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Maxime Rivest claims he fine-tuned a 4B model using just 5000 training examples, 4 hours of training, and an $80 budget to outperform GPT 5.6, arguing that cheap training data and capable coding agents now make custom model training accessible.
This paper presents an open-source pretraining recipe that trains 2B-parameter language models on consumer-grade RTX 5090 GPUs for under $7K, achieving performance near larger baselines and deriving cost scaling laws for model training.