Fireworks Managed Training

Fireworks Training Agent is a UI-accessible fine-tuning tool from Fireworks AI. It accepts a dataset and a description of the training goal, then selects a base model, cleans the data, plans and runs the fine-tuning job, chooses hyperparameters, and reports the results. Fireworks describes this guided training path as letting users describe the task, review the plan and cost, approve the run, and receive a trained model; the demonstrated workflow used supervised fine-tuning on Qwen 3 8B.

Fireworks AI's training API is a programmatic model-training offering for ML engineers who need to define custom training loops and loss functions beyond managed training. The video describes support for supervised fine-tuning, reinforcement fine-tuning, and direct preference optimization (DPO), as part of Fireworks AI's train-and-serve workflow for open models.

Fireworks AI is a training and inference platform for transforming open models into specialized, deployable AI systems. Its training offerings range from guided runs, where the platform helps define the task and plan, through configuration-led managed training, to user-written training logic with custom losses, trainers, and reinforcement-learning loops; trained checkpoints can be deployed to production. Its inference service supports open models and customer-trained versions through serverless, dedicated on-demand, and reserved deployments, with an optimized inference engine and OpenAI- and Anthropic-compatible interfaces. Fireworks also provides a model library for running open-source models and supports the continuous train-and-serve workflow described by the videos, including monitoring, hot-loading new weights without downtime, and matching training and serving numerics.

Fireworks is an AI platform that provides training and inference tools to transform open models into domain-specific or specialized intelligence. The service offers capabilities for model training, fine-tuning and serving to support customized AI deployments.

Fireworks AI's inference engine for serving AI models. It uses custom-built CUDA kernels that can be optimized for a customer's workload to target latency and performance requirements. The video credits FireAttention and related Fireworks serving work with enabling 13× faster inference for Cursor's Composer 2.