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 We do not publish figures from private vendor proposals shared with us in confidence, even where we have seen them; where a vendor's pricing is not public, we say so rather than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.

The products differ most in how clearly they disclose the entry price and included usage. Synter combines a permanent, quantified no-card Free allowance with a published pay-as-you-go rate and a flat, published fee on managed ad spend.

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 at the pay-as-you-go rate ($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:

Five dollars buys a campaign built, checked against your accounts, and shipped through official platform APIs with an approval trail. Launching requires a card on file. Price that same task as raw model compute alone and it runs about $2.40 on Claude Sonnet or $4.00 on Opus, before you have written a line of the harness. That is the point: a finished Synter task costs in the same range as the underlying model tokens, and everything between a language model and a launched campaign, the agent loop, the integrations to 20+ ad platforms, and the accountability layer, is already included rather than 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 publishes every number. Free starts at $0 with no card. Usage is pay as you go at $25 per 1,000 credits ($0.025 per credit). Managed ad spend carries a flat 3% monthly fee per connected account, and it starts only after Synter's first successful write on that account. Agency and Enterprise pricing is custom.

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.

Metering makes the unit of agent work visible even when credits are included with a signup. Reporting, analysis, and agent chat are free. Customers can estimate execution volume up front, start on the free one-time $25 usage credit, then top up only when they need more.

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.