模型

浏览来自所有提供商的 28 个标准化 LLM 模型

显示第 25–28 项,共 28 个模型

Llama 3.2 3B Instruct

美国

Meta's lightweight open-weight model with 3 billion parameters from the Llama 3.2 family. Designed for on-device and edge deployment with strong text generation capabilities relative to its size. Supports instruction following and general-purpose tasks.

上下文
131K
发布日期
2024年9月

Llama 3.2 90B Vision Instruct

美国

Meta's largest multimodal open-weight model with 90 billion parameters from the Llama 3.2 family. Delivers strong performance on both text and image understanding tasks with competitive results on visual reasoning benchmarks. Designed for high-quality inference requiring vision capabilities.

上下文
131K
发布日期
2024年9月

Llama 3.2 11B Vision Instruct

美国

Meta's multimodal open-weight model with 11 billion parameters from the Llama 3.2 family. Supports both text and image inputs, enabling visual understanding tasks alongside standard text generation. Suitable for applications requiring vision capabilities at moderate scale.

上下文
131K
发布日期
2024年9月

Llama 3.1 8B Instruct

美国

Meta's efficient open-weight model with 8 billion parameters from the Llama 3.1 family. Optimized for instruction following with strong performance on general tasks, coding, and multilingual benchmarks. Ideal for cost-effective deployment and edge inference scenarios.

上下文
131K
发布日期
2024年7月