What are the hardware requirements for Qwen2.5 Coder 14B Instruct AWQ?

Qwen2.5 Coder 14B Instruct AWQ requires approximately 10 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 Coder 14B Instruct AWQ and how large is it?

Qwen2.5 Coder 14B Instruct AWQ 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 Coder 14B Instruct AWQ?

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

Qwen2.5 Coder 14B Instruct AWQ by Qwen — VRAM 10GB, 32K context

Name: Qwen2.5 Coder 14B Instruct AWQ
Author: Qwen

Qwen2.5 Coder 14B Instruct AWQ is an open-source language model by Qwen. Features: 14b LLM, VRAM: 10GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, Code Generating, LLM Explorer Score: 0.25.

Arxiv:2309.00071 Arxiv:2407.10671 Arxiv:2409.12186 4-bit Awq Base model:quantized:qwen/qwen... Base model:qwen/qwen2.5-coder-... Chat Code Codegen Codeqwen Conversational Deploy:azure En Endpoints compatible Instruct Quantized Qwen Qwen-coder Qwen2 Region:us Safetensors Sharded Tensorflow

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

Qwen2.5 Coder 14B Instruct AWQ Parameters and Internals

Model Type

Causal Language Model

Use Cases

Areas:

research, commercial applications

Applications:

Code Agents, coding capabilities, mathematics, general competencies

Primary Use Cases:

code generation, code reasoning, code fixing

Supported Languages

en (High)

Training Details

Data Sources:

source code, text-code grounding, Synthetic data

Data Volume:

5.5 trillion tokens

Methodology:

Pretraining & Post-training

Context Length:

131072

Model Architecture:

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

Input Output

Input Format:

Message-based prompt template with roles (system, user)

Accepted Modalities:

text

Performance Tips:

Add 'rope_scaling' configuration for handling long texts; optimize for long contexts with YaRN.

LLM Name	Qwen2.5 Coder 14B Instruct AWQ
Repository 🤗	https://huggingface.co/Qwen/Qwen2.5-Coder-14B-Instruct-AWQ
Base Model(s)	Qwen/Qwen2.5-Coder-14B-Instruct Qwen/Qwen2.5-Coder-14B-Instruct
Model Size	14b
Required VRAM	10 GB
Updated	2026-07-19
Maintainer	Qwen
Model Type	qwen2
Instruction-Based	Yes
Model Files	4.0 GB: 1-of-3 4.0 GB: 2-of-3 2.0 GB: 3-of-3
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Generates Code	Yes
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.43.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	float16
Errors	replace

Rank the Qwen2.5 Coder 14B Instruct AWQ 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 Coder 14B Instruct AWQ

Best Alternatives	Context / RAM	Downloads	Likes
CogitoZ14	32K / 29.7 GB	25	1
....5 Coder 14B Instruct Bnb 4bit	32K / 9.9 GB	21134	5
UIGEN T1.1 Qwen 14B	32K / 29.7 GB	1130	32
Qwen 14B Codefourchan	32K / 29.7 GB	2	1
...wen2.5 Coder 14B Instruct 4bit	32K / 8.3 GB	2879	8
UIGEN T1.1 Qwen 14B	32K / 29.7 GB	95	41
UIGEN T1.2 Tailwind 14B	32K / 29.7 GB	4	1
Korean QWEN Coder2.5 14B	32K / 29.7 GB	19	4
...hts Qwen2.5 14B Coder Creative	986K / 29.3 GB	267	0
ZYH LLM Qwen2.5 14B V4	986K / 29.7 GB	27	8

Note: green Score (e.g. "73.2") means that the model is better than Qwen/Qwen2.5-Coder-14B-Instruct-AWQ.