What are the hardware requirements for Aixcoder 7B GPTQ?

Aixcoder 7B GPTQ requires approximately 4.5 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 Aixcoder 7B GPTQ and how large is it?

Aixcoder 7B GPTQ is developed by TechxGenus, 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 Aixcoder 7B GPTQ?

Aixcoder 7B GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Aixcoder 7B GPTQ by TechxGenus — VRAM 4.5GB, 32K context

Name: Aixcoder 7B GPTQ
Author: TechxGenus

Aixcoder 7B GPTQ is an open-source language model by TechxGenus. Features: 7b LLM, VRAM: 4.5GB, Context: 32K, Quantized, LLM Explorer Score: 0.12.

4-bit Endpoints compatible Gptq Llama Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TechxGenus/aixcoder-7b-GPTQ

Aixcoder 7B GPTQ Parameters and Internals

Model Type

code generation, code completion

Use Cases

Areas:

real development scenarios

Applications:

code completion, code generation

Limitations:

Not specifically instruct-tuned for specialized tasks like test case generation and code debugging

Training Details

Data Volume:

1.2T Unique Tokens

Methodology:

Designed pre-training tasks and contextual information for real-world code generation contexts

Input Output

Performance Tips:

Install flash attention for faster inference speeds, especially for large models

LLM Name	Aixcoder 7B GPTQ
Repository 🤗	https://huggingface.co/TechxGenus/aixcoder-7b-GPTQ
Model Size	7b
Required VRAM	4.5 GB
Updated	2026-08-07
Maintainer	TechxGenus
Model Type	llama
Model Files	4.5 GB
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	LlamaForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.39.3
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	49152
Torch Data Type	float16

Rank the Aixcoder 7B GPTQ 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 Aixcoder 7B GPTQ

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Yarn Llama 2 7B 128K GPTQ	128K / 3.9 GB	8	7
Yarn Llama 2 7B 64K GPTQ	64K / 3.9 GB	10	1
... 7B 32K Instructions V4 Marlin	32K / 4.1 GB	8	0
Calm2 7B Chat GPTQ	32K / 4.4 GB	6	5
...Calm2 7B Chat GPTQ Calib Ja 1K	32K / 4.4 GB	4	5
Llama 2 7B 32K Instruct GPTQ	32K / 3.9 GB	49	27
Codebear 7B 4bit	16K / 3.9 GB	4	1
...a 7B Instruct GPTQ Calib Ja 1K	16K / 3.9 GB	6	0
Pandalyst 7B V1.2 GPTQ	16K / 3.9 GB	8	1
Tora Code 7B V1.0 GPTQ	16K / 3.9 GB	8	0

Note: green Score (e.g. "73.2") means that the model is better than TechxGenus/aixcoder-7b-GPTQ.