What are the hardware requirements for Qwen2.5 3B Instruct Bespoke Full Sft?

Qwen2.5 3B Instruct Bespoke Full Sft 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 Instruct Bespoke Full Sft and how large is it?

Qwen2.5 3B Instruct Bespoke Full Sft is developed by groundhogLLM, 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 Instruct Bespoke Full Sft?

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

Qwen2.5 3B Instruct Bespoke Full Sft by groundhogLLM — VRAM 6.2GB, 32K context

Name: Qwen2.5 3B Instruct Bespoke Full Sft
Author: groundhogLLM

Qwen2.5 3B Instruct Bespoke Full Sft is an open-source language model by groundhogLLM. Features: 3b LLM, VRAM: 6.2GB, Context: 32K, License: other, Instruction-Based, LLM Explorer Score: 0.18.

Autotrain compatible Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-3b-ins... Conversational Endpoints compatible Full Generated from trainer Instruct Llama-factory Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/groundhogLLM/Qwen2.5-3B-Instruct-bespoke-full-sft

Qwen2.5 3B Instruct Bespoke Full Sft Parameters and Internals

LLM Name	Qwen2.5 3B Instruct Bespoke Full Sft
Repository 🤗	https://huggingface.co/groundhogLLM/Qwen2.5-3B-Instruct-bespoke-full-sft
Base Model(s)	Qwen/Qwen2.5-3B-Instruct Qwen/Qwen2.5-3B-Instruct
Model Size	3b
Required VRAM	6.2 GB
Updated	2025-09-23
Maintainer	groundhogLLM
Model Type	qwen2
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-2 1.2 GB: 2-of-2 0.0 GB
Model Architecture	Qwen2ForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.49.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 3B Instruct Bespoke Full Sft 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

Best Alternatives to Qwen2.5 3B Instruct Bespoke Full Sft

Best Alternatives	Context / RAM	Downloads	Likes
VibeThinker 3B	128K / 6.2 GB	52745	806
VibeThinker 3B	128K / 6.2 GB	361	0
Saba2 3B	128K / 6.2 GB	6	0
Tessa T1 3B	117K / 6.2 GB	10	5
UIGEN T1.5 3B	117K / 6.2 GB	7	1
Qwen2.5 3B Instruct	32K / 6.2 GB	5889234	545
SmallThinker 3B Preview	32K / 6.8 GB	30529	412
Qwen2.5 3B Haizi	32K / 6.2 GB	74	0
...n2.5 3B FinCode Reasoning Full	32K / 6.2 GB	12	1
ResearchMate Qwen2.5 3B	32K / 6.2 GB	66	2

Note: green Score (e.g. "73.2") means that the model is better than groundhogLLM/Qwen2.5-3B-Instruct-bespoke-full-sft.