 0.5B Chat SFT MCQA AWQ is developed by attention-avengers, a model with 0.5b 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 Qwen1.5 0.5B Chat SFT MCQA AWQ?

Qwen1.5 0.5B Chat SFT MCQA AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen1.5 0.5B Chat SFT MCQA AWQ by attention-avengers — VRAM 0.8GB, 32K context

Name: Qwen1.5 0.5B Chat SFT MCQA AWQ
Author: attention-avengers

Qwen1.5 0.5B Chat SFT MCQA AWQ is an open-source language model by attention-avengers. Features: 0.5b LLM, VRAM: 0.8GB, Context: 32K, Quantized, LLM Explorer Score: 0.13.

4-bit Awq Conversational Endpoints compatible Quantized Qwen2 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/attention-avengers/Qwen1.5-0.5B-Chat-SFT-MCQA-AWQ

Qwen1.5 0.5B Chat SFT MCQA AWQ Parameters and Internals

LLM Name	Qwen1.5 0.5B Chat SFT MCQA AWQ
Repository 🤗	https://huggingface.co/attention-avengers/Qwen1.5-0.5B-Chat-SFT-MCQA-AWQ
Base Model(s)	attention-avengers/Qwen1.5-0.5B-Chat-SFT-MCQA attention-avengers/Qwen1.5-0.5B-Chat-SFT-MCQA
Model Size	0.5b
Required VRAM	0.8 GB
Updated	2026-08-08
Maintainer	attention-avengers
Model Type	qwen2
Model Files	0.8 GB
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	Qwen2ForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.42.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|im_end\|>
Vocabulary Size	151936
Torch Data Type	float16
Errors	replace

Rank the Qwen1.5 0.5B Chat SFT MCQA AWQ 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 Qwen1.5 0.5B Chat SFT MCQA AWQ

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 0.5B Instruct AWQ	32K / 0.7 GB	22040	11
...wen2.5 Coder 0.5B Instruct AWQ	32K / 0.7 GB	392	3
Qwen2 0.5B Instruct AWQ	32K / 0.7 GB	78	5
...en2 0.5B Chat SFT AWQ Q4 NoCal	32K / 0.7 GB	5	0
Qwen1.5 0.5B Chat AWQ	32K / 0.8 GB	224	7
Qwen2 0.5B Finetune Exp 2	128K / 1 GB	16	0
Qwen2 0.5B 20240829 175401	128K / 1 GB	8	0
Qwen2 0.5B Bnb 4bit	128K / 0.5 GB	1123	3
Qwen2 0.5B Alpaca Merged St	128K / 1 GB	6	0
Qwen2 0.5B Assamese V0.2.1	128K / 1 GB	12	0

Note: green Score (e.g. "73.2") means that the model is better than attention-avengers/Qwen1.5-0.5B-Chat-SFT-MCQA-AWQ.