Modal Releases Open-Source Spindle Training Server
Modal released Spindle, an open-source training server compatible with Thinking Machines' Tinker API that runs in a user's Modal workspace. It supports full-parameter training and multi-LoRA for open models, while users control the server and pay for GPU time rather than tokens. Modal says its default configurations are tuned to maximize GPU utilization and that Spindle can support hundreds of concurrent training runs at similar performance and lower cost than closed-source APIs; the release remains in beta.
Spindle provides teams running post-training and reinforcement-learning experiments with another implementation of the Tinker-compatible training interface, server customization and GPU-time billing on Modal infrastructure.
Thinking Machines’ Tinker changed how people do post-training. You write the training loop in plain Python on your laptop, and Tinker runs the forward and backward passes on its GPUs. We’re big fans, and so are many of the teams we work with.
As those teams scale up, however, they keep raising the same two problems:
- Per-token pricing gets expensive once you’re running dozens of experiments.
- You can only use the models and features the provider decides to support.
We think a good API deserves more than one implementation. Today we’re releasing Spindle, an open-source, Tinker-compatible training server that runs in your Modal workspace. Because you own the server, you can customize anything in it, and you pay for GPU time instead of tokens. Our default configs are tuned to maximize GPU utilization out of the box, and we plan to keep shipping optimizations to push price-performance further.
All it takes is a single command to deploy a server:
spindle deploy#Modal#Spindle#Tinker#Thinking Machines#Modal Dojo#Miles#SGLang#GPT-OSS-20B#Qwen3.5-9B