What are the hardware requirements for Llama 2 13B Chat Hf?

Llama 2 13B Chat Hf requires approximately 26 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 Llama 2 13B Chat Hf and how large is it?

Llama 2 13B Chat Hf is developed by meta-llama, a model with 13b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Llama 2 13B Chat Hf perform on standard benchmarks?

Llama 2 13B Chat Hf has the following published scores: MMLU 54.64, LMSYS ELO 1078. Compare against reference models on this page or on the LLM Explorer leaderboards.

Llama 2 13B Chat Hf by meta-llama — VRAM 26GB, 4K context

Name: Llama 2 13B Chat Hf
Author: meta-llama

Llama 2 13B Chat Hf is an open-source language model by meta-llama. Features: 13b LLM, VRAM: 26GB, Context: 4K, License: llama2, LLM Explorer Score: 0.34, ELO: 1078, Arc: 59, HellaSwag: 81.9, MMLU: 54.6, GSM8K: 15.2.

Arxiv:2307.09288 Conversational En Endpoints compatible Facebook Llama Llama2 Meta Pytorch Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/meta-llama/Llama-2-13b-chat-hf

Llama 2 13B Chat Hf Benchmarks

LMSys ELO: 1078 vs 1272 (so35)^-15.3%

LLME Score: 0.34365

^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 13B Chat Hf (meta-llama/Llama-2-13b-chat-hf)

Llama 2 13B Chat Hf Parameters and Internals

Model Type

text generation

Use Cases

Areas:

commercial, research

Primary Use Cases:

assistant-like chat, natural language generation tasks

Limitations:

Use in languages other than English, Violations of laws or regulations

Considerations:

Follow specific formatting for inputs

Additional Notes

The fine-tuning data includes publicly available instruction datasets and human-annotated examples.

Training Details

Data Sources:

publicly available datasets

Data Volume:

2 trillion tokens

Methodology:

Supervised Fine-tuning and Reinforcement Learning with Human Feedback

Hardware Used:

Meta's Research Super Cluster, third-party cloud compute

Model Architecture:

auto-regressive language model with optimized transformer architecture

Input Output

Input Format:

Text

Accepted Modalities:

text

Output Format:

Text

Release Notes

Version:

Date:

July 2023

Notes:

Llama 2 models ranging from 7 billion to 70 billion parameters released, optimized for dialogue and alignment with human preferences.

LLM Name	Llama 2 13B Chat Hf
Repository 🤗	https://huggingface.co/meta-llama/Llama-2-13b-chat-hf
Model Size	13b
Required VRAM	26 GB
Updated	2026-07-18
Maintainer	meta-llama
Model Type	llama
Model Files	9.9 GB: 1-of-3 9.9 GB: 2-of-3 6.2 GB: 3-of-3 9.9 GB: 1-of-3 9.9 GB: 2-of-3 6.2 GB: 3-of-3
Supported Languages	en
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

Quantized Models of the Llama 2 13B Chat Hf

Model	Likes	Downloads	VRAM
Luminia 13B V3	6	104	26 GB
Llama 2 13B Chat GGUF	204	6596	5 GB
Llama 2 13B Chat GGML	693	148	5 GB
Llama 2 13B Chat GPTQ	362	712	7 GB
Llama 2 13B Chat AWQ	26	293	7 GB

Best Alternatives to Llama 2 13B Chat Hf

Best Alternatives	Context / RAM	Downloads	Likes
Luminaura RP 13B	128K / 26 GB	9	1
Yarn Llama 2 13B 128K	128K / 26 GB	206	113
Agent Llama2 13B 80K	80K / 26.4 GB	5	0
Chat Llama2 13B 80K	80K / 52.8 GB	5	0
LongAlign 13B 64K	64K / 26 GB	97	13
LongAlign 13B 64K Base	64K / 26 GB	74	3
LongAlign 13B 64K	64K / 26 GB	11	13
LongAlign 13B 64K Base	64K / 26 GB	6	3
Openbuddy Llama2 13B V15p1 64K	64K / 26.1 GB	5	4
Openbuddy Llama2 13b64k V15	64K / 26.1 GB	12	2

Rank the Llama 2 13B Chat Hf 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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Llama 2 13B Chat Hf by meta-llama