25.5 Trillion Tokens a Day: How SuperPods Power Massive RL Training
zephyr_z9 · x · 2026-08-01
The post speculates on the compute power behind reinforcement learning (RL) for frontier models. If latency is ignored, a single GPU can output around 18,000 tokens per second for an Opus-tier model. Using just two SuperPod clusters, this scales to 25.5 trillion tokens generated per day. This massive compute throughput explains how major labs can pull off extraordinary RL training feats.
More from Infra
- a16z: AI Infrastructure Demand Shows No Signs of Slowing Amid Supply Chain Snags — a16z · 2026-08-01
- Together AI Deep Dive: Autoscaling Endpoints for LLM Inference — togethercompute · 2026-08-01
- Vercel AI Gateway Adds Team and Project Spend Budgets — cramforce · 2026-08-01
- Tesla Signs 469MW Solar Deals to Lock in AI Compute Power Years Ahead — XFreeze · 2026-08-01
- Local Deployment on DGX Spark: Exploring Upgrades Beyond Qwen 3.5 122B — Voxandr · 2026-08-01
- Analyst Spots Equinix Expanding San Jose Campus by ~200MW — BenBajarin · 2026-08-01