DEVELOPER
LLM Token & Cost Visualizer
Understand and visualize how large language models segment text into tokens. Compare real-time API pricing across GPT-4o, Claude 3.5 Sonnet, Gemini 1.5, and DeepSeek V3 in seconds.
Context: 128k
Estimated Tokens
~91
418 characters • 53 words
Input Prompt Cost
$0.00023
$2.5 / 1M tokens
Est. Response Cost
$0.00500
Assumes 500 output tokens
Cost for 100k Calls
$522.75
Scale production estimation
Expected Output Tokens:500 tokens
You are an expert full-stack engineer and solutions architect.
Analyze the following microservices architecture for potential bottlenecks, race conditions, and scalability risks:
1. User Authentication Service (Go + Redis)
2. Payment Processing Pipeline (Node.js + Kafka + PostgreSQL)
3. Real-time Notification Engine (Rust + WebSockets)
Provide high-priority security recommendations and database indexing strategies.
Mastering LLM Tokenization and API Budgeting
Every modern AI model processes text as tokens rather than whole words. Punctuation, whitespace, and programming code fragments can inflate your token usage unexpectedly.
Our visualizer breaks your prompt down into discrete segments and computes exact input and response costs for single queries and scaled production workloads.
How to use this tool
- Paste your prompt, system instructions, or code snippet into the editor.
- Select your target model (OpenAI, Anthropic, Google Gemini, or DeepSeek).
- Inspect the live BPE token breakdown and per-token character count.
- View estimated production costs and copy the formatted prompt.