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Tokens per word in Hindi

Hindi averages about 3.2 tokens per word on current BPE tokenizers, which is 141% more tokens than the same count in English. Devanagari fragments heavily. A Hindi prompt can cost more than twice an English prompt of the same meaning.

3.2Tokens per word

0.31words per token

3,200Tokens per 1,000 words

+141%vs English

Hindi to tokens table

Words → Tokens (Hindi, 3.2 tokens per word)
Words	Tokens
100	320
250	800
500	1,600
1,000	3,200
2,500	8,000
5,000	16,000
10,000	32,000
25,000	80,000
50,000	160,000
100,000	320,000

Language comparison

Language	Tokens per word	Tokens for 1,000	Cost multiplier vs English
English	1.33	1,330	1.00×
Spanish	1.7	1,700	1.28×
French	1.8	1,800	1.35×
German	1.9	1,900	1.43×
Portuguese	1.7	1,700	1.28×
Russian	2.4	2,400	1.80×
Arabic	2.9	2,900	2.18×
Hindi	3.2	3,200	2.41×
Chinese	1.5	1,500	1.13×
Japanese	1.8	1,800	1.35×

Ratios are per word except Chinese and Japanese, which are per character. Comparing them directly is approximate — the honest way to budget is to tokenize a sample of your own corpus.

Cost of 1,000 words in Hindi

Cost of 3,200 tokens (1,000 words) — USD, rates verified October 2026
#	Model	Provider	Input	Output	Blended
1	GPT-6 Luna	OpenAI	$0.00032	$0.0016	$0.00072
2	GPT-5.6 Luna	OpenAI	$0.00064	$0.00384	$0.0016
3	GPT-5.4 nano	OpenAI	$0.00064	$0.004	$0.00164
4	Gemini 3.5 Flash-Lite	Google Gemini	$0.00096	$0.008	$0.00296
5	DeepSeek V4.1 Flash	DeepSeek	$0.00096	$0.00384	$0.00192
6	GPT-5.4 mini	OpenAI	$0.0024	$0.0144	$0.006
7	Gemini 3.8 Flash	Google Gemini	$0.0024	$0.012	$0.0054
8	Gemini 3.7 Flash	Google Gemini	$0.0024	$0.012	$0.0054
9	Claude Haiku 4.5	Anthropic	$0.0032	$0.016	$0.0072
10	Gemini 2.5 Pro	Google Gemini	$0.004	$0.032	$0.012
11	Grok 4.3	xAI Grok	$0.004	$0.008	$0.006
12	DeepSeek V4 Pro	DeepSeek	$0.00422	$0.0127	$0.00739
13	Gemini 3.5 Flash	Google Gemini	$0.0048	$0.0288	$0.012
14	GPT-5.2	OpenAI	$0.0056	$0.0448	$0.0168
15	GPT-6.1 Sol	OpenAI	$0.0064	$0.032	$0.0144
16	GPT-6 Sol	OpenAI	$0.0064	$0.032	$0.0144
17	GPT-5.6 Terra	OpenAI	$0.0064	$0.0384	$0.016
18	GPT-4.1	OpenAI	$0.0064	$0.0256	$0.0128
19	Claude Sonnet 5	Anthropic	$0.0064	$0.032	$0.0144
20	Gemini 3.1 Pro (Preview)	Google Gemini	$0.0064	$0.0384	$0.016
21	Grok 4.6	xAI Grok	$0.0064	$0.0192	$0.0112
22	GPT-5.4	OpenAI	$0.008	$0.048	$0.02
23	Claude Sonnet 4.6	Anthropic	$0.0096	$0.048	$0.0216
24	GPT-5.6 Sol	OpenAI	$0.0128	$0.064	$0.0288
25	GPT-5.5	OpenAI	$0.016	$0.096	$0.04
26	Claude Opus 5	Anthropic	$0.016	$0.08	$0.036
27	GPT-6 Astra	OpenAI	$0.032	$0.16	$0.072
28	Claude Fable 5.1	Anthropic	$0.032	$0.16	$0.072

Input = 3,200 prompt tokens. Output = 3,200 generated tokens. Blended = input + 25% of output, the same weighting used across this site.

What this means for a multilingual product

If you serve Hindi and English from the same budget, Hindi consumes 2.4× the tokens for the same number of words. Either the price per token absorbs that, or the Hindi product quietly runs at a lower margin. Measuring the ratio on your own text is the only reliable way to price it.

FAQ

How many tokens is 1,000 words in Hindi?

About 3,200 tokens, using 3.2 tokens per word. That is 141% more tokens than the same count in English (1,330).

Why is Hindi more expensive per word?

Devanagari fragments heavily. A Hindi prompt can cost more than twice an English prompt of the same meaning. Providers bill per token, not per word, so a language that fragments into more tokens costs more for the same meaning.

How do I get an exact count for Hindi?

Run a sample of your own text through the tokenizer of the model you will be billed on. Public ratios are averages; product names, numbers and formatting in your own data can move the result by 20% or more.

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