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DeepSeek V3: token counter & pricing

DeepSeek · approximate, within ±3% of reference · pricing as of 2026-04-26.

Provider
DeepSeek
API model ID
deepseek-chat
Context window
128,000 tokens
Input price
$0.27 per 1M tokens
Output price
$1.10 per 1M tokens
Tokenizer accuracy
approximate, within ±3% of reference
Pricing as of
2026-04-26

Open the counter to count tokens for DeepSeek V3 in real time.

What is DeepSeek V3?

DeepSeek V3 is the flagship model from Chinese AI lab DeepSeek — a 671-billion-parameter mixture-of-experts model that competes with frontier closed models on benchmarks at a fraction of the price. Open weights under a permissive license. Strongly priced API access from DeepSeek directly.

How tokens are counted here

DeepSeek uses a BPE tokenizer derived from the LLaMA family with extensions. We approximate in your browser, accurate to ~±3% for typical English text. Marked ≈±3%.

For exact counts, use DeepSeek's official tokenizer via Hugging Face: AutoTokenizer.from_pretrained("deepseek-ai/DeepSeek-V3").

Why DeepSeek matters

The price-to-capability ratio is the most aggressive in the industry as of 2026:

That's roughly 9× cheaper than GPT-4o on input, 9× cheaper on output, with similar quality on most tasks.

When to use DeepSeek

When not to use it:

Pricing notes

Pricing is from DeepSeek's official API. Self-hosting (via Together, Replicate, etc.) costs more — DeepSeek subsidizes API access aggressively. Verify on api-docs.deepseek.com.

DeepSeek also offers prompt caching at substantial discount (cached input tokens at ~10% of standard rate). Not reflected in this calculator.

Common questions

Is using DeepSeek's API safe for production data?

Read DeepSeek's data-handling policy and your own compliance requirements. The API does process your prompts in China-based infrastructure. For sensitive data, self-host the open weights via Together.ai or similar.

How does DeepSeek V3 compare to Claude Sonnet on coding?

DeepSeek tends to win on raw code generation benchmarks. Claude Sonnet tends to win on understanding complex existing codebases and producing edits that match local conventions. Try both with your prompts.

What's the context window?

128k tokens. Comparable to GPT-4o, Llama 3.1, and Claude Haiku. Below Gemini 2.5 (1M+) and Claude Sonnet/Opus (200k).

Compare DeepSeek V3 to other models