What are the hardware requirements for Qwen2.5 14B Instruct Bnb 4bit?

Qwen2.5 14B Instruct Bnb 4bit requires approximately 9.9 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 14B Instruct Bnb 4bit and how large is it?

Qwen2.5 14B Instruct Bnb 4bit is developed by unsloth, a model with 14b 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 14B Instruct Bnb 4bit?

Qwen2.5 14B Instruct Bnb 4bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 14B Instruct Bnb 4bit by unsloth — VRAM 9.9GB, 32K context

Name: Qwen2.5 14B Instruct Bnb 4bit
Author: unsloth

Qwen2.5 14B Instruct Bnb 4bit is an open-source language model by unsloth. Features: 14b LLM, VRAM: 9.9GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.2.

Arxiv:2309.00071 Arxiv:2407.10671 4-bit 4bit Ara Base model:quantized:qwen/qwen... Base model:qwen/qwen2.5-14b-in... Bitsandbytes Conversational Deu Endpoints compatible Eng Fra Instruct Ita Jpn Kor Por Quantized Qwen2 Region:us Rus Safetensors Sharded Spa Tensorflow Tha Unsloth Vie Zho

Model Card on HF 🤗: https://huggingface.co/unsloth/Qwen2.5-14B-Instruct-bnb-4bit

Qwen2.5 14B Instruct Bnb 4bit Parameters and Internals

Model Type

Causal Language Models

Supported Languages

en (Full), multi-languages (Multilingual support for over 29 languages)

Training Details

Methodology:

Pretraining & Post-training

Context Length:

131072

Model Architecture:

transformers with RoPE, SwiGLU, RMSNorm, and Attention QKV bias

LLM Name	Qwen2.5 14B Instruct Bnb 4bit
Repository 🤗	https://huggingface.co/unsloth/Qwen2.5-14B-Instruct-bnb-4bit
Base Model(s)	Qwen/Qwen2.5-14B-Instruct Qwen/Qwen2.5-14B-Instruct
Model Size	14b
Required VRAM	9.9 GB
Updated	2026-07-23
Maintainer	unsloth
Model Type	qwen2
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-2 4.9 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	4.49.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 14B Instruct Bnb 4bit 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

Quantized Models of the Qwen2.5 14B Instruct Bnb 4bit

Model	Likes	Downloads	VRAM
Qwen Carpmuscle V0.4.1	0	9	29 GB
Qwen Carpmuscle V0.4	1	9	29 GB
Qwen Carpmuscle V0.2	0	10	29 GB
Qwen Carpmuscle V0.1	0	11	29 GB

Best Alternatives to Qwen2.5 14B Instruct Bnb 4bit

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 14B Instruct 1M 8bit	986K / 15.7 GB	430	12
Qwen2.5 14B Instruct 1M 4bit	986K / 8.3 GB	379	2
...en2.5 14B Instruct 1M Bnb 4bit	986K / 9.9 GB	95	2
...B Instruct 1M Unsloth Bnb 4bit	986K / 14.3 GB	14	4
...n2.5 Math 14B Instruct Preview	32K / 29.7 GB	51	1
Qwen Carpmuscle V0.4.1	32K / 29.7 GB	9	0
...wen2.5 Math 14B Instruct Alpha	32K / 29.7 GB	57	2
Reasoning 1 1K Demo	32K / 29.7 GB	38	1
RQwen V0.1	32K / 29.7 GB	30	2
Sphinx2.0	32K / 29.7 GB	0	1

Note: green Score (e.g. "73.2") means that the model is better than unsloth/Qwen2.5-14B-Instruct-bnb-4bit.