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What is the YouTube RPM for education and how-to channels in 2026?

Short answer

Education and how-to YouTube channels earn an RPM of $4.00–$10 per 1,000 long-form views in 2026, with a typical figure near $6.00. That means 100,000 views pays roughly $600 in ad revenue. Shorts in the same niche pay about $0.05 per 1,000 views.

Education and how-to RPM and earnings benchmarks

MetricValueNotes
Long-form RPM$4.00–$10$6.00 typical
Implied CPM (pre-split)$7.60–$19before YouTube's 45% cut
10,000 views$60
100,000 views$600
1,000,000 views$6,000
Shorts RPM$0.05per 1,000 Shorts views
Sponsorship CPM$20typical integrated deal

Run your own numbers

Pre-filled: education and how-to, 100K views
Ad revenue
$600
Range $400 – $1,000
Sponsorship
$2,000
On the same views
Total
$2,600
Open the full YouTube revenue calculator

How to read this table

Context

RPM in this niche is set mainly by advertiser competition: broad, evergreen demand with a mix of consumer and edtech advertisers. Two education and how-to channels with identical view counts can still land at opposite ends of the $4.00–$10 band, because audience geography (a US-heavy channel often doubles the RPM of a globally split one), video length (10+ minutes unlocks multiple mid-rolls) and Shorts share all move the number.

What moves this number

Audience geography

US, UK, Canada, and Australia viewers monetise several times higher than most of Asia, Africa, and Latin America. A channel with 70% US audience and one with 70% India audience can post identical view counts and see a 5–10× revenue gap.

Niche and advertiser demand

Finance, B2B software, insurance, and legal topics attract advertisers with real customer value, so they bid more per impression. Gaming, reaction, and general vlog content compete for cheaper inventory.

Format mix

Long-form ad revenue and Shorts pool payouts are not comparable. Shifting views toward Shorts almost always lowers blended RPM even while total views rise.

Watch time and ad load

Videos over eight minutes can carry mid-roll ads, which is the single biggest controllable lever on revenue per view.

Seasonality

Advertiser budgets peak in Q4 and reset hard in January. Same views, up to 40% swing in payout between December and January.

Methodology

Figures blend YouTube Partner Program payout data, public creator disclosures for education and how-to channels, and anonymised submissions to the RevenueLab YouTube Revenue Calculator. RPM is post-split (what actually lands in AdSense); CPM columns are grossed back up at roughly 1.9× to show the advertiser-side price.

Assumptions and caveats

Frequently asked questions

What is the YouTube RPM for education and how-to channels in 2026?

Education and how-to YouTube channels earn an RPM of $4.00–$10 per 1,000 long-form views in 2026, with a typical figure near $6.00. That means 100,000 views pays roughly $600 in ad revenue. Shorts in the same niche pay about $0.05 per 1,000 views.

Which option pays the most in the education and how-to rpm and earnings benchmarks table?

1,000,000 views, at $6,000. That row represents the strongest case in this dataset, so use it as an upper bound rather than an expectation.

What is a realistic low-end figure?

Shorts RPM at $0.05 (per 1,000 Shorts views). Plan your costs so the low end still works, then treat anything above it as upside.

Why do the numbers vary so much?

The spread between the highest and lowest row is about 120000×. Audience geography and niche and advertiser demand explain most of that gap — see the drivers section above for the full list.

Where do these numbers come from?

Figures blend YouTube Partner Program payout data, public creator disclosures for education and how-to channels, and anonymised submissions to the RevenueLab YouTube Revenue Calculator. RPM is post-split (what actually lands in AdSense); CPM columns are grossed back up at roughly 1.9× to show the advertiser-side price.

How can I estimate my own number instead of using a benchmark?

Use the YouTube Revenue Calculator on RevenueLab — it takes your own inputs and returns a figure specific to your setup, which is always more accurate than a published range.

Model your own numbers

Related reading

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Last updated 2026-08-21.