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Plan a 10-trillion-token pre-training run end to end: compute, fleet, layout, data, checkpoints and a schedule with a failure budget.

Build a training schedule from explicit model, token, state and recovery assumptions. Keep active compute time separate from availability and contingency.

Updated Sep 2026 · Learn how AI infrastructure works through explanations, worked examples and diagrams, then practise applying it to interview questions.

Build a training schedule from explicit model, token, state and recovery assumptions. Keep active compute time separate from availability and contingency.

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Work through the numbers

Change the assumptions in a free calculator, then explain what the result establishes and what still needs measurement.

GPUs and time-to-train calculator

The concepts behind this question

Use these concept explanations to review the ideas behind this question.

🧮 Napkin Math & CapacitySign in

GPU-Hours and Time to TrainConvert a stated work budget into elapsed time and GPU-hours. Vary utilization, invert for a deadline, and separate productive time from calendar delays without counting them twice.

📐 AI Systems Design🔒 Premium

Evaluation and Data Pipeline InfrastructureData pipelines prepare traceable training inputs; evaluation pipelines compare model behavior. Both need versioned inputs, reproducible execution and useful failure reporting.

🕸️ Distributed Training

Data Parallelism and DDPReplicas combine gradients from different data. Follow a two-worker update, fix unequal-token weighting, and see why queued gradient buckets can leave more than one reduction exposed.

🕸️ Distributed TrainingSign in

ZeRO and FSDPZeRO and FSDP reduce replicated training state by distributing it across workers. The memory saving comes with communication and temporary-buffer costs.

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Next in this trackDesign a distillation pipeline that improves a target task without hiding capability regressions Next in this trackA PyTorch team wants to train on TPUs. Do they rewrite in JAX with MaxText, use PyTorch/XLA, or wait for TorchTPU?Closest to this topicYou need to train a 100B dense model and it does not fit on one node. Walk me through how you would lay it out.

FEDITOR'S NOTE

Check that batch arithmetic closes, token IDs fit their format, checkpoint recovery matches the failure domain, and power includes non-GPU IT load.

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