What are the hardware requirements for Llama 2 Coder 7B AWQ?

Llama 2 Coder 7B AWQ requires approximately 3.9 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama 2 Coder 7B AWQ and how large is it?

Llama 2 Coder 7B AWQ is developed by TheBloke, 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 Llama 2 Coder 7B AWQ?

Llama 2 Coder 7B AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 2 Coder 7B AWQ by TheBloke — VRAM 3.9GB, 4K context

Name: Llama 2 Coder 7B AWQ
Author: TheBloke

Llama 2 Coder 7B AWQ is an open-source language model by TheBloke. Features: 7b LLM, VRAM: 3.9GB, Context: 4K, License: apache-2.0, Quantized, Code Generating, LLM Explorer Score: 0.08.

4-bit Awq Base model:mrm8488/llama-2-cod... Base model:quantized:mrm8488/l... Code Codegen Coding Dataset:huggingfaceh4/codealpa... Generated from trainer Llama Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/Llama-2-Coder-7B-AWQ

Llama 2 Coder 7B AWQ Parameters and Internals

Model Type

text-generation, code-generation

Use Cases

Areas:

code generation, coding assistance

Applications:

software development, educational coding tools

Primary Use Cases:

coding assistant for instruction-based code generation

Additional Notes

The model includes optimizations for performance through quantization methods like AWQ, and is compatible with systems like vLLM for managing concurrent inference workloads.

Training Details

Data Sources:

HuggingFaceH4/CodeAlpaca_20K

Data Volume:

20k entries

Methodology:

Fine-tuning using QLoRA with PEFT library

Model Architecture:

Transformer-based architecture

Input Output

Input Format:

Instruction-based prompt template

Accepted Modalities:

text

Output Format:

Text-based code generation

LLM Name	Llama 2 Coder 7B AWQ
Repository 🤗	https://huggingface.co/TheBloke/Llama-2-Coder-7B-AWQ
Model Creator	mrm8488
Base Model(s)	Llama 2 Coder 7B mrm8488/llama-2-coder-7b
Model Size	7b
Required VRAM	3.9 GB
Updated	2026-08-06
Maintainer	TheBloke
Model Type	llama
Model Files	3.9 GB
Supported Languages	code
AWQ Quantization	Yes
Quantization Type	awq
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.31.0
Tokenizer Class	LlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Llama 2 Coder 7B 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 Llama 2 Coder 7B AWQ

Best Alternatives	Context / RAM	Downloads	Likes
CodeLlama 7B Instruct AWQ	16K / 3.9 GB	278	4
CodeLlama 7B AWQ	16K / 3.9 GB	75	6
CodeLlama 7B Python AWQ	16K / 3.9 GB	5	4
...Llama 7B Python Hf W4 G128 AWQ	16K / 3.9 GB	8	0
...ama 7B Instruct Hf W4 G128 AWQ	16K / 3.9 GB	6	0
...eepseek Coder 7B Base V1.5 AWQ	4K / 4.8 GB	0	0
CodeLlama 7B Java 16bit	16K / 13.5 GB	10	0
Codellama 7B Bnb 4bit	16K / 3.9 GB	3695	9
...ruct Solidity Bnb 4bit Smashed	16K / 4.2 GB	6	0
...lama 7B Tofuagent Contpretrain	16K / 13.5 GB	6	0

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Llama-2-Coder-7B-AWQ.