What are the hardware requirements for Llama2 70B Chat 4bit AWQ?

Llama2 70B Chat 4bit 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 Llama2 70B Chat 4bit AWQ and how large is it?

Llama2 70B Chat 4bit AWQ is developed by jamesdborin, 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 Llama2 70B Chat 4bit AWQ?

Llama2 70B Chat 4bit AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama2 70B Chat 4bit AWQ by jamesdborin — VRAM 36.6GB, 4K context

Name: Llama2 70B Chat 4bit AWQ
Author: jamesdborin

Llama2 70B Chat 4bit AWQ is an open-source language model by jamesdborin. Features: 70b LLM, VRAM: 36.6GB, Context: 4K, License: llama2, Quantized, LLM Explorer Score: 0.1.

Arxiv:2307.09288 4-bit 4bit Awq Base model:meta-llama/llama-2-... Base model:quantized:meta-llam... En Facebook Llama Llama2 Meta Pytorch Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/jamesdborin/llama2-70b-chat-4bit-AWQ

Llama2 70B Chat 4bit AWQ Parameters and Internals

Model Type

llama

Use Cases

Areas:

Commercial, Research

Primary Use Cases:

Dialogue optimization, Assistant-like chat features

Limitations:

Use in non-English languages, Inaccurate or objectionable responses

Additional Notes

Optimized for dialogue use cases and converted for Hugging Face Transformers format.

Training Details

Data Volume:

2.0T

Methodology:

Supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF)

Context Length:

4000

Training Time:

1720320 GPU hours

Hardware Used:

A100-80GB GPUs

Model Architecture:

Auto-regressive transformer model with Grouped-Query Attention (GQA)

LLM Name	Llama2 70B Chat 4bit AWQ
Repository 🤗	https://huggingface.co/jamesdborin/llama2-70b-chat-4bit-AWQ
Model Name	Llama 2 70B Chat
Model Creator	Meta Llama 2
Base Model(s)	Llama 2 70B Chat Hf meta-llama/Llama-2-70b-chat-hf
Model Size	70b
Required VRAM	36.6 GB
Updated	2026-07-19
Maintainer	jamesdborin
Model Type	llama
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\|4bit
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	4096
Model Max Length	4096
Transformers Version	4.31.0.dev0
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 Llama2 70B Chat 4bit AWQ 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 Llama2 70B Chat 4bit 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
MultiVerse 70B AWQ	32K / 41.3 GB	70	2
Opus V1.2 70B AWQ	32K / 36.7 GB	9	1
QuartetAnemoi 70B T0.0001 AWQ	31K / 36.7 GB	3	1
Senku 70B AWQ 4bit GEMM	31K / 36.7 GB	2	1

Note: green Score (e.g. "73.2") means that the model is better than jamesdborin/llama2-70b-chat-4bit-AWQ.