What are the hardware requirements for ECE TW3 JRGL V5?

ECE TW3 JRGL V5 requires approximately 159.6 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 ECE TW3 JRGL V5 and how large is it?

ECE TW3 JRGL V5 is developed by paloalma, 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 ECE TW3 JRGL V5?

ECE TW3 JRGL V5 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

ECE TW3 JRGL V5 by paloalma — VRAM 159.6GB, 32K context

Name: ECE TW3 JRGL V5
Author: paloalma

ECE TW3 JRGL V5 is an open-source language model by paloalma. Features: 72b LLM, VRAM: 159.6GB, Context: 32K, License: apache-2.0, Merged, LLM Explorer Score: 0.23.

Merged Model Endpoints compatible Ibivibiv/alpaca-dragon-72b-v1 Llama Lora Moreh/momo-72b-lora-1.8.7-dpo Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/paloalma/ECE-TW3-JRGL-V5

ECE TW3 JRGL V5 Parameters and Internals

Additional Notes

This model is a "merge" type, specifically created using the MergeKit tool by combining two specified models: moreh/MoMo-72B-lora-1.8.7-DPO and ibivibiv/alpaca-dragon-72b-v1.

LLM Name	ECE TW3 JRGL V5
Repository 🤗	https://huggingface.co/paloalma/ECE-TW3-JRGL-V5
Merged Model	Yes
Model Size	72b
Required VRAM	159.6 GB
Updated	2026-08-04
Maintainer	paloalma
Model Type	llama
Model Files	5.0 GB: 1-of-82 3.8 GB: 2-of-82 3.5 GB: 3-of-82 3.8 GB: 4-of-82 3.5 GB: 5-of-82 3.5 GB: 6-of-82 3.5 GB: 7-of-82 3.8 GB: 8-of-82 3.2 GB: 9-of-82 3.5 GB: 10-of-82 3.5 GB: 11-of-82 3.8 GB: 12-of-82 3.2 GB: 13-of-82 3.5 GB: 14-of-82 3.5 GB: 15-of-82 3.8 GB: 16-of-82 3.2 GB: 17-of-82 3.5 GB: 18-of-82 3.5 GB: 19-of-82 3.8 GB: 20-of-82 3.2 GB: 21-of-82 3.5 GB: 22-of-82 3.5 GB: 23-of-82 3.8 GB: 24-of-82 3.2 GB: 25-of-82 3.5 GB: 26-of-82 3.5 GB: 27-of-82 3.8 GB: 28-of-82 3.2 GB: 29-of-82 3.5 GB: 30-of-82 3.5 GB: 31-of-82 3.8 GB: 32-of-82 3.2 GB: 33-of-82 3.5 GB: 34-of-82 3.5 GB: 35-of-82 3.8 GB: 36-of-82 3.2 GB: 37-of-82 3.5 GB: 38-of-82 3.5 GB: 39-of-82 3.8 GB: 40-of-82 3.2 GB: 41-of-82 3.5 GB: 42-of-82 3.5 GB: 43-of-82 3.8 GB: 44-of-82 3.2 GB: 45-of-82
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.39.3
Vocabulary Size	152064
LoRA Model	Yes
Torch Data Type	float32

Rank the ECE TW3 JRGL V5 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 ECE TW3 JRGL V5

Best Alternatives	Context / RAM	Downloads	Likes
2 Pro Math	128K / 141.9 GB	10	0
TW3 JRGL V2	32K / 79.7 GB	16209	0
Le Triomphant ECE TW3	32K / 79.7 GB	16266	5
Smaug 72B V0.1	32K / 144.5 GB	8736	468
MoMo 72B Lora 1.8.7 DPO	32K / 208.5 GB	314	68
Rhea 72B V0.5	32K / 144.5 GB	8194	134
JuliusCesar 72B BeyonderV.0	32K / 74.2 GB	77	0
Caigun Model 72B KGI	32K / 144.6 GB	31	0
Rhea 125 V0.5	32K / 249 GB	13	1
Exodius 70B	32K / 144.6 GB	8	0

Note: green Score (e.g. "73.2") means that the model is better than paloalma/ECE-TW3-JRGL-V5.