What are the hardware requirements for MediChat Medium?

MediChat Medium requires approximately 2.3 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed MediChat Medium and how large is it?

MediChat Medium is developed by ryorichie, a model with 3.9b 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 MediChat Medium?

MediChat Medium is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

MediChat Medium by ryorichie — VRAM 2.3GB, 4K context

Name: MediChat Medium
Author: ryorichie

MediChat Medium is an open-source language model by ryorichie. Features: 3.9b LLM, VRAM: 2.3GB, Context: 4K, License: mit, Quantized, Instruction-Based, LLM Explorer Score: 0.13.

4-bit 4bit Bitsandbytes Conversational Dataset:ryorichie/shortmedical... Endpoints compatible Id Instruct Mistral Quantized Region:us Safetensors Unsloth

Model Card on HF 🤗: https://huggingface.co/ryorichie/MediChat_Medium

MediChat Medium Parameters and Internals

Model Type

Text Generation

Use Cases

Considerations:

We want to address the challenges in accessing accurate and timely medical information, especially amidst issues such as long wait times for medical appointments, a shortage of medical professionals, temporal, geographical, and organizational barriers within the healthcare system, as well as limited access to healthcare resources. Our application aimed to provide a solution for individuals relying on online platforms for medical assistance by offering easier and more reliable access.

Supported Languages

Indonesia (NLP)

LLM Name	MediChat Medium
Repository 🤗	https://huggingface.co/ryorichie/MediChat_Medium
Model Size	3.9b
Required VRAM	2.3 GB
Updated	2026-08-06
Maintainer	ryorichie
Model Type	mistral
Instruction-Based	Yes
Model Files	2.3 GB
Supported Languages	id
Quantization Type	4bit
Model Architecture	MistralForCausalLM
License	mit
Context Length	4096
Model Max Length	4096
Transformers Version	4.41.0
Tokenizer Class	LlamaTokenizer
Padding Token	<\|placeholder6\|>
Vocabulary Size	32064
Torch Data Type	bfloat16

Rank the MediChat Medium 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

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Note: green Score (e.g. "73.2") means that the model is better than ryorichie/MediChat_Medium.