Tinker

Founded by Mira Murati in 2025

Fine-tune open-source models efficiently without managing infrastructure.

Cost

Pay As You Go

Rating

★ People love it

Time to value

Quick Setup (< 1 hour)

You can use Tinker to fine-tune open-source models like Llama and Qwen using LoRA, without handling the underlying infrastructure. It provides a simple API with functions for forward and backward passes, optimization steps, sampling, and saving training progress. Tinker manages scheduling, resource allocation, and reliability, allowing you to focus on your data and algorithms.

What Tinker does

Perform forward and backward passesUpdate model weightsGenerate sample outputsSave and resume training progressManage training datasetsMonitor training performanceAdjust training parametersDeploy fine-tuned modelsFine-tune open-source models with LoRASimple API for training operationsNo need to manage infrastructureSupports models like Llama and QwenHandles scheduling and resource managementDownload model weights anytime