What are the hardware requirements for Qwen2.5 Coder 7B Instruct AWQ?

Qwen2.5 Coder 7B Instruct AWQ requires approximately 5.6 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 7B Instruct AWQ and how large is it?

Qwen2.5 Coder 7B Instruct AWQ is developed by Qwen, a model with 7b 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 7B Instruct AWQ?

Qwen2.5 Coder 7B 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 7B Instruct AWQ by Qwen — VRAM 5.6GB, 32K context

Name: Qwen2.5 Coder 7B Instruct AWQ
Author: Qwen

Qwen2.5 Coder 7B Instruct AWQ is an open-source language model by Qwen. Features: 7b LLM, VRAM: 5.6GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, Code Generating, LLM Explorer Score: 0.23.

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-7B-Instruct-AWQ

Qwen2.5 Coder 7B Instruct AWQ Parameters and Internals

Model Type

text-generation

Use Cases

Areas:

code generation

Applications:

Code reasoning, code fixing, real-world applications like Code Agents

Primary Use Cases:

Coding enhancements, mathematics and general competencies

Limitations:

Performance impact on shorter texts with static YaRN configuration

Considerations:

Advised `rope_scaling` configuration only for long context processing

Supported Languages

en (English)

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

Performance Tips:

To enable YaRN, add specific configurations to `config.json`

LLM Name	Qwen2.5 Coder 7B Instruct AWQ
Repository 🤗	https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct-AWQ
Base Model(s)	Qwen/Qwen2.5-Coder-7B-Instruct Qwen/Qwen2.5-Coder-7B-Instruct
Model Size	7b
Required VRAM	5.6 GB
Updated	2026-06-09
Maintainer	Qwen
Model Type	qwen2
Instruction-Based	Yes
Model Files	4.0 GB: 1-of-2 1.6 GB: 2-of-2
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	4.44.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	float16
Errors	replace

Rank the Qwen2.5 Coder 7B 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 7B Instruct AWQ

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Qwen2.5 Coder 7B Instruct AWQ	32K / 5.7 GB	563249	1
Text2sql Qwen2.5 Duckdb	32K / 15.2 GB	336	1
...query Qwen2.5 7B V5.2 Hardened	32K / 15.2 GB	478	0
Securereview 7B Mlx 4bit	32K / 4.3 GB	22	4
...2.5 Coder 7B Instruct Bnb 4bit	32K / 5.5 GB	74603	13
Qwen2.5 CoderX 7B V0.7	32K / 15.2 GB	5	2
Qwen2.5 Coder 7B Instruct 4bit	32K / 4.3 GB	13602	17
Qwen2.5 CoderX 7B V0.5	32K / 15.2 GB	6	2
Sft Model	32K / 15.2 GB	8	0
UIGEN 7B 16bit	32K / 15.2 GB	14	5

Note: green Score (e.g. "73.2") means that the model is better than Qwen/Qwen2.5-Coder-7B-Instruct-AWQ.