Transform OpenAI gpt-oss Models into Domain Experts with Together AI Fine-Tuning
Transform OpenAI gpt-oss Models into Domain Experts with Together AI Fine-Tuning
The release of OpenAI's gpt-oss-120B and gpt-oss-20B models marks a pivotal moment in AI development. For the first time since the release of GPT-2 in 2019, OpenAI has released language models that are completely open-weight, licensed under Apache 2.0, and purpose-built for customization. These are now available on Together AI Inference for customers to use.
While these models deliver impressive performance out-of-the-box, fine-tuning unlocks their true potential, enabling organizations to create specialized AI systems that understand their unique domains, workflows, and requirements.
Together AI makes this transformation accessible. Our production-ready infrastructure, proven optimizations, and comprehensive fine-tuning capabilities mean you can customize OpenAI's breakthrough reasoning models without the complexity of managing distributed training infrastructure or the uncertainty of experimental platforms.
Together AI offers a unified platform for both fine-tuning and serving, streamlining your entire AI development workflow. Once your model is fine-tuned, you can instantly deploy it on a dedicated endpoint with enterprise-grade performance and reliability. Get started on your own through our self-service platform, or talk to our sales team for volume commitments and custom enterprise solutions.
Advantages of Fine-Tuning gpt-oss Models
Freedom to Adapt & Deploy
Open weights and a permissive license mean you can modify, evaluate, and run the model wherever you need.
Predictable, Stable Performance
Your customized model won't shift unexpectedly due to vendor updates or policy changes. You control the entire lifecycle, ensuring consistent performance and behavior across your applications without the risk of external dependencies disrupting critical business operations.
Superior Economics
Smaller, fine-tuned models frequently outperform bigger, more expensive base models on narrow tasks. Stop paying for slower, bloated generalist models.
Why Fine-Tuning Production Models is Challenging
Despite this, fine-tuning large reasoning models presents significant technical and operational hurdles. While fine-tuning even the 120B variant doesn’t require a massive amount of GPU resources, efficiently orchestrating distributed training is a complex task. ML Engineering teams frequently encounter out-of-memory errors, suboptimal resource utilization, and training instabilities that can derail entire projects without proper coordination.
Together AI Fine-Tuning Platform
Together AI eliminates these barriers through our comprehensive fine-tuning platform designed specifically for frontier models like gpt-oss-120B and gpt-oss-20B. Our Fine-Tuning API transforms complex distributed training into a simple three-step process: upload your formatted dataset, configure your training parameters, and launch your job. All without managing GPU clusters or debugging memory allocation issues.
Our platform handles the technical complexity automatically, from data validation and preprocessing to efficient LoRA training and model deployment. Fine-tuned models can be deployed to dedicated endpoints with the same performance optimizations and 99.9% uptime SLA that backs our serving platform. Enterprise reliability extends throughout the entire workflow, with SOC 2 compliance and comprehensive monitoring.
Both gpt-oss-20B and gpt-oss-120B are available for fine-tuning with the following configuration:
- LoRA fine-tuning
- 16K context window for supervised fine-tuning (SFT)
- 8K context window for direct preference optimization (DPO)
View our pricing page for additional details.
Getting Started & Next Steps
Fine-tuning OpenAI's gpt-oss models on Together AI opens new possibilities for organizations seeking to deploy specialized reasoning capabilities. Whether you're adapting models for domain-specific tasks, localizing for global markets, or training on your organization's private datasets, our platform provides the infrastructure and tools needed to succeed.
Ready to explore fine-tuning with gpt-oss models? Our Fine-Tuning Platform makes it simple to customize these powerful reasoning models for your specific use cases.
OpenAI's open reasoning models combined with Together AI's production infrastructure make it practical for organizations to build specialized AI systems while maintaining the performance, reliability, and cost efficiency needed for production use. These models represent a shift toward more accessible and customizable AI development.
Start building today:
- Interactive Playground: Test gpt-oss models before fine-tuning
- Fine-Tuning UI: Launch your experiments directly from the website
- API Documentation: Integration guides and fine-tuning examples
- Lower
Cost20% - faster
training4x - network
compression117x
Q: Should I use the RedPajama-V2 Dataset out of the box?
RedPajama-V2 is conceptualized as a pool of data that serves as a foundation for creating high quality datasets. The dataset is thus not intended to be used out of the box and, depending on the application, data should be filtered out using the quality signals that accompany the data. With this dataset, we take the view that the optimal filtering of data is dependent on the intended use. Our goal is to provide all the signals and tooling that enables this.