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AI Updates16 Oct 2026·4 min read

Sarvam's Bulbul V4 Flash: Indian-Sounding AI Voice for ₹20 per 10,000 Characters

Sarvam AI's new text-to-speech model speaks 11 languages, starts audio in under 250 ms and costs a third less than V3. Here is what it means if you build apps in India.

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Nudge Daily Team
Sarvam's Bulbul V4 Flash: Indian-Sounding AI Voice for ₹20 per 10,000 Characters

Most AI voices still sound like a foreigner reading Hindi off a card. Sarvam AI, the Bengaluru company, says its new Bulbul V4 Flash fixes that, and it costs less than the model it replaces.

What launched

Bulbul V4 Flash is a text-to-speech model: you send text, you get spoken audio. According to Sarvam's launch post and coverage by MarTechAI:

  • 11 languages: Hindi, Bengali, Gujarati, Kannada, Malayalam, Marathi, Odia, Punjabi, Tamil, Telugu and Indian English
  • Under 250 ms time-to-first-audio in production, which matters for live voice agents
  • ₹20 per 10,000 characters, down from ₹30 for Bulbul V3 (about a third less)
  • 200+ voice personas, grouped by language and speaking style
  • Access through REST, HTTP streaming and WebSocket APIs

Why it matters in India

  • Names and numbers: Sarvam says a text-normalisation layer reads things like PNR numbers, PAN, Aadhaar, EMI and dates the way people actually say them. ISRO is read as a word, EMI letter by letter.
  • Code-mixing: it is built for Hinglish-style sentences, not just clean single-language text.
  • Cost: at ₹20 per 10,000 characters, a 1,000-character reply (roughly 150 to 200 words) costs about ₹2. That is our arithmetic from the published price.

What you could build

  1. A Hindi or Tamil voice tutor for exam prep
  2. A voice helpline for a small business
  3. Audio versions of your own blog posts or notes
  4. Narration for reels and explainers in your language

How to try it

  1. Open Sarvam's launch post and listen to the sample voices.
  2. Get an API key from Sarvam's developer dashboard. Check the current free credits and limits there, we have not verified them.
  3. Start with a short sentence in your language and test names, numbers and English words mixed in.
  4. Measure latency from your own network before you build on it.

Caveats

The quality and latency claims come from Sarvam's own demos. We have not tested the API ourselves, so listen to samples in your language before you commit.

Sources

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