What are the hardware requirements for Llama 3 70B Instruct Abliterated?

Llama 3 70B Instruct Abliterated requires approximately 141.9 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama 3 70B Instruct Abliterated and how large is it?

Llama 3 70B Instruct Abliterated is developed by failspy, a model with 70b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Llama 3 70B Instruct Abliterated perform on standard benchmarks?

Llama 3 70B Instruct Abliterated has the following published scores: MMLU 79.8. Compare against reference models on this page or on the LLM Explorer leaderboards.

Llama 3 70B Instruct Abliterated by failspy — VRAM 141.9GB, 8K context

Name: Llama 3 70B Instruct Abliterated
Rating: 1 (1 reviews)
Author: failspy

Llama 3 70B Instruct Abliterated is an open-source language model by failspy. Features: 70b LLM, VRAM: 141.9GB, Context: 8K, License: llama3, Instruction-Based, LLM Explorer Score: 0.27, Arc: 71.8, HellaSwag: 86, MMLU: 79.8, GSM8K: 85.2.

Conversational Endpoints compatible Instruct Llama Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/failspy/llama-3-70B-Instruct-abliterated

Llama 3 70B Instruct Abliterated Parameters and Internals

Model Type

text generation

Additional Notes

This model has had certain weights manipulated to "inhibit" the model's ability to express refusal. It is not guaranteed to never refuse a request and may still express ethical/safety considerations.

LLM Name	Llama 3 70B Instruct Abliterated
Repository 🤗	https://huggingface.co/failspy/llama-3-70B-Instruct-abliterated
Model Size	70b
Required VRAM	141.9 GB
Updated	2026-08-03
Maintainer	failspy
Model Type	llama
Instruction-Based	Yes
Model Files	4.6 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 2.1 GB: 30-of-30
Model Architecture	LlamaForCausalLM
License	llama3
Context Length	8192
Model Max Length	8192
Transformers Version	4.40.1
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the Llama 3 70B Instruct Abliterated 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

Best Alternatives to Llama 3 70B Instruct Abliterated

Best Alternatives	Context / RAM	Downloads	Likes
... Chat 1048K Chinese Llama3 70B	1024K / 141.9 GB	9069	5
... Chat 1048K Chinese Llama3 70B	1024K / 141.9 GB	7684	4
... 3 70B Instruct Gradient 1048K	1024K / 141.9 GB	22	122
Llama3 Function Calling 1048K	1024K / 141.9 GB	5	1
...a 3 70B Instruct Gradient 524K	512K / 141.9 GB	24	23
...a 3 70B Instruct Gradient 262K	256K / 141.9 GB	20	56
...ama 3 70B Arimas Story RP V2.0	256K / 141.1 GB	10	3
...ama 3 70B Arimas Story RP V1.6	256K / 141.2 GB	5	0
...ama 3 70B Arimas Story RP V1.5	256K / 141.2 GB	21	3
Llama 3.1 70B Instruct	128K / 141.9 GB	813492	938

Note: green Score (e.g. "73.2") means that the model is better than failspy/llama-3-70B-Instruct-abliterated.