What are the hardware requirements for MedScholar 1.5B F32 GGUF?

MedScholar 1.5B F32 GGUF requires approximately 0.7 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed MedScholar 1.5B F32 GGUF and how large is it?

MedScholar 1.5B F32 GGUF is developed by prithivMLmods, 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 MedScholar 1.5B F32 GGUF?

MedScholar 1.5B F32 GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

MedScholar 1.5B F32 GGUF by prithivMLmods — VRAM 0.7GB

Name: MedScholar 1.5B F32 GGUF
Author: prithivMLmods

MedScholar 1.5B F32 GGUF is an open-source language model by prithivMLmods. Features: 1.5b LLM, VRAM: 0.7GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.19.

Base model:quantized:yasserrmd... Base model:yasserrmd/medschola... En Endpoints compatible Gguf Quantized Qwen2 Region:us

Model Card on HF 🤗: https://huggingface.co/prithivMLmods/MedScholar-1.5B-f32-GGUF

MedScholar 1.5B F32 GGUF Parameters and Internals

LLM Name	MedScholar 1.5B F32 GGUF
Repository 🤗	https://huggingface.co/prithivMLmods/MedScholar-1.5B-f32-GGUF
Base Model(s)	yasserrmd/MedScholar-1.5B yasserrmd/MedScholar-1.5B
Model Size	1.5b
Required VRAM	0.7 GB
Updated	2026-07-27
Maintainer	prithivMLmods
Model Type	qwen2
Model Files	3.1 GB 3.1 GB 6.2 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
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel
License	apache-2.0

Rank the MedScholar 1.5B F32 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 MedScholar 1.5B F32 GGUF

Best Alternatives	Context / RAM	Downloads	Likes
MoeinGTS1.5 1.5B	0K / 1 GB	113	1
Qwen2 1.5B Instruct GGUF	0K / 0.4 GB	346	8
Jenna V3 Qwen2 1.5 GGUF Q4	0K / 1 GB	29	0
Jenna V3 Qwen2 1.5 GGUF	0K / 3.1 GB	24	1
Qwen2 1.5B Ita V2	0K / 0.1 GB	16	0
Qwen2 1.5B	0K / 1.1 GB	13	0
Qwen2 1.5B MAC Gguf Q8 0	0K / 0.4 GB	23	0
Qwen2 1.5B MAC Gguf Q4 K M	0K / 0.3 GB	22	0
Qwen2 1.5B MAC Gguf F16	0K / 3.1 GB	17	0
Qwen2 1.5B Gguf F16	0K / 3.1 GB	16	0

Note: green Score (e.g. "73.2") means that the model is better than prithivMLmods/MedScholar-1.5B-f32-GGUF.