A 32-billion-parameter student model fine-tuned on DeepSeek-R1’s reasoning traces scored 72.6% Pass@1 on AIME 2024, beating OpenAI’s o1-mini (63.6%) while costing roughly an order of magnitude less per token to serve. Released with the DeepSeek-R1 checkpoints, it is the strongest production evidence yet that knowledge distillation—not larger GPUs—is the dominant …
Editorial team 
Reasoning Models Cost 15x. Adaptive Depth Saves 60%
Send one complex query to OpenAI o3 and it can burn 10,000 to 50,000 reasoning tokens before emitting a single visible word — all billed at the $60-per-million output rate, all hidden in a thinking block that never appears in the response (source). Reasoning models are the single biggest line-item …