Jason Li

Jason Li

Jason Li is a researcher at Epoch AI, where he studies topics related to AI inference. Before Epoch, he worked at NVIDIA on LLM serving and inference optimization.

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By Jason Li

How many AI agents could we run?
Report
Oct. 2, 2026
How many AI agents could we run?

Memory shipped through 2027 could run 33–171 million concurrent frontier-model agents, or billions using efficient open models. Epoch AI estimates inference capacity from HBM supply, serving benchmarks, and agent-hour costs.

By Jason Li

Latency scaling differences for GPT and Claude models
Report
Sep. 8, 2026
Latency scaling differences for GPT and Claude models

Epoch AI measures long-context latency scaling across four frontier models. GPT-5.6 Terra and Sol show quadratic time-to-first-token growth with context length, while Claude Sonnet 5 and Opus 5 stay near-linear.

By Jason Li