Models on Databricks Foundation Model Serving
13 models available · Databricks
| Model | Input (per 1M) | Output (per 1M) | Context | |
|---|---|---|---|---|
| Llama 2 70B Chat | $0.5 | $1.5 | 4K | |
| Mixtral 8x7B | $0.5 | $1 | 32K | |
| MPT 7B | $0.5 | $0.5 | — | |
| DBRX Instruct | $0.75 | $2.25 | 32K | |
| Llama 2 13B Chat | $0.95 | $0.95 | 4K | |
| Llama 3 70B Instruct | $1 | $3 | 8K | |
| MPT 30B | $1 | $1 | — | |
| DBRX | — | — | 32K | |
| DeepSeek R1 | — | — | 128K | |
| Llama 3 8B Instruct | — | — | 8K | |
| Llama 3.1 405B Instruct | — | — | 128K | |
| Llama 3.1 70B Instruct | — | — | 128K | |
| Llama 3.1 8B Instruct | — | — | 128K |
Pricing Overview
About Databricks Foundation Model Serving
Databricks offers a comprehensive AI platform that integrates a lakehouse model, combining the flexibility of data lakes with the management capabilities of data warehouses. The platform features a natural language interface for conversational data querying, automated infrastructure management for optimized performance, and robust governance tools ensuring data privacy and compliance. It supports a wide range of functionalities including data engineering, real-time streaming, and a marketplace for data sharing, while enabling seamless collaboration among data scientists, engineers, and DevOps teams . The platform's capabilities extend to advanced machine learning operations (MLOps), facilitating the entire lifecycle of AI model development. It includes built-in support for popular libraries like TensorFlow and PyTorch, tools for monitoring data quality and model performance, and automated workflows for building production-ready ETL pipelines. The platform also integrates with large language models (LLMs) for generative AI applications, emphasizing cost efficiency and ease of use. This comprehensive suite of tools empowers organizations to effectively leverage AI while maintaining control over their data and models .
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