Embedding Cost Calculator: 10M Token Vectorization

Complete Analysis: 10,001,000 tokens for text-embedding-3-small
🔍 10,000,000 Embedding Tokens

Complete analysis of pricing, performance, and use cases for OpenAI's text-embedding-3-small model with 10,000,000 Embedding Tokens.

$20.012000 (rounded ~ 20.01) Total Cost
10,001,000 Total Tokens
5 hours, 36 minutes, 42.00 seconds Processing Time
495 Effective Tokens/Sec
ℹ️ Note: Calculation represents bulk volume across multiple requests; single-request limit is 32,768 tokens.

Select AI Model

Text Embedding 3 Small
OtherMax Context: 32,768 tokens
Input: $2.000000 / 1M
Output: $12.000000 / 1M

Calculate Token Costs

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Provider-specific multipliers applied after all calculations
Enable for Haiku 4.5 hard cap bypass
Select platform to enforce context limits
Number of requests (max 1M). Summary view auto-enabled >10k.
Multiply total cost by quantity for project budgeting
$20.012000Total Cost
$20.000000Input Cost
$0.012000Output Cost
$0.000000Unit Cost
$0.000000Search Cost
$0.000000Request Fee
$0.000000Tool Fee
$0.000000Code Execution
10,001,000Total Tokens
$0.002001Cost per 1K
499,750Tokens per $

Click Recalculate to update after making changes

Calculate Processing Speed

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336m 42sProcessing Time
500Tokens/Second
200msTime to First Token
495Effective Speed

Model Comparison

Select a model to see comparisons with competitors.

Model Information

Select a model to see detailed information.

🔄 Advanced Options

⚡ Optimization
0%
Flat fee per session (e.g., $0.03 for Code Interpreter)
Hourly storage fee for cached data (Pro: $4.50/1M/hr, Flash: $1.00/1M/hr)
First 50 hours free, $0.05/hour after (reset at 00:00 UTC)
🧠 Specialized Modes
Enable Thinking Mode (Google models)
Manual thinking tokens (billed at output rate, disabled by default)
Adaptive thinking token estimation for DeepSeek models
30% output surcharge (Vertex AI priority)
Billed at output rate × reasoning multiplier
Global 2x multiplier for priority processing
Enable Reasoning/Thinking Mode (DeepSeek R1, Grok Deep Reason)
Enable Agentic Swarm
🔧 Automated Service Fees
Enable for DeepSeek V4 ($0.01 per 1M tokens)
Enable code execution (adds $0.05 flat fee)
$0.01 per query (auto-applied based on Search Queries input)
🤖 xAI Agent Tools (Unified $5.00/1k)
Real-time X data access calls
Standard internet search calls
Python sandbox execution calls (overrides flat fee if set)
📚 xAI RAG Tools (Unified $2.50/1k)
File search tool access
Collections/RAG knowledge base access - aggregated with File Search at $2.50/1k
ℹ️ Updated xAI Tool Pricing: Agent tools (web, X, code) at $5.00/1k calls. RAG tools (collections, file) at $2.50/1k calls. Integer code_execution_calls overrides boolean.
🎤 Realtime Audio & Deep Research
Enable Deep Research ($2.00/$8.00 rates)
Session length for billing ($0.01 per minute, rounded up)
Active speech time within session
📄 Mistral AI - Unit-Based Options
Number of pages to process with OCR (tiered pricing auto-applied)
Enable HTML table reconstruction surcharge
Duration-based audio processing (not token-based)
Enable speaker diarization (Voxtral models only)
Enable context biasing (Voxtral models only)
🔬 Research & Citation
Enable research tier pricing ($2.00/$8.00 + $0.005/query)
Enable reasoning with 1,000 token floor ($0.015 min)
Fee per source cited when research mode is enabled
⚙️ Performance Tuning
Low = Fast
High = Creative
📊 Advanced Cost Breakdown

text-embedding-3-small OpenAI

$20.012000 (rounded ~ 20.01)
Total Cost
⚠️ Note: Calculation represents bulk volume across multiple requests; single-request limit is 32,768 tokens.
📊 Batch API
👁️
Vision/Images
✗ Not Available
🎧
Audio Processing
✗ Not Available
🎥
Video Analysis
✗ Not Available
🔧
Tool Usage
✗ Not Available
📄
OCR Support
✗ Not Available
📊
Batch API
✗ Not Available
⚡
Caching
✗ Not Available

💰 Total Cost Calculation

Base Cost (No Optimizations) $20.012000 (rounded ~ 20.01) Input: $20.000000
Output: $0.012000 (rounded ~ 0.01)
Optimized Cost $20.012000 (rounded ~ 20.01) Input: $20.000000
Output: $0.012000 (rounded ~ 0.01)
Unit: $0.000000
Fees: $0.000000

Detailed Cost Analysis

For 10,000,000 input tokens and 1,000 output tokens:

  • Input Cost: $20.000000
  • Output Cost: $0.012000 (rounded ~ 0.01)
  • Total Cost: $20.012000 (rounded ~ 20.01)
  • Cost per 1K tokens: $0.002001 (rounded ~ 0.00)
  • Tokens per dollar: 499,750 tokens
  • Context Window: 32768 tokens

Speed & Performance Analysis

With a processing speed of 500 tokens per second and 200ms time to first token:

  • Processing Time: 5 hours, 36 minutes, 42.00 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 500 tokens/second
  • Effective Throughput: 495 tokens/second (temperature-adjusted)

Best Use Cases

Search enginesRecommendation systemsRAG

Large-Scale Vector Database Population

Calculates costs for creating embeddings for search, recommendation, and RAG systems at massive scale.

Embedding Scale

  • Tokens: 10,000,000 to embed
  • Model: text-embedding-3-small ($0.02/1M)
  • Output: 0 (embeddings only)
  • Batch: Supported (no discount for embeddings)
  • Use Case: Populating vector database

Frequently Asked Questions

How accurate are these AI model cost calculations?
Our calculations are based on official pricing from each provider (Google, OpenAI, Anthropic, Meta, xAI, Perplexity, DeepSeek, Mistral) and are updated regularly. We account for all factors including multimodal inputs, caching discounts, batch API pricing, tool usage multipliers, OCR processing, audio minutes, silence fees, and research mode pricing.
What is the YemHub AI Calculator Tool?
The YemHub AI Calculator is the most comprehensive tool for estimating costs and comparing performance metrics across 44+ AI models. It calculates token-based pricing, analyzes multimodal processing, accounts for state-dependent pricing (context cliffs, tiered tunnels), and provides optimization recommendations.