What are the hardware requirements for Gilgamesh 72B?

Gilgamesh 72B requires approximately 146 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 Gilgamesh 72B and how large is it?

Gilgamesh 72B is developed by rubenroy, a model with 72b 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 Gilgamesh 72B?

Gilgamesh 72B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gilgamesh 72B by rubenroy — VRAM 146GB, 32K context

Name: Gilgamesh 72B
Author: rubenroy

Gilgamesh 72B is an open-source language model by rubenroy. Features: 72b LLM, VRAM: 146GB, Context: 32K, License: other, Instruction-Based, LLM Explorer Score: 0.3.

Autotrain compatible Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-72b-in... Chat Conversational Dataset:rubenroy/gammacorpus-c... Dataset:rubenroy/gammacorpus-f... Dataset:rubenroy/gammacorpus-v... En Endpoints compatible Gammacorpus Gilgamesh Instruct Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/rubenroy/Gilgamesh-72B

Gilgamesh 72B Parameters and Internals

LLM Name	Gilgamesh 72B
Repository 🤗	https://huggingface.co/rubenroy/Gilgamesh-72B
Base Model(s)	Qwen/Qwen2.5-72B-Instruct Qwen/Qwen2.5-72B-Instruct
Model Size	72b
Required VRAM	146 GB
Updated	2025-05-24
Maintainer	rubenroy
Model Type	qwen2
Instruction-Based	Yes
Model Files	4.5 GB: 1-of-31 5.0 GB: 2-of-31 4.8 GB: 3-of-31 4.8 GB: 4-of-31 4.8 GB: 5-of-31 5.0 GB: 6-of-31 4.8 GB: 7-of-31 4.8 GB: 8-of-31 4.8 GB: 9-of-31 5.0 GB: 10-of-31 4.8 GB: 11-of-31 4.8 GB: 12-of-31 4.8 GB: 13-of-31 5.0 GB: 14-of-31 4.8 GB: 15-of-31 4.8 GB: 16-of-31 4.8 GB: 17-of-31 5.0 GB: 18-of-31 4.8 GB: 19-of-31 4.8 GB: 20-of-31 4.8 GB: 21-of-31 5.0 GB: 22-of-31 4.8 GB: 23-of-31 4.8 GB: 24-of-31 4.8 GB: 25-of-31 5.0 GB: 26-of-31 4.8 GB: 27-of-31 4.8 GB: 28-of-31 4.8 GB: 29-of-31 3.2 GB: 30-of-31 2.5 GB: 31-of-31
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.46.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Gilgamesh 72B capabilities

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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 Gilgamesh 72B

Best Alternatives	Context / RAM	Downloads	Likes
EVA Qwen2.5 72B V0.2	128K / 146 GB	159	22
AceInstruct 72B	128K / 146 GB	88	18
...n2.5 72B 2x Instruct TIES V1.0	128K / 146.1 GB	76	1
...2B PT BR Instruct Experimental	128K / 146 GB	20	0
... BI Qwen2.5 72B PT BR Instruct	128K / 146 GB	5	0
...A Abliterated TIES Qwen2.5 72B	128K / 146.1 GB	8	1
72B Qwen2.5 Kunou V1	128K / 146 GB	77	26
EVA Qwen2.5 72B V0.1	128K / 146 GB	17	19
EVA Qwen2.5 72B V0.0	128K / 146 GB	10	5
Qwen2 72B Instruct	32K / 145.5 GB	61318	718

Note: green Score (e.g. "73.2") means that the model is better than rubenroy/Gilgamesh-72B.