What are the hardware requirements for Qwen2.6 14B Instruct?

Qwen2.6 14B Instruct requires approximately 29.7 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 Qwen2.6 14B Instruct and how large is it?

Qwen2.6 14B Instruct is developed by qingy2024, 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 Qwen2.6 14B Instruct?

Qwen2.6 14B Instruct is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.6 14B Instruct by qingy2024 — VRAM 29.7GB, 128K context

Name: Qwen2.6 14B Instruct
Author: qingy2024

Qwen2.6 14B Instruct is an open-source language model by qingy2024. Features: 14b LLM, VRAM: 29.7GB, Context: 128K, Instruction-Based, Merged, LLM Explorer Score: 0.26.

Merged Model Arxiv:2306.01708 Arxiv:2311.03099 Ara Base model:arcee-ai/virtuoso-s... Base model:cultrix/seqwence-14... Base model:qingy2024/qwen2.5-m... Base model:qwen/qwen2.5-14b Base model:v000000/qwen2.5-lum... Conversational Deu Endpoints compatible Eng Fra Instruct Ita Jpn Kor Por Qwen2 Region:us Rus Safetensors Sharded Spa Tensorflow Tha Vie Zho

Model Card on HF 🤗: https://huggingface.co/qingy2024/Qwen2.6-14B-Instruct

Qwen2.6 14B Instruct Parameters and Internals

LLM Name	Qwen2.6 14B Instruct
Repository 🤗	https://huggingface.co/qingy2024/Qwen2.6-14B-Instruct
Base Model(s)	CultriX/Qwen2.5-14B-MegaMerge-pt2 qingy2019/Qwen2.5-Math-14B-Instruct SeQwence 14B v000000/Qwen2.5-Lumen-14B Virtuoso Small Qwen/Qwen2.5-14B CultriX/Qwen2.5-14B-MegaMerge-pt2 qingy2019/Qwen2.5-Math-14B-Instruct CultriX/SeQwence-14B v000000/Qwen2.5-Lumen-14B arcee-ai/Virtuoso-Small Qwen/Qwen2.5-14B
Merged Model	Yes
Model Size	14b
Required VRAM	29.7 GB
Updated	2026-05-22
Maintainer	qingy2024
Model Type	qwen2
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-6 5.0 GB: 2-of-6 5.0 GB: 3-of-6 5.0 GB: 4-of-6 5.0 GB: 5-of-6 4.8 GB: 6-of-6
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.46.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151665
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.6 14B Instruct 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 Qwen2.6 14B Instruct

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 14B Instruct 1M	986K / 29.6 GB	10388	342
T3Q Qwen2.5 14B V1.0 E3	986K / 29.7 GB	852	28
ZYH LLM Qwen2.5 14B V4	986K / 29.7 GB	27	8
Qwen2.5 14B 1M YOYO V3	986K / 29.7 GB	254	4
Qwen2.5 14B YOYO V4	986K / 29.7 GB	20	5
Qwen2.5 14B YOYO Latest V2	986K / 29.7 GB	129	0
ZYH LLM Qwen2.5 14B V3	986K / 29.7 GB	23	8
...14B Instruct 1M GRPO Reasoning	986K / 29.7 GB	11	4
Impish QWEN 14B 1M	986K / 29.7 GB	56	26
Q2.5 14B Instruct 1M Harmony	986K / 29.7 GB	3	1

Note: green Score (e.g. "73.2") means that the model is better than qingy2024/Qwen2.6-14B-Instruct.