> Canonical page: https://posttrainllm.com/inspiration

The people and projects behind the lab

# Built in good company.

PostTrainLLM grew by studying tools that solved hard problems in public. Here are the ideas we admired, the parts we tried, and the limits we kept.

[Meet the projects ↓](https://posttrainllm.com/inspiration#all-inspirations)

## With thanks to

24 named tools and projects

- 01 ### [TrainLoop AI](https://posttrainllm.com/inspiration/trainloop-ai) Research loops [Read the story ↗](https://posttrainllm.com/inspiration/trainloop-ai)
- 02 ### [Baseten](https://posttrainllm.com/inspiration/baseten) Factory framing [Read the story ↗](https://posttrainllm.com/inspiration/baseten)
- 03 ### [Hugging Face](https://posttrainllm.com/inspiration/hugging-face) Open baselines [Read the story ↗](https://posttrainllm.com/inspiration/hugging-face)
- 04 ### [SQLCoder and Arctic Text2SQL](https://posttrainllm.com/inspiration/sqlcoder) Evaluation [Read the story ↗](https://posttrainllm.com/inspiration/sqlcoder)
- 05 ### [Apple Foundation Models](https://posttrainllm.com/inspiration/apple-foundation-models) Mac capability [Read the story ↗](https://posttrainllm.com/inspiration/apple-foundation-models)
- 06 ### [Castform](https://posttrainllm.com/inspiration/castform) Training loops [Read the story ↗](https://posttrainllm.com/inspiration/castform)
- 07 ### [Cline](https://posttrainllm.com/inspiration/cline) Agent architecture [Read the story ↗](https://posttrainllm.com/inspiration/cline)
- 08 ### [Gigatoken](https://posttrainllm.com/inspiration/gigatoken) Data preparation [Read the story ↗](https://posttrainllm.com/inspiration/gigatoken)
- 09 ### [Needle 2](https://posttrainllm.com/inspiration/needle-2) Small specialists [Read the story ↗](https://posttrainllm.com/inspiration/needle-2)
- 10 ### [parakeet.wgsl](https://posttrainllm.com/inspiration/parakeet-wgsl) Browser runtimes [Read the story ↗](https://posttrainllm.com/inspiration/parakeet-wgsl)
- 11 ### [Savante and Aryabhata](https://posttrainllm.com/inspiration/savante-aryabhata) Specialist data [Read the story ↗](https://posttrainllm.com/inspiration/savante-aryabhata)
- 12 ### [Bonsai 2](https://posttrainllm.com/inspiration/bonsai-2) Packaging [Read the story ↗](https://posttrainllm.com/inspiration/bonsai-2)
- 13 ### [QORL](https://posttrainllm.com/inspiration/qorl) Evaluation [Read the story ↗](https://posttrainllm.com/inspiration/qorl)
- 14 ### [vLLM](https://posttrainllm.com/inspiration/vllm) Serving systems [Read the story ↗](https://posttrainllm.com/inspiration/vllm)
- 15 ### [Splash](https://posttrainllm.com/inspiration/splash) Mac runtimes [Read the story ↗](https://posttrainllm.com/inspiration/splash)
- 16 ### [Halo](https://posttrainllm.com/inspiration/halo) Scale boundary [Read the story ↗](https://posttrainllm.com/inspiration/halo)
- 17 ### [Transformer Explainer](https://posttrainllm.com/inspiration/transformer-explainer) Learning tools [Read the story ↗](https://posttrainllm.com/inspiration/transformer-explainer)
- 18 ### [CoreML-LLM](https://posttrainllm.com/inspiration/coreml-llm) Mac runtimes [Read the story ↗](https://posttrainllm.com/inspiration/coreml-llm)
- 19 ### [MLX](https://posttrainllm.com/inspiration/mlx) Mac foundations [Read the story ↗](https://posttrainllm.com/inspiration/mlx)
- 20 ### [oMLX](https://posttrainllm.com/inspiration/omlx) Mac runtimes [Read the story ↗](https://posttrainllm.com/inspiration/omlx)
- 21 ### [Prime Intellect](https://posttrainllm.com/inspiration/prime-intellect) Scale boundary [Read the story ↗](https://posttrainllm.com/inspiration/prime-intellect)
- 22 ### [teale and Petals](https://posttrainllm.com/inspiration/teale-petals) Scale boundary [Read the story ↗](https://posttrainllm.com/inspiration/teale-petals)
- 23 ### [Weco AI](https://posttrainllm.com/inspiration/weco) Research loops [Read the story ↗](https://posttrainllm.com/inspiration/weco)
- 24 ### [Aster AI Labs](https://posttrainllm.com/inspiration/aster) Scale boundary [Read the story ↗](https://posttrainllm.com/inspiration/aster)

Credit, with context

## Admiration is a starting point.

Some ideas became local tools; some stayed studies, and some failed our tests. Each article links the original project and our own evidence so you can follow the distinction. Papers and articles live in the[reading list](https://posttrainllm.com/docs/learn/external-references/) and appear here as sources, not separate entries.

[Browse the evidence dossiers ↗](https://posttrainllm.com/studies)