# How IOTA Train at Home rewards are shown in USD

IOTA Watch shows official subnet IOTA amounts and a public SN9 market estimate in USD. The dollar figure is not a payout.

- Canonical: https://iotahome.site/en/learn/iota-rewards-in-usd
- Publisher: IOTA Watch
- Topics: IOTA
- Published: 2026-09-12
- Updated: 2026-10-24

## At a glance

The dollar figure is a public-market estimate for SN9 subnet IOTA, not an official payout amount. Missing reward quantities or valid quotes remain unknown, not $0; IOTA Layer 1 prices are not substituted.

The dashboard shows **two numbers for the same reward**: the official IOTA amount from Train at Home entitlements, and an estimated USD value beside it.

## What is official

IOTA Watch labels IOTA as Yesterday's rewards by attributing the next accounting day's records to the preceding date in UTC+8. For example, records dated October 17 appear under October 16. Only pending and settled count; frozen and future timestamps are excluded. This display convention does not prove the actual training date or the date funds reached a wallet.

## What is an estimate

The USD line multiplies that IOTA amount by a public market price for the Train at Home subnet token (SN9 / CoinGecko `iota-2`). It is **not** the IOTA Foundation Layer 1 price, not TAO, and not a promise that you can sell at that rate.

## When USD is a dash

If the market feed is down, IOTA amounts stay visible and USD shows unknown. Missing price is not treated as $0.

> Use the IOTA number for official accounting. Use USD only as a rough scale.

If this token is still being mixed up with IOTA Layer 1, see [Train at Home vs the IOTA coin](https://iotahome.site/en/learn/iota-train-at-home-vs-iota-coin).

## Common questions

### Why can IOTA rewards exist while USD is a dash?

Rewards and prices use different sources; an unavailable quote prevents a reliable conversion.

### Can I use the IOTA Layer 1 token price?

No. It is a different asset from Train at Home’s SN9 subnet token.

## Sources and implementation

- [Macrocosmos · Train at Home user guide](https://docs.macrocosmos.ai/product-and-services/tah/tah-user-guide)
- [Macrocosmos · Train at Home FAQs](https://docs.macrocosmos.ai/product-and-services/tah/faqs)
- [IOTA Watch · source code](https://github.com/molimao/iota)