Credits Usage Guide
Overview
Your usage on the platform is measured in credits, which reflect the amount of AI processing you consume. Credits are primarily calculated based on the number of input tokens and output tokens processed by AI models during a request. In addition to token usage, credits are also consumed by other platform capabilities, including:
- Knowledge Base operations (e.g., retrieval, vector search)
- Built-in tools such as:
- File parsing
- URL Crawling
- Text extraction Each of these operations has its own credit cost depending on the processing required.
This document explains how credits are calculated and lists the credit values for all supported models.
What Are Tokens?
Tokens represent pieces of text used by AI models.
- 1 token ≈ 4 characters
- ~75 tokens ≈ 1 sentence
- ~1000 tokens ≈ 750 words
Models charge separately for:
- Input tokens (your request)
- Output tokens (AI response)
How Credits Are Calculated
Input Credits = (input_tokens / 1000) × input_credit_per_1k
Output Credits = (output_tokens / 1000) × output_credit_per_1k
Total Credits = Input Credits + Output Credits
Credits ensure consistent and predictable billing across models and providers.
KnowledgeBase Credits
The Knowledge Base credit consumption uses a different mechanism. Credits are consumed for:
1. URL-based Knowledge Base
| Component | Description | Credits |
|---|---|---|
| URL Crawl | Cost applied per URL crawled | 5 |
| Embedding Cost | Text extracted from pages is embedded | Based on embedding model credits consumption |
2. Document-based Knowledge Base
| Component | Description | Credits |
|---|---|---|
| Document Page | Cost applied per page of uploaded document | 6 |
| Embedding Cost | Text extracted from pages is embedded | Based on embedding model credits consumption |
Embedding credits follow the same table as models in the Embedding section below.
Supported Models & Credits
Below are the credit tables grouped by provider within tabs.
- OpenAI
- Anthropic
| Model | Input Credits / 1K Tokens | Output Credits / 1K Tokens |
|---|---|---|
| chatgpt-4o-latest | 5 | 15 |
| gpt-4o | 2.5 | 10 |
| gpt-4o-mini | 0.15 | 0.6 |
| gpt-5 | 1.25 | 10 |
| gpt-5-mini | 0.25 | 2 |
| gpt-5-nano | 0.05 | 0.4 |
| text-embedding-3-small | 0.13 | 0 |
| text-embedding-3-large | 0.02 | 0 |
| text-embedding-ada-002 | 0.10 | 0 |
| Model | Input Credits / 1K Tokens | Output Credits / 1K Tokens |
|---|---|---|
| claude-opus-4-1-20250805 | 15 | 75 |
| claude-sonnet-4-5-20250929 | 6 | 22.5 |
| claude-haiku-4-5-20251001 | 1 | 5 |
| Model | Input Credits / 1K Tokens | Output Credits / 1K Tokens |
|---|---|---|
| gemini-2.5-pro | 2.5 | 15 |
| gemini-2.5-flash | 0.3 | 2.5 |
| gemini-2.5-flash-lite | 0.1 | 0.4 |
| gemini-2.0-flash | 0.1 | 0.4 |
| gemini-2.0-flash-lite | 0.075 | 0.3 |
| gemini-embedding-001 | 0.15 | 0 |
Summary
- Credits standardize costs across different AI providers.
- Each model defines separate rates for input and output tokens.
- Total credits = input credits + output credits.
- These tables ensure transparent and predictable usage billing.