What are the hardware requirements for Puro 2B Base?

Puro 2B Base requires approximately 4.1 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 Puro 2B Base and how large is it?

Puro 2B Base is developed by thu-pacman, a model with 2b 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 Puro 2B Base?

Puro 2B Base is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Puro 2B Base by thu-pacman — VRAM 4.1GB, 4K context

Name: Puro 2B Base
Author: thu-pacman

Puro 2B Base is an open-source language model by thu-pacman. Features: 2b LLM, VRAM: 4.1GB, Context: 4K, License: apache-2.0, LLM Explorer Score: 0.32.

Arxiv:2608.27370 Base-model Conversational Dataset:thu-pacman/puro-2b En Endpoints compatible Fp8 Fully-open Open-recipe Qwen3 Region:us Rtx-5090 Safetensors Zh

Model Card on HF 🤗: https://huggingface.co/thu-pacman/Puro-2B-Base

Puro 2B Base Parameters and Internals

LLM Name	Puro 2B Base
Repository 🤗	https://huggingface.co/thu-pacman/Puro-2B-Base
Model Size	2b
Required VRAM	4.1 GB
Updated	2026-09-02
Maintainer	thu-pacman
Model Type	qwen3
Model Files	4.1 GB
Supported Languages	en zh
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	4096
Model Max Length	4096
Transformers Version	5.13.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Errors	replace

Rank the Puro 2B Base capabilities

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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

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