The AI Advertising Pricing Index (2026)

Every price in this index comes from a vendor's official pricing page, fetched directly, or from independent third-party reporting where a vendor does not publish pricing. We do not publish figures from private vendor proposals shared with us in confidence, even where we have seen them; where a vendor's pricing is not public, we say so rather than estimate. We also did not use secondhand review sites as a pricing source unless a vendor's own page was unavailable.

We grouped products into four sets: AI app builders (v0, Replit, Lovable, Bolt.new), AI coding agents (Amp, Cursor, Claude Code), direct AI advertising competitors (Ploy.ai, GoMarble, Ryze, HyperFX, AdCreative.ai, Sprites, Smartly.io), and the enterprise platforms we have been evaluated against directly in customer deals (Pixis, Kovva). The first two groups establish the pattern across AI-native software generally; the second two are who we actually compete against for a customer's business. Those 16 vendors, plus Synter itself, make up the 17 products in the index.

Across all 17 products, only Synter and Amp let a customer pay for usage without first committing to a monthly plan. Amp has no permanent free tier for new users as of this writing. Synter is the only product in the index that combines a permanent, quantified free allowance with zero required commitment.

The Economist's Big Mac Index works because the burger is the same everywhere, so its price reveals what each economy actually charges for an identical good. AI agents need the same instrument. So we define one standard unit and price it across the industry from published rates only.

Read the index bottom-up and the finding is stark: on 13 of the 17 products audited, the price of one completed agent task cannot be computed from public information, and on three of them not even the price of the door is public. A unit of agent work is only priceable at all on usage-based products, and only Synter posts the finished task itself as the unit. That is the entire argument for usage pricing in one table: you cannot comparison-shop work you cannot price.

Methodology: published vendor pricing as of July 2026 only, per the audit table below. The standard task profile (40 calls, 400K tokens, 3:1 input:output) is stated so anyone can recompute or contest it; where a vendor publishes neither a unit price nor consumption rates, the index value is reported as not computable rather than estimated. We will reprice this index as vendors change their pricing.

Subscriptions hide the unit of work; usage pricing exposes it. So here is the comparison that subscriptions make impossible: the published price of one unit of AI work, normalized across the products that publish one at all. A Synter credit is 2.5 cents ($25 per 1,000), and every agent action has a posted credit price, so the cost of a finished task is knowable before you run it.

And because Synter meters per action, the per-task math is public. These are the posted rates, in credits and dollars:

Yes, a Synter credit costs more than the raw tokens underneath it. That spread is the point: it is the price of everything between a language model and a launched campaign. Five dollars buys a campaign built, checked against your accounts, and shipped through official platform APIs with an approval trail. The raw-token route buys the model's attention; the harness, the integrations to 20+ ad platforms, and the accountability layer are left as an exercise for your engineering team. Compare that five dollars to what the same launch costs in a media buyer's hour, or to a month of a subscription seat that ships no work at all, and the unit economics of paying per task explain themselves.

Zoom out from any single vendor and a pattern holds across enterprise AI advertising platforms: pricing is either per seat, per month, on top of a required subscription, or not published anywhere and gated behind a sales call. Smartly.io, one of the category's largest incumbents, publishes no pricing page at all; third parties report a monthly floor in the thousands of dollars, billed as a percentage of managed ad spend. Kovva, a newer entrant, gates access behind an application form with no public pricing disclosed.

Synter's pricing does not depend on team size or ad spend: $0 in required commitment, then $25 per 1,000 credits only for the work the agents actually do, with execution across every core ad platform from the first day.

Pricing is half the comparison. The other half is what a platform's AI agents can actually do inside an ad account. Google's official Google Ads MCP server, released in 2026, is read-only: it can analyze a campaign but cannot pause it, change a bid, or launch an ad. Synter's MCP server executes campaign changes on 12 ad platforms, including Google, Meta, LinkedIn, TikTok, Reddit, X, and Microsoft, with reporting across 19 ad platforms in total. See our full MCP server comparison and Google Ads MCP servers compared for the full breakdown.

A subscription is a bet a customer makes before they know whether they will use the product. A purchased credit is a bet they have already placed: they bought it because they intend to use it. That difference shows up in usage data, not just in psychology, which is part of why so few software companies choose pure usage-based pricing even though it is better for the customer.

Every action a Synter agent takes is logged, budgeted, and approvable. Campaign changes carry an audit trail, manual credit purchases are capped at $10,000, automatic top-ups respect a customer-set monthly limit, and high-impact actions can require human approval. Synter builds these controls because its own agents move real advertising budgets every day, not as an afterthought.