What are the hardware requirements for Qwen2.5 3B Sft 10?

Qwen2.5 3B Sft 10 requires approximately 6.2 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen2.5 3B Sft 10 and how large is it?

Qwen2.5 3B Sft 10 is developed by CriteriaPO, a model with 3b 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 Qwen2.5 3B Sft 10?

Qwen2.5 3B Sft 10 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 3B Sft 10 by CriteriaPO — VRAM 6.2GB, 32K context

Name: Qwen2.5 3B Sft 10
Author: CriteriaPO

Qwen2.5 3B Sft 10 is an open-source language model by CriteriaPO. Features: 3b LLM, VRAM: 6.2GB, Context: 32K, LLM Explorer Score: 0.18.

Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-3b Conversational Endpoints compatible Generated from trainer Qwen2 Region:us Safetensors Sft Sharded Tensorflow Trl

Model Card on HF 🤗: https://huggingface.co/CriteriaPO/qwen2.5-3b-sft-10

Qwen2.5 3B Sft 10 Parameters and Internals

LLM Name	Qwen2.5 3B Sft 10
Repository 🤗	https://huggingface.co/CriteriaPO/qwen2.5-3b-sft-10
Model Name	qwen2.5-3b-sft-10
Base Model(s)	Qwen/Qwen2.5-3B Qwen/Qwen2.5-3B
Model Size	3b
Required VRAM	6.2 GB
Updated	2026-08-31
Maintainer	CriteriaPO
Model Type	qwen2
Model Files	5.0 GB: 1-of-2 1.2 GB: 2-of-2 0.0 GB
Model Architecture	Qwen2ForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.46.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|im_end\|>
Vocabulary Size	151665
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 3B Sft 10 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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Note: green Score (e.g. "73.2") means that the model is better than CriteriaPO/qwen2.5-3b-sft-10.