AI Token Counter

Estimate token counts for GPT-4o, DeepSeek V4, K3, GLM-5, Qwen-Plus, and Claude. Free. No signup.

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Estimated Counts

Characters

total chars

Words

space-separated

Estimated Tokens

avg: ~0.75 chars/token

Lines

newline count

Rule of thumb: 1 token ≈ 4 English characters, or ≈ 0.75 English words, or ≈ 1.5 Chinese characters. Code uses more tokens (~1.5-2x) due to punctuation and spacing.

Model Limits Check

See how your text fits within each model's context window.

Why Token Count Matters

Factor	Impact
Pricing	Most APIs charge per 1M input + output tokens. Longer prompts = higher cost.
Context Window	Each model has a max token limit. Exceeding it truncates or errors.
Latency	More input tokens = longer "time to first token" (TTFT).
Quality	Very long contexts can degrade attention quality in some models.

Token Estimation by Language

Language	Approx. Tokens per Character	Example
English	~0.25 (1 token per 4 chars)	"Hello world" ≈ 3 tokens
Chinese	~0.6-0.7 (1 token per 1.5 chars)	"你好世界" ≈ 4 tokens
Code (Python/JS)	~0.3-0.5	Highly variable by density
Japanese	~0.5-0.6	Similar to Chinese
Korean	~0.4-0.5	Slightly fewer than Chinese
Numbers	~0.3 per digit	"12345" ≈ 2 tokens

How to Reduce Token Usage

Remove redundant instructions and examples from system prompts
Use bullet points instead of full paragraphs when possible
Cache repeated context between API calls (e.g., using conversation state)
Split long documents into chunks and process independently
Use shorter variable names in code (minor savings, but adds up)
Avoid XML/JSON wrapping unless the model specifically needs structured input

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