Model Garden

A model garden is a platform that provides access to a curated collection of pre-trained AI models, often from multiple providers, through a unified interface. Major cloud platforms — Google Cloud's Model Garden, AWS Bedrock, Azure AI Studio — all offer model garden services that let organisations experiment with and deploy different models without managing the underlying infrastructure.

What a model garden provides

• Model catalogue: A browsable collection of models organised by task (text generation, image recognition, translation, etc.), provider, and capability.
• Unified API: Access different models through a consistent interface, reducing the integration effort when switching between models.
• Managed infrastructure: The platform handles model hosting, scaling, and maintenance.
• Evaluation tools: Built-in capabilities to test models on your data and compare their performance.
• Fine-tuning capabilities: Tools to customise models on your own data without managing training infrastructure.

Why model gardens matter

The AI model landscape is evolving rapidly. New models are released regularly, each with different strengths, pricing, and licensing terms. A model garden allows organisations to:

• Compare before committing: Test multiple models on the same tasks to find the best fit before investing in integration.
• Avoid vendor lock-in: When your application calls a model through a unified API, switching from one model to another requires changing a configuration rather than rewriting code.
• Stay current: As better models become available, they can be adopted quickly through the model garden rather than requiring new infrastructure.
• Manage compliance: Model gardens from major cloud providers often include compliance certifications and data residency guarantees that simplify regulatory requirements.

Major model gardens

• Google Cloud Model Garden: Offers access to Google's models (Gemini, PaLM) alongside open-source and third-party models within Vertex AI.
• AWS Bedrock: Provides access to models from Anthropic (Claude), Meta (Llama), Cohere, Stability AI, and Amazon's own models through a unified API.
• Azure AI Studio: Hosts OpenAI's models alongside open-source models with Azure's enterprise infrastructure.
• Hugging Face Hub: An open platform hosting over a million models, though with less managed infrastructure than cloud provider offerings.

Choosing a model garden

The right model garden depends on your existing cloud infrastructure, the specific models you need, data residency requirements, and pricing. Most enterprises end up using the model garden from their primary cloud provider, supplemented by direct API access to specific providers when needed.

The strategic implication

Model gardens represent a shift from "picking the one right model" to "orchestrating multiple models for different tasks." The organisations that build this multi-model capability will be better positioned to adopt improvements as the field advances.