What are the hardware requirements for Qwen2.5 14B Instruct 1M?

Qwen2.5 14B Instruct 1M requires approximately 29.6 GB of VRAM and supports a context window of 986K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen2.5 14B Instruct 1M and how large is it?

Qwen2.5 14B Instruct 1M is developed by Qwen, 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 1M?

Qwen2.5 14B Instruct 1M 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 1M by Qwen — VRAM 29.6GB, 986K context

Name: Qwen2.5 14B Instruct 1M
Author: Qwen

Qwen2.5 14B Instruct 1M is an open-source language model by Qwen. Features: 14b LLM, VRAM: 29.6GB, Context: 986K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.34.

Arxiv:2501.15383 Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-14b Chat Conversational Deploy:azure En Endpoints compatible Instruct Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen2.5-14B-Instruct-1M

Qwen2.5 14B Instruct 1M Parameters and Internals

LLM Name	Qwen2.5 14B Instruct 1M
Repository 🤗	https://huggingface.co/Qwen/Qwen2.5-14B-Instruct-1M
Base Model(s)	Qwen/Qwen2.5-14B Qwen/Qwen2.5-14B
Model Size	14b
Required VRAM	29.6 GB
Updated	2026-08-04
Maintainer	Qwen
Model Type	qwen2
Instruction-Based	Yes
Model Files	3.9 GB: 1-of-8 4.0 GB: 2-of-8 4.0 GB: 3-of-8 4.0 GB: 4-of-8 4.0 GB: 5-of-8 4.0 GB: 6-of-8 4.0 GB: 7-of-8 1.7 GB: 8-of-8
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	1010000
Model Max Length	1010000
Transformers Version	4.45.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 14B Instruct 1M 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

Quantized Models of the Qwen2.5 14B Instruct 1M

Model	Likes	Downloads	VRAM
Qwen2.5 14B Instruct 1M 8bit	12	430	15 GB
Qwen2.5 14B Instruct 1M 4bit	2	379	8 GB
...en2.5 14B Instruct 1M Bnb 4bit	2	95	9 GB
...B Instruct 1M Unsloth Bnb 4bit	4	14	14 GB

Best Alternatives to Qwen2.5 14B Instruct 1M

Best Alternatives	Context / RAM	Downloads	Likes
T3Q Qwen2.5 14B V1.0 E3	986K / 29.7 GB	852	28
...hts Qwen2.5 14B Coder Creative	986K / 29.3 GB	267	0
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