What are the hardware requirements for Qwen2.5?

Qwen2.5 requires approximately 15.2 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen2.5 and how large is it?

Qwen2.5 is developed by pcjgg. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Qwen2.5 perform on standard benchmarks?

Qwen2.5 has the following published scores: LMSYS ELO 1374. Compare against reference models on this page or on the LLM Explorer leaderboards.

Qwen2.5 by pcjgg — VRAM 15.2GB, 128K context

Name: Qwen2.5
Author: pcjgg

Qwen2.5 is an open-source language model by pcjgg. Features: LLM, VRAM: 15.2GB, Context: 128K, License: llama3.3, LLM Explorer Score: 0.31, ELO: 1374.

Pytorch Qwen2 Region:us Sft Sharded Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/pcjgg/qwen2.5

Qwen2.5 Benchmarks

LMSys ELO 1374 vs 1272 (so35) 8%

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Qwen2.5 Parameters and Internals

LLM Name	Qwen2.5
Repository 🤗	https://huggingface.co/pcjgg/qwen2.5
Required VRAM	15.2 GB
Updated	2025-09-23
Maintainer	pcjgg
Model Type	qwen2
Model Files	4.9 GB: 1-of-4 4.9 GB: 2-of-4 4.3 GB: 3-of-4 1.1 GB: 4-of-4
Model Architecture	Qwen2ForCausalLM
License	llama3.3
Context Length	131072
Model Max Length	131072
Transformers Version	4.50.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	152064
Torch Data Type	float16
Errors	replace

Rank the Qwen2.5 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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