FAQ
Frequently asked questions about AntSeedStats and the data behind it.
About AntSeedStats
What is AntSeedStats?
An independent, third-party analytics dashboard for AntSeed, the peer-to-peer AI-inference marketplace on Base. It turns raw on-chain activity into readable charts, tables and context — revenue, network metrics, staking, $ANTS, $DIEM, sellers, buyers, models and more.
Are you affiliated with the AntSeed team?
No. AntSeedStats is independent and runs separately — we build in the open and stay in touch with the AntSeed team, but are not operated by or officially affiliated with them. Built by @gekko_eth and provided for informational purposes only — not financial advice.
Where does the data come from?
Live, from Base mainnet (events and contract state) plus public AntSeed endpoints and our own DHT poller for provider reputation. Nothing is invented — every figure traces back to a verifiable source, and you can watch the pipeline's health on the status page.
AntSeed, $ANTS & DIEM
What is AntSeed?
A peer-to-peer marketplace for AI inference on Base. Buyers pay sellers in USDC through payment channels; the protocol takes a small fee and rewards participants with its $ANTS token.
What is $ANTS?
AntSeed's native token, emitted each epoch to sellers and buyers. Token transfers are currently gated, so there is no real market price yet — we never invent one. Note that the canonical token is
0xa87EE81b2C0Bc659307ca2D9ffdC38514DD85263; some price sites index an unrelated impostor token — ignore those.What is $DIEM?
$DIEM is the Venice ecosystem's token (
0xf4d9…a024 on Base). AntSeed runs a provider-capacity staking pool around it: stakers deposit $DIEM to back inference capacity and earn USDC from marketplace fees plus $ANTS incentives. The pool is fronted by the Venice.ai proxy seller. For a deeper explainer, see VeniceStats' “What is DIEM”.What is the “Buy & Burn”?
A share of the DIEM pool's operator fee accrues to a treasury, intended to buy back and burn $ANTS once the token becomes transferable. We read the treasury balance live on-chain and show it on the $ANTS page; no burns have happened yet.
Staking & points
What are “points”?
Points are the accounting unit of AntSeed's reward model. Each settled inference accrues points to the seller and the buyer of that trade. Each epoch emits a fixed amount of $ANTS (split between sellers, buyers, a reserve and the team), and your share of that epoch's emission equals your share of the points. In practice the seller points track settled volume very closely (they are denominated in the raw on-chain USDC unit), which is why the points and revenue charts have the same shape.
Why don't you show estimated $ANTS rewards per seller?
The points→$ANTS formula is proven in structure but one scale factor isn't fully confirmed yet against real claims. Rather than publish a number we're not certain of, we show the raw points and will add estimated $ANTS once it's validated.
The numbers
Why might your figures differ from other dashboards?
Different dashboards use different methodologies, so totals can diverge. Our approach is to reconcile everything against on-chain truth and be explicit about how each metric is computed — for example, settled revenue and volume tie to the contracts' own per-agent accumulators. When in doubt, the on-chain source wins, and we show our working.
What does “settled (gross)” vs “net to sellers” mean?
Settled (gross) is the full buyer-paid amount, including the flat 4% protocol fee. Net to sellers is gross minus that fee. Some dashboards headline the net figure as “volume”; we label both so it's unambiguous.
How fresh is the data?
Near-realtime: a WebSocket feed picks up new events as they land, backed by a catch-up worker and self-verifying ingestion. Current chain head, last indexed block and lag are on the status page.
Reading the site
What is the Network explorer?
The Network page lists every service advertised on the AntSeed DHT — one row per peer × model — with prices per million tokens, reputation, verification, stake and usage. Filter by lab, capability, provider or the green FREE chip (services priced $0 for both input and output). Peers marked “new” announce on the DHT but have not settled on-chain yet.
What are Labs?
The organizations behind the models — Anthropic, OpenAI, DeepSeek, Google and friends. The Labs pagegroups every advertised model under its lab, and typing a lab's name in any search box (or in the Network filters) narrows results to that lab's models.
How do I read the Distribution page?
Distribution measures how concentrated each side of the marketplace is. The Lorenz curve plots the cumulative value share held by the bottom X% of accounts (the further it bows below the diagonal, the more concentrated). Gini summarizes that gap (0 = perfectly even, 1 = one account takes everything); effective is the equivalent number of equal-sized participants; top-10 share is the most intuitive headline.
What is “Cached $/M”?
Some sellers price cached input tokens (prompt prefixes the model has already processed) cheaper than fresh input. The Cached $/M column shows that advertised price; when a seller does not announce one, cached input simply costs the same as regular input.
Why can't usage be split per model?
The on-chain metadata records token counts but not which model served each request, so Tokens and Users on the Network pageare provider-level totals shown on every one of that provider's rows. The AntSeed team is working on richer on-chain usage reporting; once it lands we can show true per-model usage.
What are the translucent chart bars?
Pace-to-date projections. The current day (or epoch) is still in progress, so its solid bar shows what has actually happened and the translucent extension projects the final value by scaling the so-far amount by the fraction of the period elapsed. Projections are estimates, never recorded data.
Misc
Is there an API?
A public data API is on the roadmap. For now, a machine-readable health summary is exposed at
/api/status — watch the changelog for when the full API lands.I found a bug, or want a feature?
Reach out to @gekko_eth — feedback is welcome.