Model Gateway and Model Customization

The right model for your business needs

InstructLab customization product screen
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Enhance AI model performance

watsonx.ai® enables AI Developers and machine learning engineers to choose from thousands of state- of- the- art (SOTA) foundation models. It also optimizes the model development process by bringing together customization and tuning methods for specific use cases

Access any model, anywhere

With Model Gateway, development teams can choose any model, regardless of where it is deployed or hosted.

Rapid iteration

Customize models with enterprise data in a matter of hours, not months.

Cost optimization

Optimize model performance by leveraging a smaller, task-specific model instead of relying on larger, general-purpose ones.

Model performance

Deploy models more efficiently to optimize performance and runtimes.

Product ui for use cases on watsonx page

OpenAI's open-sourced gpt-oss models available for use in watsonx.ai

One of the two models, the larger gpt-oss-120b, is available now in watsonx.ai, while the second model, gpt-oss-20b, will be added to the platform for use soon!

Learn more
Image of model gateway interface with the option for Users to leverage third-party models to develop agents using any OOTB templates, and quickly deploy them as AI services.
Public Preview Model gateway Through a uniform API approach enabled through a fully OpenAI compatible API, businesses can seamlessly switch between the model of their choice, no matter where it is hosted Learn more about how your business can take advantage of model gateway
Learn more about how your business can take advantage of model gateway
Customize your models with these methods Retrieval augmented generation (RAG)

Ground AI applications with structured and unstructured data for improved accuracy and efficiency.

Prompt tuning

Customize models efficiently through lightweight methods that preserve the core architecture while refining prompts for improved accuracy.

Synthetic data generation

Enables developers to generate high-quality, task-specific unstructured data on demand so they can tune foundation models.

Parameter efficient fine-tuning

Improve the performance of a pretrained model by training a small set of parameters, preserving the original structure and saving time and resources.

Full fine-tuning

Uses the base model’s previous knowledge as a starting point to tailor the model by tuning it with a smaller, task-specific dataset.

Prompt engineering

Helps AI models better comprehend and respond to a wide range of queries, from the simple to the highly technical.

Choose your model

Power AI applications using our library of third-party and IBM® Granite® models suitable for AI workflows or bring your own custom foundation model to the platform.

Learn more about Granite Explore foundation models in watsonx.ai
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Try watsonx.ai at no cost or continue your journey of discovery.

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Learn more: Learn about IBM’s leadership among ML Ops platforms according to IDC Marketscape Register for The Forrester Wave: AI/ML Platforms, Q3 2024 The 2025 Guide to Prompt Engineering