What are the hardware requirements for Mithril Base LLaMa 70B?

Mithril Base LLaMa 70B requires approximately 141.9 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mithril Base LLaMa 70B and how large is it?

Mithril Base LLaMa 70B is developed by TareksLab, a model with 70b 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 Mithril Base LLaMa 70B?

Mithril Base LLaMa 70B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mithril Base LLaMa 70B by TareksLab — VRAM 141.9GB, 128K context

Name: Mithril Base LLaMa 70B
Author: TareksLab

Mithril Base LLaMa 70B is an open-source language model by TareksLab. Features: 70b LLM, VRAM: 141.9GB, Context: 128K, Merged, LLM Explorer Score: 0.2.

Merged Model Arxiv:2311.03099 Base model:abacusai/dracarys2-... Base model:doctor-shotgun/l3.3... Base model:nbeerbower/llama-3.... Base model:ppoyaa/mythonemo-l3... Base model:shisa-ai/shisa-v2-l... Conversational Endpoints compatible Llama Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/TareksLab/Mithril-Base-LLaMa-70B

Mithril Base LLaMa 70B Parameters and Internals

LLM Name	Mithril Base LLaMa 70B
Repository 🤗	https://huggingface.co/TareksLab/Mithril-Base-LLaMa-70B
Base Model(s)	nbeerbower/Llama-3.1-Nemotron-lorablated-70B abacusai/Dracarys2-Llama-3.1-70B-Instruct Ppoyaa/MythoNemo-L3.1-70B-v1.0 shisa-ai/shisa-v2-llama3.3-70b Doctor-Shotgun/L3.3-70B-Magnum-Diamond nbeerbower/Llama-3.1-Nemotron-lorablated-70B abacusai/Dracarys2-Llama-3.1-70B-Instruct Ppoyaa/MythoNemo-L3.1-70B-v1.0 shisa-ai/shisa-v2-llama3.3-70b Doctor-Shotgun/L3.3-70B-Magnum-Diamond
Merged Model	Yes
Model Size	70b
Required VRAM	141.9 GB
Updated	2026-08-01
Maintainer	TareksLab
Model Type	llama
Model Files	4.7 GB: 1-of-30 4.7 GB: 2-of-30 5.0 GB: 3-of-30 5.0 GB: 4-of-30 4.7 GB: 5-of-30 4.7 GB: 6-of-30 4.7 GB: 7-of-30 5.0 GB: 8-of-30 5.0 GB: 9-of-30 4.7 GB: 10-of-30 4.7 GB: 11-of-30 4.7 GB: 12-of-30 5.0 GB: 13-of-30 5.0 GB: 14-of-30 4.7 GB: 15-of-30 4.7 GB: 16-of-30 4.7 GB: 17-of-30 5.0 GB: 18-of-30 5.0 GB: 19-of-30 4.7 GB: 20-of-30 4.7 GB: 21-of-30 4.7 GB: 22-of-30 5.0 GB: 23-of-30 5.0 GB: 24-of-30 4.7 GB: 25-of-30 4.7 GB: 26-of-30 4.7 GB: 27-of-30 5.0 GB: 28-of-30 5.0 GB: 29-of-30 2.0 GB: 30-of-30
Model Architecture	LlamaForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.55.4
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	128256
Torch Data Type	bfloat16

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