What are the hardware requirements for Qwen1.5 0.5B Chat Mistral?

Qwen1.5 0.5B Chat Mistral requires approximately 1.2 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 Mistral and how large is it?

Qwen1.5 0.5B Chat Mistral is developed by Minami-su, 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.

How does Qwen1.5 0.5B Chat Mistral perform on standard benchmarks?

Qwen1.5 0.5B Chat Mistral has the following published scores: MMLU 23.08. Compare against reference models on this page or on the LLM Explorer leaderboards.

Qwen1.5 0.5B Chat Mistral by Minami-su — VRAM 1.2GB, 32K context

Name: Qwen1.5 0.5B Chat Mistral
Author: Minami-su

Qwen1.5 0.5B Chat Mistral is an open-source language model by Minami-su. Features: 0.5b LLM, VRAM: 1.2GB, Context: 32K, License: other, LLM Explorer Score: 0.16, Arc: 25.5, HellaSwag: 26.4, MMLU: 23.1.

Conversational En Mistral Pytorch Qwen Qwen1.5 Qwen2 Region:us Zh

Model Card on HF 🤗: https://huggingface.co/Minami-su/Qwen1.5-0.5B-Chat_mistral

Qwen1.5 0.5B Chat Mistral Parameters and Internals

Model Type

text-generation

Additional Notes

Modifications were made to the Mistral version for compatibility with Qwen1.5-0.5B-Chat. The model can load in 4-bit precision.

Input Output

Input Format:

JSON (role-based messages)

Accepted Modalities:

text

Output Format:

text

Performance Tips:

The model can be loaded in 4-bit precision for performance optimization.

LLM Name	Qwen1.5 0.5B Chat Mistral
Repository 🤗	https://huggingface.co/Minami-su/Qwen1.5-0.5B-Chat_mistral
Model Size	0.5b
Required VRAM	1.2 GB
Updated	2026-07-14
Maintainer	Minami-su
Model Type	mistral
Model Files	1.2 GB
Supported Languages	en zh
Model Architecture	MistralForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.34.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen1.5 0.5B Chat Mistral 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 Mistral

Best Alternatives	Context / RAM	Downloads	Likes
Mistral 0.5B 40K	40K / 1.2 GB	11	2
Mistral 0.5B Base	4K / 2.1 GB	9	0

Note: green Score (e.g. "73.2") means that the model is better than Minami-su/Qwen1.5-0.5B-Chat_mistral.