🤖 Real-Time Token & Multi-Model Cost

AI Token Counter & LLM API Cost Calculator (2026)

Count prompt tokens instantly and compare true API costs across OpenAI GPT-6, Claude 5.5, Gemini 3.8, and DeepSeek-V4 with prompt caching discounts and multi-user bill projections.

🇺🇸 English 🇪🇸 Español 🇧🇷 Português
⚡ 100% Client-Side • Zero Telemetry

AI Token Counter & LLM API Cost Calculator (2026)

Count prompt tokens instantly, calculate exact input/output pricing, and simulate monthly cloud bills across OpenAI GPT-6 (Astra, Sol, Luna), Claude 5.5, Gemini 3.8, and DeepSeek-V4 with prompt caching discounts.

Currency:
Sample Presets:
Tokens
0
~0.75 words/token
Words
0
Whitespace split
Characters
0
Total characters
Without Spaces
0
Raw text density
500 tokens

Output tokens typically cost 3x to 5x more than inputs due to sequential GPU decoding.

Live Provider Pricing & Cost Comparison (2026 Lineup)

Production Scale & Monthly Cloud Bill Simulator

Model your projected monthly inference invoice based on active users and daily prompt volume.

Monthly Request Volume:
Monthly Token Consumption:

Projected Monthly Cloud Invoices (2026 Frontier Models)

Model & Provider Cost / Request Est. Monthly Bill Annual Cost
ScoRpii Tech • Frontier AI Engineering

Building Custom AI Agents or RAG Architectures?

ScoRpii Tech designs high-throughput AI agent systems, cost-optimized token routing across GPT-6 Astra, Claude 5.5, and DeepSeek-V4, and custom Flutter mobile integrations.

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Help & FAQs

Frequently Asked Questions

A token is the basic unit of text that a language model reads and generates. In English, one token is approximately 4 characters or 0.75 words. Punctuation, whitespace, code indentation, and non-Latin scripts consume additional tokens depending on the tokenizer.
Input tokens can be processed in parallel across GPU clusters simultaneously (prefill phase). In contrast, output tokens must be generated sequentially one token at a time (decode phase), consuming significantly more GPU compute time and memory bandwidth.
Prompt caching allows AI providers to reuse previously computed attention keys and values for static context that does not change between requests. Caching delivers 75% to 98% savings on cached input tokens (such as DeepSeek-V4 cache hits at $0.006/1M), reducing costs by thousands of dollars per month.
For cost-sensitive high-volume tasks, DeepSeek-V4.1-Flash ($0.30 / 1M input) and Claude Haiku 5.5 ($0.10 / 1M input) offer industry-leading economics. For complex reasoning and software engineering, GPT-6 Astra, Claude Sonnet 5.5, and DeepSeek-V4-Pro deliver frontier benchmark performance.
No. All token counting, text parsing, and cost modeling execute 100% locally in your browser using client-side JavaScript. No prompts, code snippets, or document data are ever transmitted to ScoRpii Tech or external servers.
ScoRpii Tech designs and builds production-grade AI agent systems, RAG architectures, and mobile apps. We implement cost-optimized model routing across GPT-6, Claude 5.5, and DeepSeek-V4, prompt caching, and bare-metal self-hosted inference to deliver maximum performance at minimal cloud cost.