AI Prompt Token Counter & Cost Estimator β Real-Time BPE Tokenizer
Calculate exact tokens and live API costs for GPT-4o, o1, Claude 3.5 Sonnet, and Gemini 1.5. 100% in-browser client-side BPE tokenizer with Zero server logs.
Flagship multimodal model with o200k_base tokenization
API Cost Estimator
$2.50 / $10.00 per 1MCross-Model Cost Comparison Matrix
Live Estimates (USD)| Model | Provider | Context | Input / 1M | Output / 1M | Total Est. Cost |
|---|---|---|---|---|---|
| GPT-4o (Omni) | OpenAI | 128k | $2.50 | $10.00 | $0.0000 |
| GPT-4o-mini | OpenAI | 128k | $0.15 | $0.60 | $0.0000 |
| OpenAI o1 | OpenAI | 200k | $15.00 | $60.00 | $0.0000 |
| Claude 3.5 Sonnet | Anthropic | 200k | $3.00 | $15.00 | $0.0000 |
| Claude 3.5 Haiku | Anthropic | 200k | $0.80 | $4.00 | $0.0000 |
| Gemini 1.5 Pro | 2000k | $1.25 | $5.00 | $0.0000 | |
| Gemini 1.5 Flash | 1000k | $0.07 | $0.30 | $0.0000 | |
| DeepSeek-V3 | DeepSeek | 64k | $0.14 | $0.28 | $0.0000 |
| Llama 3.3 (70B) | Meta | 128k | $0.20 | $0.60 | $0.0000 |
Reserved high-performance space. Zero Cumulative Layout Shift (CLS) guaranteed.
Understanding BPE Tokenization, Context Limits & LLM Pricing
Large Language Models (LLMs) such as OpenAI GPT-4o, Anthropic Claude 3.5, and Google Gemini do not process text in words or characters directly. Instead, they transform raw text streams into discrete numeric chunks known as tokens using Byte-Pair Encoding (BPE) algorithms (such as cl100k_base or o200k_base). On average in standard English text, 1 token corresponds to approximately 4 characters or 0.75 words.
Token density varies significantly between programming languages and natural prose. For example, structured JSON payloads, indentation whitespace, and special punctuation characters often generate higher token-to-character ratios than conversational paragraphs. Modern tokenizers like OpenAI o200k_base have drastically improved token compression for non-English alphabets (including Arabic, Cyrillic, and CJK) and code syntax.
API billing across all major foundation model providers is calculated on a per-token basis (typically priced per 1 Million tokens). Pricing is asymmetric: output (completion) generation requires sequential autoregressive inference and is typically 3x to 4x more expensive per token than prompt input caching.
OmniTools calculates all token distributions and financial projections 100% inside your browser memory using optimized subword boundaries. None of your sensitive prompts, confidential business logic, or customer credentials ever leave your machine.
Frequently Asked Questions (FAQ)
Our engine uses calibrated Byte-Pair Encoding (BPE) subword splitting algorithms aligned with cl100k_base and o200k_base vocabularies. For typical English prompts, code snippets, and international text, accuracy is within ~1-3% of official tokenizer binaries without making any remote network requests.
Input tokens can be pre-computed and parallelized across GPU matrix operations (and cached via Prompt Caching). In contrast, output tokens must be generated sequentially one token at a time via autoregressive decoding, requiring significantly more compute and GPU memory bandwidth.
Absolutely not. OmniTools is strictly 100% client-side. All token parsing, memory tracking, and pricing arithmetic execute locally in your browser memory with zero network calls and zero server telemetry.