Quick Start
- 1
- 2Use the Microsoft Foundry SDK or REST API to call
arctic— 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 | $2.00 |
| Output tokens | $2.00 |
Capabilities
About Arctic
Snowflake Arctic is an advanced large language model tailored for enterprise applications by Snowflake AI Research. It features an innovative Dense-MoE Hybrid transformer architecture, combining a 10 billion parameter dense transformer with a 128 x 3.66 billion parameter MoE MLP, totaling 480 billion parameters but utilizing only 17 billion actively. This structure optimizes efficiency, particularly for tasks like SQL generation, coding, and instruction following. The model's training spanned a diverse dataset of 3.5 trillion tokens, focusing on enterprise needs. Despite its capabilities, Arctic's deployment presents challenges due to its size, and it remains vulnerable to inaccuracies with unclear inputs. Open-sourced under the Apache 2.0 license, it provides comprehensive access to its weights, code, and research findings 1 2 4 5.