Using Jamba-Instruct on Microsoft Foundry
Implementation guide · Jamba · AI21 Labs
Quick Start
- 1
- 2Use the Microsoft Foundry SDK or REST API to call
jamba-instruct— see the documentation for request format. - 3
Code Examples
About Microsoft Foundry
Microsoft Foundry offers a comprehensive platform-as-a-service for enterprise AI operations. It provides multiple deployment options including Serverless APIs (pay-as-you-go), Global Standard (shared managed capacity), Provisioned Throughput Units (reserved capacity), batch processing, and bring-your-own model deployments. The platform features a unified control plane for models, agents, tools, and observability. Its Agent Service enables building and deploying AI agents with built-in tracing, monitoring, and governance. Evaluation and monitoring tools assess model performance, safety, and groundedness. Foundry supports seamless upgrades from Azure OpenAI with non-destructive migration, maintaining existing deployments while unlocking multi-provider model access and advanced platform capabilities.
Microsoft Foundry is a unified Azure platform-as-a-service offering for enterprise AI operations, model builders, and application development. It provides access to over 1,900 models from Microsoft, OpenAI, Anthropic, Mistral, xAI, Meta, DeepSeek, Hugging Face, and more. Foundry unifies agents, models, and tools under a single management grouping with built-in enterprise-readiness capabilities including tracing, monitoring, evaluations, and customizable enterprise setup configurations.
Pricing on Microsoft Foundry
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.50 |
| Output tokens | $0.70 |
Capabilities
No model capability flags are currently sourced.
About Jamba-Instruct
Jamba-Instruct, developed by AI21 Labs, is a cutting-edge large language model tailored for enterprise applications. It boasts a remarkable 256,000-token context window, enabling it to process vast amounts of data, equivalent to an 800-page novel, making it ideal for tasks like summarization, question answering, and document analysis. Utilizing a hybrid architecture that blends Structured State Space (SSM) technology with traditional Transformer layers, Jamba-Instruct is designed for optimal performance and efficiency in managing long-context scenarios. Instruction-tuned to handle complex commands and engage in open-ended dialogues, it prioritizes high safety standards, making it suitable for diverse applications such as chatbots, financial analysis, and legal document summaries while maintaining cost-effectiveness and low latency 2512.