Global Araç
Ai Token Counter
| Model | Context | Input $/M | Output $/M | Est. cost (1 call) |
|---|---|---|---|---|
| GPT-4o | 128,000 | $2.50 | $10.00 | $0.0052 |
| GPT-4o mini | 128,000 | $0.15 | $0.60 | $0.0003 |
| GPT-4 Turbo | 128,000 | $10.00 | $30.00 | $0.0158 |
| Claude Opus 4 | 200,000 | $15.00 | $75.00 | $0.0388 |
| Claude Sonnet 4 | 200,000 | $3.00 | $15.00 | $0.0078 |
| Claude Haiku 4 | 200,000 | $0.80 | $4.00 | $0.0021 |
| Gemini 1.5 Pro | 2,000,000 | $1.25 | $5.00 | $0.0026 |
| Gemini 1.5 Flash | 1,000,000 | $0.07 | $0.30 | $0.0002 |
| Llama 3.1 70B | 128,000 | $0.35 | $0.40 | $0.0002 |
| Mistral Large | 128,000 | $2.00 | $6.00 | $0.0032 |
Prices are list rates per million tokens. Estimate uses ~3.8 chars/token — within ~10% for English prose. For billing-critical counts, use each provider's official tokenizer.
Estimate tokens, characters, and API cost for GPT-4o, GPT-4, Claude, Gemini, Llama, and more — before you hit send.
Nasıl Kullanılır
- Paste the text.
- Set assumed output tokens.
- Read the per-model cost estimate.
Sık Sorulan Sorular
What's a token?
The atomic unit LLMs process. Roughly 3.8 characters per token in English, 1 word per ~1.3 tokens. Spaces, punctuation, and unusual words all count. Code and non-English text tokenize less efficiently (often 2-3x more tokens per character).
Why does my token count vary between models?
Different model families use different tokenizers. GPT-4 uses BPE (cl100k); Claude uses a different vocabulary; Gemini uses SentencePiece. Identical text produces 10-20% different token counts between them. Always estimate with the tokenizer matching your target model.
How accurate is this token estimate?
Within ~10% for English prose. Drifts 20-40% for code (tokens per character drops), non-English text (multi-byte characters are heavier), and numbers/symbols. For billing-critical workloads, use the model vendor's official tokenizer (tiktoken for OpenAI, Anthropic's library for Claude).
How many tokens fit in a context window?
GPT-4o and Claude Opus 4 handle 200k tokens (~150k words, ~600 pages of text). Gemini 1.5 Pro handles 2M tokens (~1.5M words, ~6000 pages). Most applications don't need more than 10-50k tokens per request. Context windows are about capability ceiling, not typical usage.