DeepSeek V4 Pro 0424 (Reasoning, Max Effort) Token Counter & Cost Calculator
Count tokens for DeepSeek V4 Pro 0424 (Reasoning, Max Effort) and estimate the exact API cost — $0.435
per 1M input tokens, $0.87 per 1M output tokens — using a real
o200k_base BPE tokenizer. Everything runs in your browser; nothing is uploaded.
Counts are exact for OpenAI models (o200k_base is GPT-4o/4.1/5's tokenizer). For Claude, Gemini and other vendors — whose tokenizers are not public — treat the count as a close estimate (typically within ±15%).
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Cost of this text across popular models
| Model | Input $/1M | Output $/1M | This text (input) | +500 output tokens |
|---|
Close estimate (±15%): DeepSeek does not publish its tokenizer, so this count uses OpenAI's o200k_base as an approximation.
Cost lookup — DeepSeek V4 Pro 0424 (Reasoning, Max Effort)
| Tokens | Cost on DeepSeek V4 Pro 0424 (Reasoning, Max Effort) |
|---|---|
| 1K input tokens | 0.0435¢ |
| 10K input tokens | 0.435¢ |
| 100K input tokens | $0.0435 |
| 1M input tokens | $0.4350 |
| 1K output tokens | 0.087¢ |
| 10K output tokens | 0.87¢ |
FAQ
How accurate is the DeepSeek V4 Pro 0424 (Reasoning, Max Effort) token count?
Close estimate (±15%): DeepSeek does not publish its tokenizer, so this count uses OpenAI's o200k_base as an approximation. Paste your own text above to see the exact number for your prompt.
How is DeepSeek V4 Pro 0424 (Reasoning, Max Effort) API cost calculated?
Cost = (input tokens ÷ 1,000,000) × $0.435 + (output tokens ÷ 1,000,000) × $0.87 — DeepSeek V4 Pro 0424 (Reasoning, Max Effort)'s official per-1M-token prices from Artificial Analysis.
Does this cover every reasoning-effort tier of DeepSeek V4 Pro 0424 (Reasoning, Max Effort)?
Pricing shown is for the merged representative tier. DeepSeek V4 Pro 0424 (Reasoning, Max Effort) groups 3 reasoning-effort variants: DeepSeek V4 Pro 0424 (Reasoning, Max Effort), DeepSeek V4 Pro 0424 (Reasoning, High Effort), DeepSeek V4 Pro 0424 (Non-reasoning).
See full DeepSeek V4 Pro 0424 (Reasoning, Max Effort) pricing & benchmarks, or the main token counter for every model.