What are the hardware requirements for Llama 2 70B LoRA Assemble V2 GGUF?

Llama 2 70B LoRA Assemble V2 GGUF requires approximately 29.3 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama 2 70B LoRA Assemble V2 GGUF and how large is it?

Llama 2 70B LoRA Assemble V2 GGUF is developed by TheBloke, 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 Llama 2 70B LoRA Assemble V2 GGUF?

Llama 2 70B LoRA Assemble V2 GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 2 70B LoRA Assemble V2 GGUF by TheBloke — VRAM 29.3GB

Name: Llama 2 70B LoRA Assemble V2 GGUF
Author: TheBloke

Llama 2 70B LoRA Assemble V2 GGUF is an open-source language model by TheBloke. Features: 70b LLM, VRAM: 29.3GB, License: llama2, Quantized, LLM Explorer Score: 0.09.

Base model:oh-yeontaek/llama-2... Base model:quantized:oh-yeonta... Gguf Llama Lora Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/TheBloke/Llama-2-70B-LoRA-Assemble-v2-GGUF

Llama 2 70B LoRA Assemble V2 GGUF Benchmarks

LLME Score: 0.09294

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Llama 2 70B LoRA Assemble V2 GGUF (TheBloke/Llama-2-70B-LoRA-Assemble-v2-GGUF)

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Llama 2 70B LoRA Assemble V2 GGUF Parameters and Internals

Model Type

llama

Additional Notes

Quantized by TheBloke, uses GGUF format, various quantization methods available.

Input Output

Input Format:

{prompt}

LLM Name	Llama 2 70B LoRA Assemble V2 GGUF
Repository 🤗	https://huggingface.co/TheBloke/Llama-2-70B-LoRA-Assemble-v2-GGUF
Model Name	Llama 2 70B LoRA Assemble v2
Model Creator	oh-yeontaek
Base Model(s)	Llama 2 70B LoRA Assemble V2 oh-yeontaek/llama-2-70B-LoRA-assemble-v2
Model Size	70b
Required VRAM	29.3 GB
Updated	2026-05-05
Maintainer	TheBloke
Model Type	llama
Model Files	29.3 GB 36.1 GB 33.2 GB 29.9 GB 38.9 GB 41.4 GB 39.1 GB 47.5 GB 48.8 GB 47.5 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel
License	llama2
LoRA Model	Yes

Best Alternatives to Llama 2 70B LoRA Assemble V2 GGUF

Best Alternatives	Context / RAM	Downloads	Likes
...us Qwen3 R1 Llama Distill GGUF	0K / 0.8 GB	211	2
KafkaLM 70B German V0.1 GGUF	0K / 25.5 GB	2498	79
...gekit Passthrough Yqhuxcv GGUF	0K / 16.9 GB	24	0
CodeLlama 70B Instruct GGUF	0K / 25.5 GB	1490	63
CodeLlama 70B Python GGUF	0K / 25.5 GB	1298	45
Meta Llama 3 70B Instruct GGUF	0K / 26.4 GB	133	4
DAD Model V2 70B Q4	0K / 42.5 GB	14	0
CodeLlama 70B Hf GGUF	0K / 25.5 GB	484	42
Llama 2 70B Guanaco QLoRA GGUF	0K / 29.3 GB	12	0
Swallow 70B Instruct GGUF	0K / 29.4 GB	1539	9

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Llama-2-70B-LoRA-Assemble-v2-GGUF.

Rank the Llama 2 70B LoRA Assemble V2 GGUF Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Release v20260328a

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Llama 2 70B LoRA Assemble V2 GGUF by TheBloke

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Llama 2 70B LoRA Assemble V2 GGUF Benchmarks

Llama 2 70B LoRA Assemble V2 GGUF Parameters and Internals

Best Alternatives to Llama 2 70B LoRA Assemble V2 GGUF

Rank the Llama 2 70B LoRA Assemble V2 GGUF Capabilities

What open-source LLMs or SLMs are you in search of? 53834 in total.