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

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

Qwen2.5 3B Instruct Chat Sft is developed by binhphap5, 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 Chat Sft?

Qwen2.5 3B Instruct Chat 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 Chat Sft by binhphap5 — VRAM 6.2GB, 32K context

Name: Qwen2.5 3B Instruct Chat Sft
Author: binhphap5

Qwen2.5 3B Instruct Chat Sft is an open-source language model by binhphap5. Features: 3b LLM, VRAM: 6.2GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.19.

4bit Autotrain compatible Conversational En Endpoints compatible Instruct Quantized Qwen2 Region:us Safetensors Sharded Tensorflow Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/binhphap5/Qwen2.5-3B-Instruct-Chat-sft

Qwen2.5 3B Instruct Chat Sft Benchmarks

LLME Score: 0.19218

^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 3B Instruct Chat Sft (binhphap5/Qwen2.5-3B-Instruct-Chat-sft)

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Qwen2.5 3B Instruct Chat Sft Parameters and Internals

LLM Name	Qwen2.5 3B Instruct Chat Sft
Repository 🤗	https://huggingface.co/binhphap5/Qwen2.5-3B-Instruct-Chat-sft
Base Model(s)	unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit
Model Size	3b
Required VRAM	6.2 GB
Updated	2025-09-23
Maintainer	binhphap5
Model Type	qwen2
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-2 1.2 GB: 2-of-2
Supported Languages	en
Quantization Type	4bit
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.51.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151936
Torch Data Type	float16
Errors	replace

Best Alternatives to Qwen2.5 3B Instruct Chat Sft

Best Alternatives	Context / RAM	Downloads	Likes
...5 3B Instruct Unsloth Bnb 4bit	32K / 2.4 GB	153672	7
TethysAI Base Reasoning	32K / 6.2 GB	55	0
Kyro N1 3B	32K / 6.2 GB	12	12
Athena 1 3B	32K / 6.2 GB	3	1
Qwen2.5 3B Reasoner	32K / 6.2 GB	15	0
QwQ LCoT 3B Instruct	32K / 6.2 GB	35	5
Test StealthThinker	32K / 6.2 GB	32	0
...2.5 Coder 3B Instruct Bnb 4bit	32K / 2 GB	21674	6
Qwen2.5 3B Instruct Bnb 4bit	32K / 2 GB	43519	14
Model 16bit	32K / 6.2 GB	7	0

Note: green Score (e.g. "73.2") means that the model is better than binhphap5/Qwen2.5-3B-Instruct-Chat-sft.

Rank the Qwen2.5 3B Instruct Chat Sft Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Qwen2.5 3B Instruct Chat Sft by binhphap5

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Qwen2.5 3B Instruct Chat Sft Benchmarks

Qwen2.5 3B Instruct Chat Sft Parameters and Internals

Best Alternatives to Qwen2.5 3B Instruct Chat Sft

Rank the Qwen2.5 3B Instruct Chat Sft Capabilities

What open-source LLMs or SLMs are you in search of? 53407 in total.