Reference · updated 2026-08-27
AI agent pricing
What the models, tools, and platforms behind AI agents actually charge. Every number on this page was read off the vendor's own pricing page and links back to it. Nothing is estimated.
Most cost questions get answered with a single number. A real bill has four layers, and the model is usually the smallest one.
The one number people ask for
$0.0037
per conversation, for inference
Anthropic's own worked example: 10,000 customer-support conversations for about $37 in total. About 3,700 tokens per conversation on Claude Haiku 4.5 at $1/$5 per 1M. Source, checked 2026-08-27.
That figure is real and it is also the reason cost conversations go wrong. Inference is cheap. The invoice that surprises people is built from the three layers above it.
Layer 1
The model
Charged per million tokens, in and out. Every agent pays this whatever sits on top of it. Output costs several times input at every vendor, so an agent that writes long answers costs more than one that reads long documents.
| Vendor | Model | Price | Unit | Notes | Link |
|---|---|---|---|---|---|
| Anthropic | Claude Haiku 4.5 | $1 | per 1M input tokens | Output is $5 per 1M. The cheapest current Claude tier, and the one Anthropic uses in its own support-agent cost example. | source |
| Anthropic | Claude Sonnet 5 | $2 | per 1M input tokens | Output is $10 per 1M. Anthropic states the $2/$10 launch pricing is now standard and the scheduled rise to $3/$15 will not happen. | source |
| Anthropic | Claude Opus 5 | $5 | per 1M input tokens | Output is $25 per 1M. | source |
| Anthropic | Claude Fable 5 | $10 | per 1M input tokens | Output is $50 per 1M. Top tier. | source |
| OpenAI | gpt-5-nano | $0.0500 | per 1M input tokens | Output is $0.40 per 1M. The cheapest row on the page. | source |
| OpenAI | gpt-5.6-luna | $0.20 | per 1M input tokens | Output is $1.20 per 1M. Cached input is $0.02. | source |
| OpenAI | gpt-5.6-terra | $2 | per 1M input tokens | Output is $12 per 1M. Cached input is $0.20. | source |
| OpenAI | gpt-5.6-sol | $4 | per 1M input tokens | Output is $20 per 1M. The page states this promotional rate runs at least through 2026-11-21, so treat it as temporary. | source |
| Gemini 2.5 Flash-Lite | $0.10 | per 1M input tokens | Output is $0.40 per 1M. Audio input is priced higher at $0.30. | source | |
| Gemini 3.5 Flash-Lite | $0.30 | per 1M input tokens | Output is $2.50 per 1M. | source | |
| Gemini 3.7 Flash | $0.75 | per 1M input tokens | Output is $3.75 per 1M. The page dates a rise to $1.50 / $7.50 on 2027-01-01. | source | |
| Gemini 2.5 Pro | $1.25 | per 1M input tokens | Output is $10 per 1M including thinking tokens, and both roughly double above a 200k-token prompt. | source |
Rows are the tiers a build actually chooses between. Each vendor's page carries the full model list.
Layer 1, continued
The multipliers that move the bill
These matter more for agents than for other AI work. An agent re-sends its system prompt and tool definitions on every single turn, so the same tokens get paid for over and over unless caching is on.
| Vendor | Item | Value | Unit | Notes | Link |
|---|---|---|---|---|---|
| Anthropic | Prompt cache read | $0.10 | multiple of base input price | A cache hit costs 10% of standard input. Writes cost 1.25x (5-minute) or 2x (1-hour), so a 5-minute cache pays for itself after one read. | source |
| Anthropic | Batch API | $0.50 | discount on input and output | 50% off both directions, for work that does not need an answer in real time. Not available for interactive sessions. | source |
| Anthropic | Web search tool | $10 | per 1,000 searches | Billed on top of tokens. An agent that searches on every turn adds a line item most cost models miss. | source |
| Anthropic | US-only inference (data residency) | $1.10 | multiplier on all token pricing | Pinning inference to the US adds 10% across input, output, and cache. | source |
Decay
What is scheduled to stop being true
Published prices are not permanent, and several current ones carry a date on them. This is the part worth checking before you build a budget on a number you read three months ago.
Claude Sonnet 5 stays at $2 / $10 per 1M. The rise to $3 / $15 that was scheduled for 2026-09-01 has been cancelled and the launch rate is now standard.
source, checked 2026-08-27gpt-5.6-sol is on promotional pricing, stated as available at least through 2026-11-21.
source, checked 2026-08-27Gemini 3.7 and 3.6 Flash roughly double: input $0.75 to $1.50, output $3.75 to $7.50, with caching and storage rising in step.
source, checked 2026-08-27Claude 4.7 and later use a newer tokenizer that produces roughly 30% more tokens for the same text. Per-token prices did not change, but cost per task is not comparable across the 4.6 / 4.7 line.
source, checked 2026-08-27Layer 2
The platform, and its unit
Read the middle column first. What a platform meters decides what happens to your bill when volume grows: a per-seat plan barely moves, a per-task or per-conversation plan moves with every extra customer. Two platforms with the same monthly price can differ by an order of magnitude at scale purely because of this.
| Vendor | Plan | Metered by | Price | Notes | Link |
|---|---|---|---|---|---|
| Zapier | Professional | per task | $19.99per month, from | Printed as a starting price; the real figure moves with your task tier. Team starts at $69 per month for 25 users. A free tier gives 100 tasks a month. | source |
| Make | Core | per credit (one module action) | $12per month | At the default 10,000 credits a month. Pro is $21 and Teams $38 at the same volume. Free tier allows up to 1,000 credits a month with no time limit. | source |
| n8n | Starter | per full workflow execution, not per step | not published | Priced in euros even from a US request (EUR 20 a month billed annually, 2,500 executions), so no verified USD figure exists to quote. Metering per whole execution rather than per step is the notable part: a 30-step workflow costs the same as a 3-step one. | source |
| Lindy | Plus | per seat plus a shared credit pool | $29.99per user, per month | Includes 3,000 credits per user. Pro is $99.99 and Max $199.99 per user. No free tier. | source |
| Gumloop | Pro | per credit, plus an 8% orchestration fee | $37per month, from | The 8% fee stacks on credit consumption, so the sticker is not the effective rate. Only two tiers exist and there is no free plan. | source |
| Salesforce | Agentforce, per action | per action, via Flex Credits | $0.10per action | Derived from figures printed on the same page: an action is 20 Flex Credits and credits are $500 per 100,000. Voice actions are 30 credits, so $0.15. A per-conversation option is $2. | source |
| Microsoft | Copilot Studio | per Copilot Credit | $0.0100per credit, pay as you go | A prepaid pack is $200 a month for 25,000 credits. Microsoft's own Azure pricing page renders this rate as a dash; the figure is confirmed in the Copilot Credits Guide. | source |
| Gemini Enterprise Agent Platform, compute | per vCPU-hour | $0.0850per vCPU-hour | Pure consumption, no seats and no tiers, with the first 50 vCPU-hours a month free. This product was called Vertex AI Agent Builder; the name no longer appears on the pricing page, so older comparisons are stale. | source | |
| Relevance AI | Self-serve plans | Actions and Vendor Credits | not published | No self-serve price is published at all; the pricing page is a single Enterprise card with a sales contact. Only top-up rates remain documented, at $80 per 1,000 Actions. | source |
| CrewAI | Paid tiers | per workflow execution | not published | Nothing purchasable sits between the free tier (50 executions a month) and a custom enterprise quote. There is no published middle. | source |
Three of these vendors will not tell you the price.
Relevance AI has reduced its public pricing page to a single enterprise card with a sales contact. CrewAI publishes a free tier and a custom quote with nothing purchasable in between. Salesforce prints unit rates but gates every plan behind a form. That is worth recording, because a price you cannot see before a sales call is a price you cannot compare.
Layer 3, voice
Where the headline number lies
If your agent speaks, this is the layer that decides the bill, and it is the one most often quoted wrong. A voice platform's advertised per-minute rate usually covers the platform alone. Bland states exactly that about its competitors on its own pricing page.
| Vendor | Product | Price | Unit | What it covers | Link |
|---|---|---|---|---|---|
| Vapi | Vapi hosting (Build) | $0.0500 | per call minute | Platform fee only. The page states hosting excludes model provider costs: speech-to-text, the model, and speech synthesis are billed at cost, and transport is charged by the provider. | source |
| Retell AI | Voice infrastructure | $0.0550 | per call minute | Retell is unusual in publishing a per-minute rate for every component, which is why its stack is the one that resolves exactly. | source |
| Retell AI | Speech synthesis | $0.0150 | per call minute | Rises to $0.040 per minute if you pick ElevenLabs voices. | source |
| Bland AI | Start plan | $0.14 | per talk minute | Model, speech-to-text and speech synthesis are included with no token charges. Telephony is billed separately. The only vendor here whose headline number is close to the real one. | source |
| ElevenLabs | Agents, additional minute | $0.0800 | per call minute | Speech synthesis, speech-to-text and retrieval are included. The page states the model and any telephony are billed separately on top, both at cost. | source |
| Deepgram | Voice Agent API (Standard) | $0.0560 | per call minute | Bundles speech-to-text, model and speech synthesis orchestration, billed on websocket connection time. The page dates a rise to $0.075 on 2026-09-12. Telephony is not included. | source |
The parts underneath
Whether a platform bundles these or passes them through, somebody pays them. Watch the unit on speech synthesis: it is charged per character, not per minute, which is the reason no honest all-in per-minute quote exists.
| Vendor | Component | Price | Unit | Notes | Link |
|---|---|---|---|---|---|
| Deepgram | Nova-3 streaming speech-to-text | $0.0048 | per minute | Pay-as-you-go rate. Listening is the cheapest part of a voice agent by a wide margin. | source |
| Deepgram | Aura-2 speech synthesis | $0.0300 | per 1,000 characters | Charged per character, not per minute. This is the line that stops any stack from producing a clean per-minute number, because it depends on how much the agent says. | source |
| Twilio | US local inbound voice | $0.0085 | per minute | Outbound US is $0.0140. SIP trunking, which is the rate most voice-AI platforms actually hit, is $0.0040 in both directions. | source |
| Twilio | US local phone number | $1.15 | per month | Toll-free is $2.15 per month. A fixed cost per number, regardless of call volume. | source |
| OpenAI | gpt-realtime-2.1 audio | $32 | per 1M audio input tokens | Audio output is $64 per 1M. OpenAI publishes NO per-minute price for realtime voice; it is token-billed only. Any "$X per minute for OpenAI Realtime" figure is somebody else's conversion. | source |
The arithmetic
One five-minute call
Priced from the tables above. Two of these resolve to a real number. Two do not, and that is the finding: when speech synthesis bills per character and the model bills per token, the vendor cannot tell you what a call costs until it has happened.
resolves exactly
Their own default calculator, bring-your-own SIP
Voice infrastructure $0.055 + model $0.04 + speech synthesis $0.015 per minute, telephony $0 on your own SIP. $0.11 per minute.
sourceresolves exactly
Premium voices and a top-tier model
Voice infrastructure $0.055 + ElevenLabs synthesis $0.040 + GPT-5.5 $0.16 + Twilio $0.015. $0.27 per minute, or roughly 2.5x the default.
sourceresolves exactly
Start plan, Twilio local inbound
$0.14 per minute covering model, speech-to-text and synthesis, plus about $0.04 of telephony across five minutes.
sourcefloor only, cannot resolve
Agents, additional minutes
$0.08 per minute for the platform. The model and telephony are billed at cost on top, so the total depends on which model you attach.
sourcefloor only, cannot resolve
Build plan, components at cost
A verifiable FLOOR, not a price: hosting $0.25 + speech-to-text $0.024 + telephony $0.043. Speech synthesis is per character and the model is per token, so neither can be resolved without knowing how much the agent says.
sourceThe same call runs from about $0.55 to $1.35 on one vendor alone, depending only on which voice and which model you attach. Before comparing two platforms, check you are comparing the same stack.
Layer 4
The people
The largest line on most AI budgets, and the one where published numbers are least comparable. A median wage, a total-compensation figure including equity, and a contractor day rate are three different measurements that all get quoted as "what an AI engineer costs". Read the measure column before the number.
| Source | Role | Measure | Figure | Notes | Link |
|---|---|---|---|---|---|
| US Bureau of Labor Statistics | Data Scientists (SOC 15-2051) | median annual wage | $120,230per year | The 75th percentile is $158,880. Wages only: apply the employer cost loading below for a real comparison. | source |
| US Bureau of Labor Statistics | Software Developers (SOC 15-1252) | median annual wage | $135,980per year | The baseline AI roles get compared against. There is NO BLS occupation code for "AI Engineer", so any figure attributed to BLS under that title is invented. | source |
| US Bureau of Labor Statistics | Employer cost loading | multiplier on wages | $1.43x wages, for total employer cost | Wages are 69.9% of employer cost and benefits 30.1%. A $120,230 salary costs roughly $172,000 to employ. | source |
| Levels.fyi | Machine Learning Engineer | median total compensation | $279,000per year | Not comparable to a BLS wage, because it includes equity. The same site on the same day puts "AI Engineer" at $154,000: an 81% gap between two titles for similar work. | source |
| YunoJuno | AI Engineer, freelance | average contract rate | $70per hour | Machine Learning Engineer books at $62. The report is titled 2026 but runs on 2024 to 2025 data. | source |
| Arc.dev | AI and ML engineering, freelance | average SENIOR contract rate | $110per hour, low end of range | The range runs to $190. Read the column header: this is senior-only, not a market midpoint, which is most of why it sits about 2x above booking data. | source |
| Clutch | AI development firms, US and Canada | agency hourly band | $50per hour, low end of band | The band runs to $99 and the modal global rate is $24 to $49. The same directory shows an identical band for general software development. | source |
| Clutch | Average AI project | project total | $120,594.55per project | The most common range is $10,000 to $49,999. The comparable figure for general software projects is $132,480.29, which is HIGHER. At directory level there is no AI premium. | source |
There is no BLS code for "AI Engineer"
The nearest occupations are Data Scientists, Software Developers, and Computer and Information Research Scientists. Any figure attributed to the Bureau of Labor Statistics under the title "AI Engineer" was invented, because the category does not exist.
Rate guides and booking data differ by about 2x
Survey-based guides put freelance AI work at $110 to $190 an hour, but that column is senior-only. Platforms publishing what contracts actually booked at report $62 to $78. Both are real; they measure different populations.
At agency level there is no AI premium
The same directory shows an identical hourly band for AI firms and general software firms, and a slightly LOWER average project total for AI work. That contradicts most of what is written on the subject.
Context
Whether it pays off
Cost is only half of the question. Named research on returns, with the sample size and the date attached, and with the contested findings marked as contested rather than left out.
In AI work, algorithms are about 10% of the effort, technology about 20%, and people, process and organisation about 70%. Among those surveyed, 74% named a shortage of AI talent as a constraint and 63% said scaling costs were hard to control.
source, checked 2026-08-27Only 25% of AI initiatives have delivered the return that was expected of them, and only 16% have scaled across the enterprise.
source, checked 2026-08-27Over 40% of agentic AI projects will be cancelled by the end of 2027.
Read with care. This is a webinar poll, not a controlled survey. Read it as a signal about expectations, not a measured failure rate.
source, checked 2026-08-27Widely quoted as finding that 95% of organisations get zero return from generative AI. The same report found externally built systems reached deployment about twice as often as internally built ones.
Read with care. Contested, and included mainly so the caveat travels with the number. The document is labelled preliminary findings, is not peer reviewed, and its own limitations section concedes the build-versus-buy split rests on interviews rather than market data. The methodology repeated in the press, "150 interviews and 350 employee surveys", is a misquote of the figures above.
source, checked 2026-08-27How to read a quote
When two quotes for the same agent differ by an order of magnitude, they are usually pricing different layers. Ask which of these four a number covers.
-
Layer 1
Inference
Per million tokens, priced above. Predictable, and usually the smallest line.
-
Layer 2
Platform and orchestration
A seat, a task, a credit, or a conversation, depending on the vendor. The unit matters more than the headline price, because it decides what happens to your bill when volume grows.
-
Layer 3
Everything the agent touches
Tool calls, search, telephony if it speaks, and the systems it writes into. Anthropic bills web search at $10 per 1,000 searches on top of tokens; an agent that searches every turn adds a line most models miss.
-
Layer 4
The people
Building it, connecting it to your systems, and keeping it working when a prompt, a model, or an API changes underneath it. Priced above, and the largest line on most budgets. BCG puts algorithms at about 10% of AI effort and people, process and organisation at about 70%.
Method
Every figure was read off the vendor's own published pricing page on the date shown beside it, and each row links back to that page so you can check it. Nothing on this page is estimated, remembered, or averaged from third-party summaries.
Where a vendor does not publish a number, the index says "not published" instead of guessing. That is a finding in itself: a price you cannot see before a sales call is a price you cannot compare.
Prices move. This page carries the date it was last checked at the top, and the section above lists the changes vendors have already dated. If you are reading this well after 2026-08-27, follow the source links before you rely on a number.
Take the data. Every row on this page is downloadable as CSV or JSON, including the source URL and check date for each figure, under CC BY 4.0. Attribution with a link is enough.
Questions
How much does it cost to run an AI agent?
Why do two quotes for the same AI agent differ so much?
Does prompt caching really matter for agents?
Which published AI prices are about to change?
How is this index kept accurate?
Working out what yours would cost?
The layers above tell you what the parts cost. What they cannot tell you is which workflow in your business is worth pointing an agent at first. That is what the free plan is for.