AI shopping assistant unit economics calculator

Complete Analysis: 2,300 tokens for gpt-5-mini
🖼️ 5 Images ⚡ 70% Cached

Complete analysis of pricing, performance, and use cases for OpenAI's gpt-5-mini model with 5 Images, 70% Cached.

🖼️ Multimodal Input ⚡ Caching Optimized (up to 90% savings)
$0.077500 (rounded ~ 0.08) Total Cost
2,300 Total Tokens
5.00 seconds Processing Time
472 Effective Tokens/Sec

Select AI Model

Gpt 5 Mini
OpenAIMax Context: 400,000 tokens
Input: $5.000000 / 1M
Output: $25.000000 / 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
$0.077500Total Cost
$0.007500Input Cost
$0.020000Output Cost
$0.000000Unit Cost
$0.000000Search Cost
$0.000000Request Fee
$0.000000Tool Fee
$0.000000Code Execution
2,300Total Tokens
$0.033696Cost per 1K
29,677Tokens per $

Click Recalculate to update after making changes

Calculate Processing Speed

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5.06sProcessing Time
500Tokens/Second
200msTime to First Token
472Effective Speed

Model Comparison

Select a model to see comparisons with competitors.

Model Information

Select a model to see detailed information.

🔄 Advanced Options

⚡ Optimization
70%
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

gpt-5-mini OpenAI

$0.077500 (rounded ~ 0.08)
Total Cost
🖼️ 5 Image (Medium) ⚡ 70% Cached 🔧 Tools
👁️
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) $0.077500 (rounded ~ 0.08) Input: $0.007500 (rounded ~ 0.01)
Output: $0.020000
Optimized Cost $0.077500 (rounded ~ 0.08) Input: $0.007500 (rounded ~ 0.01)
Output: $0.020000
Unit: $0.000000
Fees: $0.050000

Advanced Cost Breakdown

💻 Code Execution
$0.050000
Flat fee per execution

Detailed Cost Analysis

For 1,500 input tokens and 800 output tokens:

  • Input Cost: $0.007500 (rounded ~ 0.01)
  • Output Cost: $0.020000
  • Service Fees: $0.050000
  • Total Cost: $0.077500 (rounded ~ 0.08)
  • Cost per 1K tokens: $0.033696 (rounded ~ 0.03)
  • Tokens per dollar: 29,677 tokens
  • Context Window: 400000 tokens

Speed & Performance Analysis

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

  • Processing Time: 5.00 seconds
  • Latency: 200 milliseconds to first token
  • Base Throughput: 500 tokens/second
  • Effective Throughput: 472 tokens/second (temperature-adjusted)

Best Use Cases

E-commerceRetailShoppingPersonalization

E-commerce AI Cost Analysis

Calculating per-customer costs for AI shopping assistants. ROI analysis for retail implementations.

Unit Economics

  • Per Session: 500-2000 tokens
  • Conversion Impact: 15-30% improvement
  • Cost per Conversion: $0.05-$0.20
  • Lifetime Value Increase

Retail Applications

Product recommendations, customer support, personalized shopping, cart abandonment recovery, upselling.

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.
How are image tokens calculated?
Images are tokenized based on resolution: Low: 85 tokens, Medium: 170 tokens, High: 255 tokens, Full: 765 tokens per image. Some models (like Llama 4 Maverick) use tile-based encoding with 1,610 tokens/image (standard) or 8,050 tokens/image (high-res).
How does prompt caching work?
Caching discounts vary by provider: Google and OpenAI offer 90% discounts on cached input tokens. Anthropic uses write (1.25x) and read (0.10x) multipliers. Savings are applied to the token portion only, not unit-based fees.
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.