Activefrontierllm Open Source

Llama 3 70B

by Meta· Released April 2024· Cutoff December 2023

Llama 3 70B is a large language model from Meta, part of the Llama 3 family, offering strong performance across a wide range of natural language tasks. It is an open-source model that balances capability with accessibility, making it suitable for both research and commercial applications. As the mid-sized variant in the Llama 3 lineup, it provides a compelling option for developers needing high-quality text generation without the computational demands of the 405B model.

Official Site API Docs 🤗 Hugging Face 📄 Research Paper

Input cost

Free (open source)

Output cost

Free (open source)

Context window

8K tokens

Max output

—

Modalities

text

Parameters

70B

License

Llama 3 Community License

Capabilities

Text GenerationCode GenerationInstruction FollowingReasoningMultilingual SupportSummarizationQuestion Answering

Best For

High-quality text generation and code synthesis with a balance of performance and efficiency.

Strengths

Strong performance on benchmarks comparable to proprietary models
Open-source with permissive license
Efficient for its size, suitable for fine-tuning and deployment
Good multilingual capabilities
Active community and ecosystem support

Limitations

Smaller context window (8K tokens) compared to some competitors
No native vision or multimodal support
May require careful prompting for complex reasoning tasks
Not as capable as the 405B variant for very demanding tasks

Use Cases

Chatbots and virtual assistants

Code generation and assistance

Content creation and summarization

Educational tools and tutoring

Research and experimentation in NLP

Fine-tuning for domain-specific applications

Language translation and multilingual tasks

Improvements Over Previous Model

Improved performance over Llama 2 70B on major benchmarks (e.g., MMLU, HumanEval)
Enhanced instruction following and safety with RLHF
Larger vocabulary (128K tokens) for better multilingual support
Grouped-query attention (GQA) for faster inference
Trained on 15 trillion tokens vs 2 trillion for Llama 2

Back to all models

Improvements Over Previous Model

Improved performance over Llama 2 70B on major benchmarks (e.g., MMLU, HumanEval)

Enhanced instruction following and safety with RLHF

Larger vocabulary (128K tokens) for better multilingual support

Grouped-query attention (GQA) for faster inference

Trained on 15 trillion tokens vs 2 trillion for Llama 2