Audience
Developers interested in a powerful free and open source large language model
About Llama 2
The next generation of our open source large language model. This release includes model weights and starting code for pretrained and fine-tuned Llama language models — ranging from 7B to 70B parameters.
Llama 2 pretrained models are trained on 2 trillion tokens, and have double the context length than Llama 1. Its fine-tuned models have been trained on over 1 million human annotations.
Llama 2 outperforms other open source language models on many external benchmarks, including reasoning, coding, proficiency, and knowledge tests.
Llama 2 was pretrained on publicly available online data sources. The fine-tuned model, Llama-2-chat, leverages publicly available instruction datasets and over 1 million human annotations.
We have a broad range of supporters around the world who believe in our open approach to today’s AI — companies that have given early feedback and are excited to build with Llama 2.
Other Popular Alternatives & Related Software
Inkling
Inkling is an open-weights multimodal AI model from Thinking Machines designed as a customizable foundation model for developers, researchers, and enterprises. The model is a Mixture-of-Experts transformer with 975 billion total parameters, 41 billion active parameters, and support for context windows up to 1 million tokens. Inkling was trained from scratch on text, images, audio, and video, giving it native capabilities across reasoning, coding, agentic tool use, vision, audio, factuality, and instruction following. It is built with controllable thinking effort so users can balance performance, latency, and token efficiency for different workloads. The model is available for fine-tuning on Tinker, with playground access, API availability through ecosystem partners, and full weights published on Hugging Face. Built for customization, Inkling gives teams an open-weights base model for building domain-specific AI systems, multimodal agents, coding workflows, research tools, and more.
Learn more about Inkling
ChatGLM
ChatGLM-6B is an open-source, Chinese-English bilingual dialogue language model based on the General Language Model (GLM) architecture with 6.2 billion parameters. Combined with model quantization technology, users can deploy locally on consumer-grade graphics cards (only 6GB of video memory is required at the INT4 quantization level). ChatGLM-6B uses technology similar to ChatGPT, optimized for Chinese Q&A and dialogue. After about 1T identifiers of Chinese and English bilingual training, supplemented by supervision and fine-tuning, feedback self-help, human feedback reinforcement learning and other technologies, ChatGLM-6B with 6.2 billion parameters has been able to generate answers that are quite in line with human preferences.
Learn more about ChatGLM
Aya
Aya is a new state-of-the-art, open-source, massively multilingual, generative large language research model (LLM) covering 101 different languages — more than double the number of languages covered by existing open-source models. Aya helps researchers unlock the powerful potential of LLMs for dozens of languages and cultures largely ignored by most advanced models on the market today.
We are open-sourcing both the Aya model, as well as the largest multilingual instruction fine-tuned dataset to-date with a size of 513 million covering 114 languages. This data collection includes rare annotations from native and fluent speakers all around the world, ensuring that AI technology can effectively serve a broad global audience that have had limited access to-date.
Learn more about Aya
Muse Spark Open
Muse Spark Open is an open-weight, natively multimodal language model for developers and organizations building AI applications, coding systems, and agentic workflows. The released model has 816 billion total parameters, 42 billion active parameters, and a 1-million-token context window. Teams can download the model weights, run inference through supported engines such as vLLM, SGLang, TensorRT-LLM, Hugging Face Transformers, Apple MLX, llama.cpp, or Unsloth, and customize the model using PyTorch. It supports long-context reasoning, software engineering, coding, tool use, and multimodal inputs. Deployment options include cloud inference through listed API providers or self-hosting on compatible GPU systems; Meta documents a desktop setup using two Apple M5 Ultra Mac Studio computers. The model is released under the Muse Model License with limited commercial terms.
Learn more about Muse Spark Open
Pricing
Starting Price:
Free
Free Version:
Free Version available.
Integrations
Company Information
Meta
Founded: 2004
United States
ai.meta.com/llama/
Videos and Screen Captures
Other Useful Business Software
Custom VMs From 1 to 96 vCPUs With 99.95% Uptime
Live migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
Product Details
Platforms Supported
Cloud
Windows
Mac
Linux
On-Premises
Training
Documentation
Llama 2 Frequently Asked Questions
Q: What kinds of users and organization types does Llama 2 work with?
Llama 2 works with these users and organization types: Mid Size Business, Small Business, Enterprise, Freelance, Nonprofit, Government, and Startup.
Q: What languages does Llama 2 support in their product?
Llama 2 supports these languages: English.
Q: What other applications or services does Llama 2 integrate with?
Llama 2 integrates with: 1min.AI, Agenta, Coginiti, Decopy AI, AI-FLOW, AI/ML API, AI4Chat, AiAssistWorks, Aili, Airtrain, Alpaca, AlphaCorp, Amazon Bedrock, Anyscale, AnythingLLM, Automi, Microsoft Foundry Agent Service, Azure Marketplace, Microsoft Foundry Models, Batteries Included, BlueFlame AI, Bolna, BrandRank.AI, NVIDIA Brev, and Browser Use and more.
Q: What type of training does Llama 2 provide?
Llama 2 provides training in the form of documentation.
Q: How much does Llama 2 cost?
Pricing for Llama 2 starts at Free.
