What are the hardware requirements for Meditor 1 2.2B A500M MoE?

Meditor 1 2.2B A500M MoE requires approximately 4.7 GB of VRAM and supports a context window of 512K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Meditor 1 2.2B A500M MoE and how large is it?

Meditor 1 2.2B A500M MoE is developed by Yo-Purple, 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 Meditor 1 2.2B A500M MoE?

Meditor 1 2.2B A500M MoE is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Meditor 1 2.2B A500M MoE by Yo-Purple — VRAM 4.7GB, 512K context

Name: Meditor 1 2.2B A500M MoE
Author: Yo-Purple

Meditor 1 2.2B A500M MoE is an open-source language model by Yo-Purple. Features: 0.5b LLM, VRAM: 4.7GB, Context: 512K, License: apache-2.0, Instruction-Based.

500k-context Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-0.5b-i... Conversational Custom-architecture Custom code Deepseek-style En Instruct Meditor Mixture-of-experts Moe Qwen2.5 Reasoning Region:us Safetensors Sparse-moe Toolformer

Model Card on HF 🤗: https://huggingface.co/Yo-Purple/Meditor-1-2.2B-A500M-MoE

Meditor 1 2.2B A500M MoE Parameters and Internals

LLM Name	Meditor 1 2.2B A500M MoE
Repository 🤗	https://huggingface.co/Yo-Purple/Meditor-1-2.2B-A500M-MoE
Model Name	Meditor-1-2.2B-A500M-MoE
Model Creator	Yo-Purple
Base Model(s)	Qwen/Qwen2.5-0.5B-Instruct Qwen/Qwen2.5-0.5B-Instruct
Model Size	0.5b
Required VRAM	4.7 GB
Updated	2026-11-06
Maintainer	Yo-Purple
Model Type	meditor
Instruction-Based	Yes
Model Files	4.7 GB
Supported Languages	en
Model Architecture	MeditorForCausalLM
License	apache-2.0
Context Length	524288
Model Max Length	524288
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

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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