What are the hardware requirements for Platypus2 70B Instruct AWQ?

Platypus2 70B Instruct AWQ requires approximately 36.6 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Platypus2 70B Instruct AWQ and how large is it?

Platypus2 70B Instruct AWQ 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 Platypus2 70B Instruct AWQ?

Platypus2 70B Instruct AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Platypus2 70B Instruct AWQ by TheBloke — VRAM 36.6GB, 4K context

Name: Platypus2 70B Instruct AWQ
Author: TheBloke

Platypus2 70B Instruct AWQ is an open-source language model by TheBloke. Features: 70b LLM, VRAM: 36.6GB, Context: 4K, License: cc-by-nc-4.0, Quantized, Instruction-Based, LLM Explorer Score: 0.09.

Arxiv:2307.09288 Arxiv:2308.07317 4-bit Awq Base model:garage-baind/platyp... Base model:quantized:garage-ba... Dataset:garage-baind/open-plat... Dataset:open-orca/openorca En Instruct Llama Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/TheBloke/Platypus2-70B-Instruct-AWQ

Platypus2 70B Instruct AWQ Parameters and Internals

Model Type

auto-regressive language model

Additional Notes

AWQ is supported for faster inference with smaller GPUs.

Supported Languages

English (fluent)

Training Details

Data Sources:

garage-bAInd/Open-Platypus, Open-Orca/OpenOrca

Methodology:

instruction fine-tuned using LoRA on 8 A100 80GB.

Hardware Used:

8 A100 80GB GPUs

Model Architecture:

LLaMA 2 transformer architecture

Input Output

Input Format:

Below is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction: {prompt} ### Response:

Accepted Modalities:

text

Output Format:

text

LLM Name	Platypus2 70B Instruct AWQ
Repository 🤗	https://huggingface.co/TheBloke/Platypus2-70B-Instruct-AWQ
Model Name	Platypus2 70B Instruct
Model Creator	garage-bAInd
Base Model(s)	Platypus2 70B Instruct garage-bAInd/Platypus2-70B-instruct
Model Size	70b
Required VRAM	36.6 GB
Updated	2026-07-27
Maintainer	TheBloke
Model Type	llama
Instruction-Based	Yes
Model Files	9.9 GB: 1-of-4 9.9 GB: 2-of-4 9.9 GB: 3-of-4 6.9 GB: 4-of-4
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	LlamaForCausalLM
License	cc-by-nc-4.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.31.0
Tokenizer Class	LlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	32000
Torch Data Type	float16

Rank the Platypus2 70B Instruct AWQ 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 Platypus2 70B Instruct AWQ

Best Alternatives	Context / RAM	Downloads	Likes
...0B Instruct Gradient 1048K AWQ	1024K / 39.9 GB	5	1
...70B Instruct Gradient 262K AWQ	256K / 39.9 GB	5	0
Llama 3.3 70B Instruct AWQ	128K / 39.9 GB	262002	46
...lama 3.3 70B Instruct AWQ INT4	128K / 39.9 GB	82744	30
Llama 3.3 70B Instruct AWQ	128K / 39.9 GB	16090	12
... SauerkrautLM 70B Instruct AWQ	128K / 39.9 GB	5	5
Llama 3 70B Instruct AWQ	8K / 39.9 GB	122175	71
Meta Llama 3 70B Instruct AWQ	8K / 39.9 GB	8	1
Llama 3 70B Instruct AWQ	8K / 39.9 GB	17	1
... Llama 3 70B Instruct AWQ GEMM	8K / 39.9 GB	6	0

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Platypus2-70B-Instruct-AWQ.