> For the complete documentation index, see [llms.txt](https://docs.atlas-ai.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.atlas-ai.org/x402-protocol/pricing.md).

# Pricing Philosophy

## What Is Knowledge Worth?

Traditional economics struggles with knowledge pricing:

* **Zero marginal cost** to share (unlike physical goods)
* **Non-rival** — your use doesn't diminish mine
* **Hard to preview** — you don't know value until you have it

x402 approaches this differently: **price reflects curation cost, not information scarcity.**

***

## The Curation Premium

### Raw Information Is Cheap

Anyone can scrape the web. AI can generate infinite text. Raw data is abundant and becoming more so.

### Curated Knowledge Is Expensive

What's genuinely scarce:

* **Human judgment** — Deciding what matters
* **Verification** — Confirming accuracy
* **Organization** — Structuring for retrieval
* **Context** — Understanding implications
* **Time** — Years of accumulated expertise

**x402 prices this curation layer, not the underlying information.**

***

## Pricing Tiers Explained

### Micro Tier — $0.001

**Use case:** Existence checks, quick lookups

*"Does this ATLAS know anything about prediction markets?"*

Returns: Yes/no with concept count, no details

### Standard Tier — $0.01

**Use case:** Concept definitions, basic queries

*"What is Mana in prediction market context?"*

Returns: Concept definition, related concepts, 2-3 key insights

### Deep Tier — $0.10

**Use case:** Comprehensive topic analysis

*"Explain the relationship between prediction markets and information aggregation"*

Returns: Full concept graph, all insights, source content, action items

### Premium Tier — $0.25

**Use case:** Expert synthesis, multi-domain queries

*"How do prediction market dynamics relate to epistemology and collective intelligence?"*

Returns: Cross-domain synthesis, novel connections, comprehensive analysis

***

## Dynamic Pricing Factors

Base prices adjust based on:

### Query Complexity

* More concepts involved = higher price
* Cross-domain queries = premium
* Temporal analysis (trends) = premium

### Knowledge Rarity

* Common concepts = base price
* Niche expertise = multiplier
* Exclusive insights = premium

### Freshness

* Recent additions = premium
* Evergreen content = standard
* Historical queries = discount

### Compute Intensity

* Simple retrieval = base
* Graph traversal = moderate
* AI synthesis = premium

***

## Comparison: x402 vs Alternatives

### vs. Web Scraping

| Factor       | Web Scraping | x402             |
| ------------ | ------------ | ---------------- |
| Cost         | $2-10/query  | $0.01-0.25/query |
| Time         | 30-60 sec    | <2 sec           |
| Reliability  | Variable     | Verified         |
| Signal/Noise | Low          | High             |

### vs. Subscription APIs

| Factor      | Subscription   | x402             |
| ----------- | -------------- | ---------------- |
| Commitment  | Monthly fee    | Pay-per-use      |
| Flexibility | Fixed access   | Query-specific   |
| Discovery   | Limited        | Open marketplace |
| Efficiency  | Pay for unused | Pay for value    |

### vs. Free Content

| Factor         | Free         | x402         |
| -------------- | ------------ | ------------ |
| Quality        | Variable     | Curated      |
| Reliability    | Uncertain    | Verified     |
| Sustainability | Ad-supported | Direct value |
| Incentives     | Engagement   | Quality      |

***

## Setting Your Prices

As a knowledge provider, you control:

### Base Multiplier

Set your knowledge's base value relative to standard pricing:

* 0.5x = Budget tier
* 1.0x = Standard
* 2.0x = Premium expertise
* 5.0x = Rare/exclusive

### Domain Premiums

Different knowledge areas can have different multipliers:

* General knowledge = 1.0x
* Professional expertise = 2.0x
* Proprietary research = 5.0x

### Access Restrictions

* Public = anyone can query
* Allowlist = approved agents only
* Private = no x402 exposure

***

## Economic Sustainability

### For Knowledge Providers

Monthly revenue potential:

| Queries/Day | Avg Price | Monthly Revenue |
| ----------- | --------- | --------------- |
| 10          | $0.05     | $15             |
| 100         | $0.05     | $150            |
| 1,000       | $0.05     | $1,500          |
| 10,000      | $0.05     | $15,000         |

As agent economy grows, query volume scales.

### For Knowledge Consumers

Cost comparison for 1,000 queries/month:

| Method          | Cost             |
| --------------- | ---------------- |
| x402 Standard   | $10              |
| x402 Deep       | $100             |
| Web scraping    | $2,000-10,000    |
| Manual research | Priceless (time) |

***

## The Virtuous Cycle

```
Better curation → Higher quality responses
        ↓
Higher prices justified → More revenue
        ↓
More incentive to curate → Better curation
```

x402 creates alignment:

* **Providers** incentivized to improve quality
* **Consumers** get better results
* **Ecosystem** improves overall


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.atlas-ai.org/x402-protocol/pricing.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.