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Meta's Llama 4 Scout model supports a record-breaking 10 million token context window. While this is impressive for research use cases, production inference at this context depth requires significant GPU memory and specialized hardware.

Setting temperature=0 reduces randomness but doesn't guarantee identical outputs across API calls - models can still vary due to sampling hardware differences. For true reproducibility, use temperature=0 AND set a fixed seed parameter (available in OpenAI and some other APIs).

GPUs (Graphics Processing Units) are excellent for parallel processing and are widely used for training AI models. TPUs (Tensor Processing Units), developed by Google, are custom-built accelerators specifically designed for neural network workloads, often providing better performance and efficiency for specific AI tasks.