How many AI agents could run on the AI chips shipped through 2027?
Closed frontier models: concurrency inferred from API spendingSince closed frontier models lack the architecture details needed for transparent hardware benchmarks, we instead look at the API costs of a continuously running agent. We analyzed TraceLab’s dataset of Codex and Claude Code agent sessions. We adjusted for human delays (agent waiting on human response) and divided spending by agent working time to normalize to an hourly rate.
- ▪Closed frontier models: concurrency inferred from API spendingSince closed frontier models lack the architecture details needed for transparent hardware benchmarks, we instead look at the API costs of a continuously running agent.
- ▪We analyzed TraceLab’s dataset of Codex and Claude Code agent sessions.
- ▪We adjusted for human delays (agent waiting on human response) and divided spending by agent working time to normalize to an hourly rate.
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Record
| Original publisher | Epoch AI |
| Canonical URL | https://epoch.ai/publications/estimating-the-agent-population |
| Publication time | Sat, 03 Oct 2026 14:17:36 +0000 |
| Retrieval time | 2026-10-03T14:33:12.829Z |
| Last seen | 2026-10-03T14:33:12.829Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | 1Dk6Pl3eSXVz · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Closed frontier models: concurrency inferred from API spendingSince closed frontier models lack the architecture details needed for transparent hardware benchmarks, we instead look at the API costs of a continuously running agent. We analyzed TraceLab’s dataset of Codex and Claude Code agent sessions. We adjusted for human delays (agent waiting on human response) and divided spending by agent working time to normalize to an hourly rate. Using the API prices listed in Table A3, we calculated the API-equivalent spending per agent-hour.We then estimate how much of that spending covers serving costs, using an assumed markup ratio of API revenue to serving cost.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Epoch AI.
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