Voice AI Cost Calculator

Calculate precise costs for your voice AI application using real-time pricing from major providers. Get detailed breakdowns and optimize your stack for cost efficiency.

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Real-time pricing comparison
Accurate cost calculations
Provider optimization insights

Provider Selection

LLM Provider

STT Provider

TTS Provider

Cost Configuration

Transcription Cost per Minute ($)

Voice Cost per Character ($)

LLM Input Token Cost ($/token)

LLM Output Token Cost ($/token)

vCPU Cost per Minute ($)

Fixed Hosting Cost ($)

Calculation Assumptions

Conversation Length (minutes)

Agents per vCPU

Words per Minute

Tokens per Word

Characters per Word

Turns per Minute

LLM Speech Ratio (50%)

0% (User speaks more)100% (LLM speaks more)

Cost Breakdown

Cost Details

Transcription Cost$0.0900

LLM Cost$0.1584

Voice Cost$0.0450

Hosting Cost$0.0011

Total Cost$0.2945

$0.0196 per minuteFinal prices might be higher!

Token Usage

Input Tokens59,475

Output Tokens975

Total Tokens60,450

Latency Calculator

Analyze and optimize the latency components of your voice AI pipeline. Adjust individual components to see their impact on total latency.

Latency Breakdown Configuration

Input Path

Mic Input

Opus Encoding

Network Transit

Packet Handling

Jitter Buffer

Opus Decoding

AI Processing

Transcription

LLM Inference

Sentence Aggregation

Text-to-Speech

Output Path

Opus Encoding

Packet Handling

Network Transit

Jitter Buffer

Opus Decoding

Speaker Output

Formula Documentation

Understand how costs and latencies are calculated in your voice AI application. All calculations are based on industry-standard formulas and real-world usage patterns.

Cost Calculations

LLM Costs

Input Cost:

Calculated by multiplying the number of input tokens by the provider's rate per token.

Input Cost = Input Tokens × Input Rate per Token

Output Cost:

Calculated by multiplying the number of output tokens by the provider's rate per token.

Output Cost = Output Tokens × Output Rate per Token

Total LLM Cost:

The sum of input and output costs.

Total LLM Cost = Input Cost + Output Cost

STT Costs

Transcription Cost:

Determined by the provider's rate per minute of audio processed.

STT Cost = Conversation Length (minutes) × Rate per Minute

TTS Costs

Voice Cost:

Calculated by multiplying the number of characters in the text by the provider's rate per character.

TTS Cost = Characters Generated × Rate per Character

Hosting Costs

Infrastructure Cost:

Calculated based on vCPU usage and the number of concurrent agents.

Hosting Cost = (vCPU Cost × Conversation Length) ÷ Agents per vCPU

Token Calculations

Input Tokens:

Quadratic growth formula accounting for context accumulation in conversations.

Input Tokens = (Words/Min × Tokens/Word ÷ Turns/Min) × (Turns/Min × Convo Length) × (Turns/Min × Convo Length + 1) ÷ 2

Output Tokens:

Calculated based on LLM speaking ratio and conversation length.

Output Tokens = Words/Min × Tokens/Word × LLM Speech Ratio × Convo Length

Latency Calculations

Total Voice-to-Voice Latency

The complete end-to-end latency chain from user's voice input to receiving the agent's voice output.

Total Latency = Mic Input + Opus Encoding + Network Transit + Packet Handling + Jitter Buffer + Opus Decoding + Transcription + LLM Inference + Sentence Aggregation + Text-to-Speech + Opus Encoding + Packet Handling + Network Transit + Jitter Buffer + Opus Decoding + Speaker Output

Frequently Asked Questions

: The cost estimates are based on current pricing from major AI providers and industry-standard usage patterns. However, actual costs may vary depending on your specific use case, provider discounts, volume pricing, and other factors. We recommend using these estimates as a starting point for budgeting and comparing different provider options.
: The total cost depends on several factors: conversation length, number of concurrent users, provider pricing, token usage (which grows quadratically with conversation length), voice synthesis requirements, and infrastructure hosting costs. The calculator accounts for all these variables to give you a comprehensive cost breakdown.
: Latency is crucial for natural conversations. Total latency under 200ms is considered fast and provides excellent user experience. 200-500ms is acceptable for most use cases, while over 500ms can feel sluggish. The latency calculator helps you optimize each component of your voice pipeline to achieve the best possible performance.
: Currently, the calculator runs in your browser and doesn't save data automatically. We recommend taking screenshots or noting down your preferred configurations. Future versions may include export functionality for sharing calculations with your team or saving them for later use.
: The calculator uses hardcoded pricing data that reflects current market rates. However, AI provider pricing can change frequently. We recommend verifying current pricing directly with providers before making final decisions, especially for high-volume applications where small price differences can have significant impact.
: Input tokens represent the text you send to the LLM (including conversation history), while output tokens are the text the LLM generates in response. Input tokens grow quadratically with conversation length due to context accumulation, while output tokens grow linearly. This is why longer conversations become increasingly expensive.
: Consider your priorities: cost optimization, latency requirements, voice quality, and reliability. Use the calculator to compare different combinations. For cost-sensitive applications, consider GPT-4o Mini with efficient TTS providers. For low-latency needs, prioritize faster STT/TTS providers even if they cost more.
: This represents how many concurrent voice AI conversations can run on a single virtual CPU. The actual number depends on your infrastructure setup, conversation complexity, and optimization. A higher number means better resource utilization and lower per-conversation hosting costs, but may impact performance.

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