What are the hardware requirements for Llamamerge?

Llamamerge requires approximately 26 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 Llamamerge and how large is it?

Llamamerge is developed by sumink, 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 Llamamerge?

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

Llamamerge by sumink — VRAM 26GB, 4K context

Name: Llamamerge
Author: sumink

Llamamerge is an open-source language model by sumink. Features: 13b LLM, VRAM: 26GB, Context: 4K, License: llama3, Merged, LLM Explorer Score: 0.2.

Merged Model Llama Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/sumink/llamamerge

Llamamerge Parameters and Internals

LLM Name	Llamamerge
Repository 🤗	https://huggingface.co/sumink/llamamerge
Merged Model	Yes
Model Size	13b
Required VRAM	26 GB
Updated	2026-07-27
Maintainer	sumink
Model Type	llama
Model Files	5.0 GB: 1-of-6 5.0 GB: 2-of-6 4.9 GB: 3-of-6 4.9 GB: 4-of-6 4.9 GB: 5-of-6 1.3 GB: 6-of-6
Model Architecture	LlamaForCausalLM
License	llama3
Context Length	4096
Model Max Length	4096
Transformers Version	4.47.1
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the Llamamerge 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

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