What are the hardware requirements for Ramgpt 13B AWQ Gemm?

Ramgpt 13B AWQ Gemm requires approximately 7.2 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Ramgpt 13B AWQ Gemm and how large is it?

Ramgpt 13B AWQ Gemm is developed by ramgpt, a model with 13b 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 Ramgpt 13B AWQ Gemm?

Ramgpt 13B AWQ Gemm is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Ramgpt 13B AWQ Gemm by ramgpt — VRAM 7.2GB, 16K context

Name: Ramgpt 13B AWQ Gemm
Author: ramgpt

Ramgpt 13B AWQ Gemm is an open-source language model by ramgpt. Features: 13b LLM, VRAM: 7.2GB, Context: 16K, License: apache-2.0, Quantized, Code Generating, LLM Explorer Score: 0.1.

4-bit Adapter-transformers Awq Code Codegen Custom code Dataset:open-orca/openorca En Instruct Llama Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/ramgpt/ramgpt-13b-awq-gemm

Ramgpt 13B AWQ Gemm Parameters and Internals

Model Type

question-answering

Use Cases

Primary Use Cases:

Advanced AI Computations, Efficient Machine Learning Operations, Data-Intensive Applications

Additional Notes

The ramgpt-13b-awq-gemm model is continuously evolving, incorporating cutting-edge advancements in AI and quantization techniques for enhanced performance.

Supported Languages

en (proficient)

LLM Name	Ramgpt 13B AWQ Gemm
Repository 🤗	https://huggingface.co/ramgpt/ramgpt-13b-awq-gemm
Model Size	13b
Required VRAM	7.2 GB
Updated	2026-06-26
Maintainer	ramgpt
Model Type	llama
Model Files	7.2 GB
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	16384
Model Max Length	16384
Transformers Version	4.35.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32016
Torch Data Type	float16

Rank the Ramgpt 13B AWQ Gemm 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 Ramgpt 13B AWQ Gemm

Best Alternatives	Context / RAM	Downloads	Likes
...th CodeLlama 13B Python Hf AWQ	16K / 7.5 GB	6	0
CodeLlama 13B Instruct AWQ	16K / 7.2 GB	261	9
NexusRaven 13B AWQ	16K / 7.2 GB	22	4
CodeLlama 13B AWQ	16K / 7.2 GB	115	4
MAmmoTH Coder 13B AWQ	16K / 7.2 GB	6	1
...odeLlama 13B Oasst Sft V10 AWQ	16K / 7.2 GB	7	1
CodeLlama 13B Python AWQ	16K / 7.2 GB	14	2
...ma 13B Instruct Hf W4 G128 AWQ	16K / 7.2 GB	10	0
...lama 13B Python Hf W4 G128 AWQ	16K / 7.2 GB	5	0
WhiteRabbitNeo 13B V1	16K / 26 GB	3146	453

Note: green Score (e.g. "73.2") means that the model is better than ramgpt/ramgpt-13b-awq-gemm.