• Llama models are approaching 350 million downloads to date (more than 10x the downloads compared to this time last year), and they were downloaded more than 20 million times in the last month alone, making Llama the leading open source model family.
  迄今为止，Llama 模型的下载量接近 3.5 亿次（是去年同期下载量的 10 倍以上），仅在上个月，它们的下载量就超过 2000 万次，使 Llama 成为领先的开源模型系列。
• Llama usage by token volume across our major cloud service provider partners has more than doubled in just three months from May through July 2024 when we released Llama 3.1.
  从 2024 年 5 月到 2024 年 7 月我们发布 Llama 3.1 的短短三个月内，我们主要云服务提供商合作伙伴的令牌量 Llama 使用量就增加了一倍多。
• Monthly usage (token volume) of Llama grew 10x from January to July 2024 for some of our largest cloud service providers.
  从 2024 年 1 月到 7 月，我们一些最大的云服务提供商的 Llama 的月使用量（代币量）增长了 10 倍。

It’s been just over a month since we released Llama 3.1, expanding context length to 128K, adding support across eight languages, and introducing the first frontier-level open source AI model with our Llama 3.1 405B. As we did with our Llama 3 and Llama 2 releases, today we’re sharing an update on the momentum and adoption we’re seeing across the board.
距离我们发布 Llama 3.1 已经一个多月了，它将上下文长度扩展到 128K，增加了对八种语言的支持，并在我们的 Llama 3.1 405B 中引入了第一个前沿级开源 AI 模型。正如我们对 Llama 3 和 Llama 2 版本所做的那样，今天我们将分享我们看到的全面发展势头和采用情况的最新情况。

The success of Llama is made possible through the power of open source. By making our Llama models openly available we’ve seen a vibrant and diverse AI ecosystem come to life where developers have more choice and capability than ever before. The innovation has been broad and rapid, from start-ups pushing new boundaries to enterprises of all sizes using Llama to build on-premises or through a cloud service provider. Industry is building and innovating with Llama, and we’re even more excited for what’s to come.
Llama 的成功是通过开源的力量实现的。通过公开提供我们的 Llama 模型，我们看到了一个充满活力和多样化的 AI 生态系统，开发人员拥有比以往更多的选择和能力。从突破新界限的初创公司到各种规模的企业使用 Llama 在本地或通过云服务提供商进行构建，创新是广泛而迅速的。工业界正在与 Llama 一起建设和创新，我们对即将发生的事情更加兴奋。

Alongside the release of Llama 3.1, Mark Zuckerberg shared an open letter on the benefits of open source AI—further cementing our vision and commitment to an open approach. Open source is in our company’s DNA, and Llama both embodies and reinforces our commitment to sharing our work in a responsible way. Open source promotes a more competitive ecosystem that’s good for consumers, good for companies (including Meta), and ultimately good for the world.
在 Llama 3.1 发布的同时，Mark Zuckerberg 分享了一封关于开源 AI 优势的公开信，进一步巩固了我们对开放方法的愿景和承诺。开源是我们公司的 DNA，Llama 既体现又加强了我们以负责任的方式分享工作的承诺。开源促进了一个更具竞争力的生态系统，这对消费者、公司（包括 Meta）都有好处，并最终对世界有好处。

In just 18 months since our initial launch, Llama has evolved from a single state-of-the-art foundation model to a robust system for developers. With Llama 3.1, we now offer developers a complete reference system to more easily create their own custom agents along with a new set of security and safety tools to help build responsibly.
自首次发布以来，在短短 18 个月内，Llama 已从单一的最先进的基础模型发展成为面向开发人员的强大系统。在 Llama 3.1 中，我们现在为开发人员提供了一个完整的参考系统，以便更轻松地创建自己的自定义代理，以及一组新的安全工具，以帮助负责任地构建。

The Llama ecosystem is growing rapidly. Llama models are approaching 350 million downloads on Hugging Face to date—an over 10x increase from where we were about a year ago. Llama models were downloaded more than 20 million times on Hugging Face in the last month alone. And this is just one piece of the Llama success story with these models also being downloaded on services from our partners across the industry.
Llama 生态系统正在迅速发展。迄今为止，美洲驼模型在 Hugging Face 上的下载量接近 3.5 亿次，比大约一年前增长了 10 倍以上。仅在上个月，美洲驼模型在 Hugging Face 上的下载量就超过 2000 万次。这只是 Llama 成功故事的一部分，这些模型还可以在我们整个行业合作伙伴的服务中下载。

In addition to Amazon Web Services (AWS) and Microsoft’s Azure, we’ve partnered with Databricks, Dell, Google Cloud, Groq, NVIDIA, IBM watsonx, Scale AI, Snowflake, and others to better help developers unlock the full potential of our models. Hosted Llama usage by token volume across our major cloud service provider partners more than doubled May through July 2024 when we released Llama 3.1.
除了 Amazon Web Services （AWS） 和 Microsoft 的 Azure，我们还与 Databricks、Dell、Google Cloud、Groq、NVIDIA、IBM watsonx、Scale AI、Snowflake 等合作，以更好地帮助开发人员释放我们模型的全部潜力。截至 2024 年 7 月，当我们发布 Llama 3.1 时，我们主要云服务提供商合作伙伴的托管 Llama 使用量（按令牌量计算）增加了一倍多。

Monthly usage of Llama grew 10x from January to July 2024 for some of our largest cloud service providers. And in the month of August, the highest number of unique users of Llama 3.1 on one of our major cloud service provider partners was the 405B variant, which shows that our largest foundation model is gaining traction.
从 2024 年 1 月到 7 月，我们一些最大的云服务提供商的 Llama 月使用量增长了 10 倍。在 8 月份，我们的主要云服务提供商合作伙伴之一的 Llama 3.1 独立用户数量最多的是 405B 变体，这表明我们最大的基础模型正在获得关注。

We’ve grown the number of partners in our Llama early access program by 5x with Llama 3.1 and will do more to meet the surging demand from partners. We’ve heard from a number of companies that want to be future LEAP and integration Llama partners, including Wipro, Cerebras, and Lambda.
在 Llama 3.1 中，我们已将 Llama 早期访问计划的合作伙伴数量增加了 5 倍，并将采取更多措施来满足合作伙伴不断增长的需求。我们从许多公司那里听说，他们希望成为未来的 LEAP 和集成 Llama 合作伙伴，包括 Wipro、Cerebras 和 Lambda。

Swami Sivasubramanian, VP, AI and Data, AWS: “Customers want access to the latest state-of-the-art models for building AI applications in the cloud, which is why we were the first to offer Llama 2 as a managed API and have continued to work closely with Meta as they released new models. We’ve been excited to see the uptake for Llama 3.1 from customers across both Amazon SageMaker and Amazon Bedrock, and we look forward to seeing how customers use this model to solve their most complex use cases.”
AWS AI 和数据副总裁 Swami Sivasubramanian：“客户希望访问最新的先进模型，以便在云中构建 AI 应用程序，这就是为什么我们是第一个将 Llama 2 作为托管 API 提供的公司，并在 Meta 发布新模型时继续与他们密切合作。我们很高兴看到 Amazon SageMaker 和 Amazon Bedrock 上的客户对 Llama 3.1 的采用，我们期待看到客户如何使用此模型来解决他们最复杂的使用案例。

Ali Ghodsi, CEO & Co-Founder, Databricks: “In the weeks since launch, thousands of Databricks customers have adopted Llama 3.1, making it our fastest adopted and best selling open source model ever. This generation of Llama models finally bridges the gap between OSS and commercial models on quality. Llama 3.1 is a breakthrough for customers wanting to build high quality AI applications, while retaining full control, customizability, and portability over their base LLM.”
阿里·戈德西，Databricks的首席执行官兼联合创始人：“自发布以来的几周内，成千上万的Databricks客户已经采用了Llama 3.1，使其成为我们有史以来最快采用和最畅销的开源模型。这一代 Llama 模型最终弥合了 OSS 和商业模型在质量上的差距。对于希望构建高质量 AI 应用程序的客户来说，Llama 3.1 是一个突破，同时保留了对其基础LLM的完全控制、可定制性和可移植性。

Jonathan Ross, Founder & CEO, Groq: “Open-source wins. Meta is building the foundation of an open ecosystem that rivals the top closed models and at Groq we put them directly into the hands of the developers—a shared value that’s been fundamental at Groq since our beginning. To date Groq has provided over 400,000 developers with 5 billion free tokens daily, using the Llama suite of models and our LPU Inference. It’s a very exciting time and we’re proud to be a part of that momentum. We can’t add capacity fast enough for Llama. If we 10x’d the deployed capacity it would be consumed in under 36 hours.”
乔纳森·罗斯，Groq的创始人兼首席执行官：“开源赢了。Meta 正在构建一个开放生态系统的基础，该生态系统可与顶级封闭模型相媲美，在 Groq，我们将它们直接交到开发人员手中——这一共同价值观自 Groq 成立以来就一直是 Groq 的基础。迄今为止，Groq 已使用 Llama 模型套件和我们的 LPU 推理，每天为超过 400,000 名开发人员提供 50 亿个免费代币。这是一个非常激动人心的时刻，我们很自豪能成为这一势头的一部分。我们无法以足够快的速度为 Llama 增加容量。如果我们将部署的容量增加 10 倍，它将在 36 小时内用完。

Jensen Huang, Founder & CEO of NVIDIA: “Llama has profoundly impacted the advancement of state-of-the-art AI. The floodgates are now open for every enterprise and industry to build and deploy custom Llama supermodels using NVIDIA AI Foundry, which offers the broadest support for Llama 3.1 models across training, optimization, and inference. It’s incredible to witness the rapid pace of adoption in just the past month.”

What's even more encouraging than how many people are using Llama is who is using Llama and how they’re using Llama.

We’re seeing growing preference in the developer community for Llama and strong indicators for continued growth. According to a survey from Artificial Analysis, an independent site for AI benchmarking, Llama was the number two most considered model and the industry leader in open source.

With more than 60,000 derivative models on Hugging Face, there’s a vibrant community of developers fine-tuning Llama for their own use cases. Large enterprises like AT&T, DoorDash, Goldman Sachs, Niantic, Nomura, Shopify, Spotify, and Zoom are just a few success stories, and both Infosys and KPMG are using Llama internally.

Let’s take a closer look.

Accenture is using Llama 3.1 to build a custom LLM for ESG reporting that they expect to improve productivity by 70% and quality by 20 – 30%, compared with the company’s existing way of generating Accenture’s annual ESG report. With its exciting advancements in multilingual capabilities, Accenture is able to extend AI models across regions, for example to help a global organization make chatbots more culturally conscious and relevant. Accenture believes companies will need to leverage many different AI models from different providers. Open source models like Llama 3.1 expand options, accelerate innovation, and will have a positive ripple effect across business and society.

Customer care is an area of focus for AI-powered innovation at AT&T. Through fine-tuning Llama models, they’ve been able to cost effectively improve customer care by better understanding key trends, needs and opportunities to enhance the experience moving forward. Overall, Llama and GenAI have driven a nearly 33% improvement in search-related responses for AT&T customer care engagements while reducing costs and speeding up response times.

DoorDash uses Llama to streamline and accelerate daily tasks for its software engineers, such as leveraging its internal knowledge base to answer complex questions for the team and delivering actionable pull request reviews to improve its codebase.

Goldman Sachs AI platform, known as the GS AI Platform, allows Goldman engineers to use Llama models for various use cases in a safe and responsible way, including information extraction from documents.

To drive the virtual world of its first-of-its-kind AR game Peridot, Niantic integrated Llama, transforming its adorable creatures, called “Dots,” into responsive AR pets that now exhibit smart behaviors to simulate the unpredictable nature of physical animals. Llama generates each Dot’s reaction in real time, making every interaction dynamic and unique.

Leading Japanese financial institution Nomura uses Llama on AWS for key benefits, including faster innovation, transparency, bias guardrails, and robust performance across text summarization, code generation, log analysis, and document processing.

Shopify is continuing to experiment with best-in-class open source models, including LLaVA, which is built on the foundations of Llama. They use finetunes of LLaVA for multiple specialized tasks and are currently doing 40M – 60M Llava inferences per day supporting the company’s work on product metadata and enrichment.

Zoom uses its own models as well as closed- and open-source LLMs—including Llama—to power its AI Companion, a generative AI assistant that helps workers avoid repetitive, mundane tasks. AI Companion serves up meeting summaries, smart recordings, and next steps to Zoom users, freeing up more of their time to collaborate, make connections, and get things done.

Llama is leading the way on openness, modifiability, and cost efficiency. We’re committed to building in the open and helping ensure that the benefits of AI extend to everyone. And a growing number of academics and entrepreneurs alike agree that open source AI is the right path forward.

LLMs can help us answer tough questions, improve our productivity, and spark our creativity. As the Llama ecosystem expands, so, too, do the capabilities and accessibility of Meta AI. Our smart assistant is available across Instagram, WhatsApp, Messenger, and Facebook, as well as via the web. We’ve also brought it to Meta Quest and the Ray-Ban Meta collection—bringing us a step closer to our vision of a future where an always-available contextual AI assistant in a convenient, wearable form factor will proactively help you as you go about your day.

We’re excited by the growth of the Llama community and encouraged knowing we're building the most advanced large language models, open sourced for the world today. Stay tuned to the blog in the weeks and months ahead as we continue spotlighting all the incredible ways developers and companies are finding value with Llama.

Thanks to the developers building with Llama. As always, we’re listening to your feedback, and we’ll have many more updates to share soon.

New to Llama? Download the latest models and start building today.