Hey HN,
I built a small HTTP framework to experiment with free-threaded and wanted to share some observations. Barq is ~500 lines of pure Python — no C extensions, no Rust, no Cython. It uses only the standard library plus Pydantic.
Benchmarks (Barq 4 threads vs FastAPI 4 worker processes):
- JSON: Barq 10,114 req/s vs FastAPI 5,665 req/s → Barq +79%
- DB query: Barq 9,962 req/s vs FastAPI 1,015 req/s → Barq +881%
- CPU bound: Barq 879 req/s vs FastAPI 1,231 req/s → FastAPI +29%
by timonpimba ·
How is Deepseek actually doing this? Are they just feeding claude's answers into their own models as their own model as training data to improve reasoning? How exactly one train it's model on output of other? what's enginnering inovlved here?
I'd love breakdown of how thsi is executed at scale.
Backstory:
Anthropic recently accused Deepseek,Minimax,Moonshot of using lots of fake accounts to generate exchanges with claude, using the outputs to train the model and called it "distillation attack".