Compare pricing and specifications for large language models from all major providers.
Meta's flagship open-weight model for 2026. Llama 5 Maverick is a large mixture-of-experts system with a 2M token window and native multimodal input, released under the Llama 5 Community License.
The compact member of the Llama 5 family. Scout runs on a single 24 GB consumer GPU at full speed while keeping a 1M token window and vision input, which makes it the practical choice for local and edge work.
Meta's largest released model, positioned against closed frontier systems. Behemoth is served through partners rather than being practical to self-host, and it leads open-weight benchmarks on reasoning and math.
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 flagship open-weight model for 2026. Llama 5 Maverick is a large mixture-of-experts system with a 2M token window and native multimodal input, released under the Llama 5 Community License.
The compact member of the Llama 5 family. Scout runs on a single 24 GB consumer GPU at full speed while keeping a 1M token window and vision input, which makes it the practical choice for local and edge work.
Meta's largest released model, positioned against closed frontier systems. Behemoth is served through partners rather than being practical to self-host, and it leads open-weight benchmarks on reasoning and math.
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.