---
title: 'LLaMA: Open and Efficient Foundation Language Models'
license: CC-BY-4.0
license_url: https://creativecommons.org/licenses/by/4.0/
license_note: 'paper is CC BY 4.0 (verified on arXiv abs page 2026-11-11; icon by-4.0.png, http://creativecommons.org/licenses/by/4.0/); note is our own summary'
source: https://iinventedlight.com/library/notes/2302-13971-llama.md
source_license: 'CC BY 4.0'
attribution: 'Summary by iinventedlight (AI-assisted). Source: Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, et al. (14 authors), LLaMA: Open and Efficient Foundation Language Models (CC BY 4.0).'
author: 'iinventedlight (AI-assisted)'
date: 2026-11-11
status: published
approved_by: "Cole Withington, 2026-11-11 20:58 PT, Grok Bot chat widget t1717s7407: \"Publish all 100 including the LLMs Encode Clinical Knowledge note\""
checked_on: 2026-11-11
as_of: 2026-11-11
confidence: medium
untested: 'Not reproduced. Abs page and HTML key sections read 2026-11-11. Named code URLs checked; code not run.'
category: arxiv
topic_area: 'ai-research: foundations'
tags: arxiv, foundations, language-models
arxiv_id: 2302.13971
alias: 2302.13971-llama
sources:
  - id: S1
    title: 'LLaMA: Open and Efficient Foundation Language Models'
    publisher: arXiv
    authors: 'Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, et al. (14 authors)'
    url: https://arxiv.org/abs/2302.13971
    version_read: 'v1 (27 Feb 2023)'
    accessed: 2026-11-11
    license: 'CC BY 4.0'
---
# LLaMA: Open and Efficient Foundation Language Models

## Summary
LLaMA is a collection of foundation language models ranging from 7B to 65B parameters, trained on publicly available datasets. In particular, LLaMA 13B outperforms GPT-3 (175B) on most benchmarks, and LLaMA 65B is competitive with the best models, Chinchilla 70B and PaLM 540B. They released the models to the research community. [S1]

## Claims
- id: C1
  claim: 'LLaMA is a collection of models ranging from 7B to 65B parameters.'
  source: S1
  evidence: "foundation language models ranging from 7B to 65B parameters"
- id: C2
  claim: 'They report that LLaMA-13B outperforms GPT-3 (175B) on most benchmarks.'
  source: S1
  evidence: "LLaMA-13B outperforms GPT-3 (175B) on most benchmarks"
- id: C3
  claim: 'They released the models to the research community.'
  source: S1
  evidence: "We release all our models to the research community"

## Verification
- Code available: Paper: https://github.com/facebookresearch/llama, which returned HTTP 200 and redirected to https://github.com/meta-llama/llama on 2026-11-11. Not run.
- Reproduced: not reproduced (2026-11-11). Code not run.
- Related work: Live notes 2401-04088-mixtral-of-experts and 2210-11416-flan-instruction-finetuning. This is the paper-verification note for LLaMA itself.
- Limits: No dedicated Limitations section was found in the HTML. The paper presents pretrained base models trained on public data and does not itself report instruction-tuning results.
- License: CC BY 4.0 on the abs page (2026-11-11; icon by-4.0.png; http://creativecommons.org/licenses/by/4.0/). Submitted 27 Feb 2023 (v1). Sources: [S1] https://arxiv.org/abs/2302.13971, v1 (27 Feb 2023). checked_on: 2026-11-11.

## When to apply
Use when comparing early openly released foundation models, or when tracing later Llama-family work back to the original 7B-to-65B release.

## Facts
- id: F1
  claim: 'LLaMA is a collection of foundation language models ranging from 7B to 65B parameters.'
  confidence: medium
  date: 2026-11-11
  sources: [S1]
  license: CC BY 4.0
- id: F2
  claim: 'The authors report that LLaMA-13B outperforms GPT-3 (175B) on most benchmarks.'
  confidence: medium
  date: 2026-11-11
  sources: [S1]
  license: CC BY 4.0
- id: F3
  claim: 'They report that LLaMA-65B is competitive with Chinchilla-70B and PaLM-540B.'
  confidence: medium
  date: 2026-11-11
  sources: [S1]
  license: CC BY 4.0

## Sources
- [S1] arXiv 2302.13971, https://arxiv.org/abs/2302.13971. License: CC BY 4.0. v1 (27 Feb 2023). Accessed 2026-11-11.

License: this note is CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Summary by iinventedlight (AI-assisted). Paper is CC BY 4.0.

---

Agents: [/agents.md](/agents.md) | [/.well-known/agent-library.json](/.well-known/agent-library.json).