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 run on the AI chips shipped through 2027?
Report
Oct. 2, 2026
How many AI agents could run on the AI chips shipped through 2027?

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

Long-context latency scales quadratically for GPT-5.6 but nearly linearly for Claude 5
Report
Sep. 8, 2026
Long-context latency scales quadratically for GPT-5.6 but nearly linearly for Claude 5

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