What are the hardware requirements for Meta Llama 3 70B Instruct Ov Int4?

Meta Llama 3 70B Instruct Ov Int4 requires approximately 44.3 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 Meta Llama 3 70B Instruct Ov Int4 and how large is it?

Meta Llama 3 70B Instruct Ov Int4 is developed by fakezeta, 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 Meta Llama 3 70B Instruct Ov Int4?

Meta Llama 3 70B Instruct Ov Int4 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Meta Llama 3 70B Instruct Ov Int4 by fakezeta — VRAM 44.3GB, 8K context

Name: Meta Llama 3 70B Instruct Ov Int4
Author: fakezeta

Meta Llama 3 70B Instruct Ov Int4 is an open-source language model by fakezeta. Features: 70b LLM, VRAM: 44.3GB, Context: 8K, License: other, Instruction-Based, LLM Explorer Score: 0.12.

Conversational En Endpoints compatible Facebook Instruct Llama Llama-3 Meta Openvino Pytorch Region:us

Model Card on HF 🤗: https://huggingface.co/fakezeta/Meta-Llama-3-70B-Instruct-ov-int4

Meta Llama 3 70B Instruct Ov Int4 Parameters and Internals

Model Type

text generation, instruction tuned

Use Cases

Areas:

commercial, research

Applications:

assistant-like chat (instruction tuned), natural language generation tasks (pre-trained)

Primary Use Cases:

dialogue, text and code generation

Limitations:

Use violating laws or regulations not allowed, English-only pretraining testing

Considerations:

Users may fine-tune for other languages under the license.

Additional Notes

Implemented safety and misuse mitigations; allows model fine-tuning for uses beyond initial capabilities under license conditions.

Supported Languages

English (Full support)

Training Details

Data Sources:

publicly available online data

Data Volume:

15T+ tokens

Methodology:

auto-regressive with optimized transformer architecture, RLHF

Context Length:

8192

Hardware Used:

Meta's Research SuperCluster, H100-80GB GPUs

Model Architecture:

Transformer

Safety Evaluation

Methodologies:

red teaming, adversarial evaluations

Findings:

Model was extensively tested to lower residual risks

Risk Categories:

CBRNE, cybersecurity, child safety

Ethical Considerations:

misuse mitigation measures in place.

Responsible Ai Considerations

Mitigation Strategies:

Implement safeguards like Llama Guard and Code Shield.

Input Output

Input Format:

text input only

Accepted Modalities:

text

Output Format:

text and code

LLM Name	Meta Llama 3 70B Instruct Ov Int4
Repository 🤗	https://huggingface.co/fakezeta/Meta-Llama-3-70B-Instruct-ov-int4
Model Size	70b
Required VRAM	44.3 GB
Updated	2026-08-07
Maintainer	fakezeta
Model Type	llama
Instruction-Based	Yes
Model Files	44.3 GB
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	other
Context Length	8192
Model Max Length	8192
Transformers Version	4.40.1
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	128256

Rank the Meta Llama 3 70B Instruct Ov Int4 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

Quantized Models of the Meta Llama 3 70B Instruct Ov Int4

Model	Likes	Downloads	VRAM
...ta Llama 3 70B Instruct Marlin	6	141	39 GB
...Llama 3 70B Instruct GPTQ Int8	2	32	74 GB
...Llama 3 70B Instruct GPTQ Int4	6	19	39 GB

Best Alternatives to Meta Llama 3 70B Instruct Ov Int4

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 fakezeta/Meta-Llama-3-70B-Instruct-ov-int4.