Compare pricing and specifications for large language models from all major providers.
Meta's large Llama 4 Mixture-of-Experts model with 400B total parameters (17B active per expert, 128 experts). Natively multimodal with a 1M token context window. Open source.
Meta's efficient Llama 4 model with an industry-leading 10M token context window. 109B total parameters (17B active per expert, 16 experts). Natively multimodal and open source.
Meta's Llama 4 Maverick with mixture-of-experts architecture, 1M context window, and strong multilingual support. Open-source model.
Meta's Llama 4 Scout with an industry-leading 10M token context window and 16 experts MoE architecture. Optimized for efficiency.
Meta's latest 70B parameter model with improved performance and capabilities, offering state-of-the-art results for its size.
Meta's multimodal model combining text and vision capabilities with strong performance across various tasks.
A smaller, efficient multimodal model from Meta with vision capabilities, suitable for edge deployment and cost-sensitive applications.
Meta's largest and most capable Llama 3.1 model, designed for complex reasoning, coding, and nuanced instruction following.
A large instruction-tuned model from Meta's Llama 3.1 series, offering a strong balance of performance and efficiency for a wide range of tasks.
A highly efficient instruction-tuned model from Meta's Llama 3.1 series, suitable for fast, on-device, or edge applications.
Meta's large Llama 4 Mixture-of-Experts model with 400B total parameters (17B active per expert, 128 experts). Natively multimodal with a 1M token context window. Open source.
Meta's efficient Llama 4 model with an industry-leading 10M token context window. 109B total parameters (17B active per expert, 16 experts). Natively multimodal and open source.
Meta's Llama 4 Maverick with mixture-of-experts architecture, 1M context window, and strong multilingual support. Open-source model.
Meta's Llama 4 Scout with an industry-leading 10M token context window and 16 experts MoE architecture. Optimized for efficiency.
Meta's latest 70B parameter model with improved performance and capabilities, offering state-of-the-art results for its size.
Meta's multimodal model combining text and vision capabilities with strong performance across various tasks.
A smaller, efficient multimodal model from Meta with vision capabilities, suitable for edge deployment and cost-sensitive applications.
Meta's largest and most capable Llama 3.1 model, designed for complex reasoning, coding, and nuanced instruction following.
A large instruction-tuned model from Meta's Llama 3.1 series, offering a strong balance of performance and efficiency for a wide range of tasks.
A highly efficient instruction-tuned model from Meta's Llama 3.1 series, suitable for fast, on-device, or edge applications.