What Indian languages cost on AI models.
The same passage in six languages on 11 models: how many more tokens, and rupees, an Indian language costs.
Tokens per language, as a multiple of English
Darker means more tokens for the same meaning. Sorted from most to least efficient across the five Indian languages.
| Model | English tokens | Hindi | Marathi | Bengali | Tamil | Telugu | Average |
|---|---|---|---|---|---|---|---|
| Sarvam-105BSarvam | 123 | 1.2× | 1.4× | 1.1× | 1.4× | 1.4× | 1.3× |
| Gemini 3.6 FlashGoogle | 123 | 1.2× | 1.4× | 1.1× | 1.4× | 1.8× | 1.4× |
| GPT-5 MiniOpenAI | 121 | 1.4× | 1.8× | 1.5× | 2.1× | 2.0× | 1.8× |
| Ministral 3 14BMistral | 124 | 1.7× | 2.1× | 1.8× | 2.4× | 2.3× | 2.1× |
| Grok 4.6xAI | 121 | 1.6× | 2.0× | 2.1× | 2.8× | 4.3× | 2.6× |
| DeepSeek V3.2DeepSeek | 124 | 2.8× | 2.9× | 1.8× | 3.3× | 3.9× | 2.9× |
| Kimi-K2-Instruct-0905Moonshot | 121 | 2.8× | 2.9× | 2.8× | 4.5× | 4.2× | 3.5× |
| Claude Haiku 4.5 (latest)Anthropic | 127 | 3.2× | 3.6× | 3.7× | 4.8× | 4.4× | 3.9× |
| Llama-3.3-70B-InstructMeta | 123 | 2.4× | 2.8× | 5.6× | 8.3× | 8.9× | 5.6× |
| Qwen3 235B A22B Instruct 2507Qwen | 123 | 4.6× | 4.7× | 4.9× | 6.8× | 7.7× | 5.7× |
| GLM-5.3Z.ai | 123 | 4.3× | 4.7× | 4.7× | 8.3× | 8.9× | 6.2× |
| Average across models | 2.5× | 2.8× | 2.8× | 4.2× | 4.5× |
What it does to the bill
The input cost of 10,000 customer messages like the test passage, in English and in Hindi, at each model's live price on Rapid Router. Output tokens grow the same way, so a reply in Hindi costs more again.
| Model | Price per 1M input | English | Hindi | Tamil |
|---|---|---|---|---|
| Sarvam-105B | ₹35.37 | ₹43.51 | ₹54.12 | ₹62.25 |
| Gemini 3.6 Flash | ₹73.69 | ₹90.64 | ₹112.74 | ₹129.69 |
| GPT-5 Mini | ₹24.56 | ₹29.72 | ₹42.49 | ₹61.65 |
| Ministral 3 14B | ₹19.65 | ₹24.37 | ₹40.87 | ₹57.77 |
| Grok 4.6 | ₹197 | ₹237.77 | ₹389.07 | ₹654.35 |
| DeepSeek V3.2 | ₹25.55 | ₹31.68 | ₹87.62 | ₹103.46 |
| Kimi-K2-Instruct-0905 | ₹73.69 | ₹89.16 | ₹250.54 | ₹403.81 |
| Claude Haiku 4.5 (latest) | ₹98.25 | ₹124.78 | ₹404.79 | ₹596.38 |
| Llama-3.3-70B-Instruct | ₹9.83 | ₹12.08 | ₹28.59 | ₹100.31 |
| Qwen3 235B A22B Instruct 2507 | ₹8.84 | ₹10.88 | ₹49.61 | ₹74.45 |
| GLM-5.3 | ₹138 | ₹169.19 | ₹734.52 | ₹1,404.39 |
Method
One passage of 107 English words about a small shop using an AI assistant, translated by us into the five languages with the same meaning and register. Each version was sent once to each model through the Rapid Router API on 18 October 2026. We recorded the prompt token count each provider reported, minus the count for a one-word message, so the fixed overhead of the chat format cancels out.
Limits worth knowing: it is one passage, so treat the figures as indicative rather than exact; native writers phrase things differently from a translation; and tokenizers change between model versions, so a newer release can move a lot. Two models that share a tokenizer family, or that fall back to splitting rare scripts byte by byte, can report identical counts; that is a real result, not a copy.
A small clothing shop in Jaipur gets about two hundred customer messages every day. Most of them ask the same things: is this size available, how long will delivery take, can I return it if it does not fit. The owner used to answer every message herself late at night. Now an AI assistant reads each message, checks the stock list and the courier's tracking page, and writes a short, polite reply in the customer's own language. She reads the replies once in the morning and corrects the few that are wrong. Her customers get answers in minutes instead of hours, and she has her evenings back.
For models built for Indian languages, see the Indic collection; for quality rather than cost, the best model for each task.