a reply in hindi might include an english product name, a delivery address, and a price in rupees. your text-to-speech provider needs to read that mix clearly and keep the conversation easy to follow.

we've compared seven sarvam ai alternatives for indian-language text to speech: rumik silk, smallest.ai, gnani.ai, murf, indic-speak by bodhan ai and ai4bharat, cartesia, and elevenlabs. for each one, we look at the languages and voices available, what you'll pay, and what you'd need to change in your app.

1. rumik silk

• product type: text-to-speech api and voice-agent platform

• recommended users: teams adding indian-language speech to customer support, learning, and conversational apps

• pricing options: pay as you go and unlimited monthly plans

what is rumik silk?

rumik silk (that's us) is a text-to-speech platform for learning content, voiceovers, and indian-language apps. its voice-agent platform also lets you build assistants that listen and respond to users in a conversation.

silk uses two speech-generation models, mulberry and muga. mulberry builds the voice from a description you send with the text, so you can specify the accent, pace, and delivery. mulberry 1.6 supports languages including hindi, tamil, telugu, marathi, and bengali. muga guides short hindi-english dialogue with mood tags and vocal sounds such as laughter or sighs.

key features

• indian numbers and dates: silk's normalization handles rupee amounts, lakh/crore values, and day-first dates in messages such as payment reminders and order updates.

• hinglish replies: you can give muga "aapka refund aa gaya" or "आपका refund आ गया". it accepts hindi in both forms and lets you mix in english.

• voice descriptions: mulberry accepts directions such as "a warm hindi voice with a steady pace" alongside the speech text. those directions can guide a generated speaker or one of silk's named voices.

• streaming: silk's audio streaming lets playback begin while the rest of a line is being generated. it works with complete utterances, including shorter parts of a longer reply.

how does rumik silk compare to sarvam ai?

silk has the advantage when you want to describe the speaker inside each speech request. mulberry voice model accepts your own voice description, while sarvam's standard tts api selects a catalog speaker or persona. muga also accepts romanized hindi, whereas sarvam recommends devanagari for hindi and latin letters for english.

silk's unlimited plans give you a fixed monthly tts budget based on simultaneous requests. sarvam's plans remain metered, so silk offers a different way to budget for frequent conversations.

rumik silk pricing

rumik silk has pay-as-you-go pricing and unlimited monthly plans. the difference is whether the bill follows the amount of text generated or the number of requests the account can run at once.

pay as you go

silk bills the submitted text, including spaces, punctuation, and inline tags. mulberry's voice descriptions are billed at the same rate. pay as you go allows four requests at once across tts and agents, with agent calls charged by the minute.

unlimited monthly plans

the monthly fee covers unlimited generation at the chosen capacity. a two-request plan, for example, can run two generations together and accept a new one whenever either finishes. tts and agents share that capacity.

teams needing more than eight simultaneous requests can contact rumik for a higher-capacity plan.

when should you choose rumik silk?

• you want unlimited tts. silk's unlimited plans let you keep generating speech for a fixed monthly price, without a monthly character limit.

• you have a voice in mind. with mulberry voice model, you can describe what you're after, like "a calm hindi voice that speaks slowly", and try it with your app's text.

• easier implementation: the api quickstart and sdk cover the first integration steps, with the rumik team available for setup questions.

try a few lines from your app in the silk playground and hear which voice works for you.

bottom line

if you want expressive indian-language speech with unlimited monthly generation, choose rumik silk as your sarvam ai alternative and pay for the capacity your app needs.

2. smallest.ai

• product type: text-to-speech api and voice-agent platform

• recommended users: developers building multilingual apps, phone assistants, and narration tools

• pricing options: pay as you go and custom enterprise plans

what is smallest.ai?

smallest.ai generates speech through its lightning voice models. they can supply the voice in an existing app, while its separate voice-agent platform supports phone, web, and mobile conversations.

key features

• indian-language voices: the voice catalog includes choices such as devansh and sunidhi for hindi, and jeevan and rajeshwari for tamil. the standard and pro models have separate voice selections.

• mixed-language speech: lightning v3.1 supports language changes within defined groups. switching across groups is not supported within the same session.

• pronunciation dictionaries: pronunciations for names, brand terms, and abbreviations can be saved in a dictionary and reused in later speech requests.

• streaming replies: lightning v3.1's websocket continuations accept text in parts as an llm writes a reply. the audio streams back for playback while generation continues.

how does smallest.ai compare to sarvam ai?

smallest.ai's main advantage here is lightning v3.1 pro's wider language coverage. its catalog includes french, japanese, and arabic voices alongside indian-language voices. sarvam's bulbul models focus on indian languages and english, so pro gives an app serving more countries another set of voices to try.

smallest.ai pricing

smallest.ai's pay-as-you-go rates are about $0.175 (₹16.64) per 10,000 characters for lightning v3.1 and $0.195 (₹18.55) for lightning v3.1 pro [approximate inr equivalents at current exchange rates on 27 october 2026]. both are billed by usage, with custom enterprise pricing available. these are tts rates, separate from the cost of running a managed voice agent.

when should you choose smallest.ai?

• you need indian and international languages. your app might need hindi for one audience and japanese for another. lightning v3.1 pro has voices for both.

• some names need a particular pronunciation. a dictionary can keep the pronunciation of a product name or abbreviation consistent across replies.

• you want to choose from existing voices. smallest.ai has separate standard and pro catalogs, with language-specific choices to hear against the content from your app.

bottom line

if you need indian-language speech as well as french, japanese, or arabic, choose smallest.ai as your sarvam ai alternative for lightning v3.1 pro's broader voice catalog.

3. gnani.ai

• product type: text-to-speech api, voice-cloning and agent-builder

• recommended users: developers building indian-language conversations, narration, and spoken characters

• pricing options: custom enterprise pricing

what is gnani.ai?

gnani.ai offers text-to-speech, speech recognition, voice cloning, and a platform for building voice agents. its timbre voice models provide the speech output for customer conversations and narration, with v3.0 adding tags for whispers, laughter, and pauses.

key features

• expression within a line: timbre v3.0 supports audio tags such as <whispers>, <excited>, <laugh>, and <pauses>. these guide delivery and add vocal reactions within the selected voice.

• amounts and account details: timbre's automatic normalization prepares written amounts, dates, and account numbers for speech. the selected language determines the number and currency wording.

• streaming audio: websocket and SSE streaming allow playback to begin before the full audio clip is ready. the speech api can also return a complete audio file for narration or batch generation.

• voice-agent tools: gnani's agent builder brings together prompts, knowledge bases, configured integrations, and call analytics for customer conversations.

how does gnani.ai compare to sarvam ai?

gnani's voice cloning and agent builder use separate workflows from a standard timbre tts request. each v3.0 voice supports the ten catalog languages, while mid-sentence language switching remains in beta.

gnani.ai pricing

gnani.ai offers custom enterprise pricing, with a quote based on usage and deployment.

when should you choose gnani.ai?

• you want expression inside a line. a character might whisper one sentence and laugh in the next. timbre v3.0 has tags for both.

• your app uses the same speaker in several languages. a v3.0 voice can read hindi and tamil replies, as well as the other languages in its catalog.

• you also need transcription or a cloned voice. gnani offers prisma for speech-to-text and separate voice-cloning APIs alongside timbre.

bottom line

if you want tts, speech-to-text, and cloning under a custom enterprise plan, gnani.ai is a sarvam ai alternative for that setup. sarvam offers a similar speech stack with public API rates.

4. murf

• product type: text-to-speech api, voiceover studio, and managed voice agents

• recommended users: developers building indian-language speech apps and teams creating voiceovers

• pricing options: pay-as-you-go api pricing and custom enterprise plans

what is murf?

murf offers a studio for editing voiceovers, a speech api for apps, and a managed service for voice agents. falcon 2.1 is its conversational tts model. it turns text into audio using a selected voice and can stream a reply as your app generates it.

key features

• mixed-language replies: a compatible falcon voice can switch languages within a sentence. it also reads numbers, dates, and currency amounts, with pronunciation controls for words that need a specific reading.

• saved pronunciations: you can keep names, brand terms, and abbreviations in a pronunciation dictionary and reuse them across requests. inline IPA gives you control over individual words too.

• regional api endpoints: falcon has an india endpoint as well as other regional routes. you can choose where to send speech requests rather than rely on the global router.

• voice cloning: murf offers instant and professional cloning through its enterprise plans. instant cloning uses a recording of up to 30 seconds, and the cloned voice works with falcon 2.1.

how does murf compare to sarvam ai?

murf has assamese voices in falcon's catalog, while sarvam's current bulbul language list doesn't include it. murf's cloning requires enterprise access, and its managed voice agents are a separate service from the tts api.

murf pricing

murf's falcon 2.1 api pricing is $0.01 (about ₹0.95) per 1,000 characters [approximate inr equivalent at 27 october 2026 exchange rates]. you get $10 in trial credits, and purchased credits don't expire. pay-as-you-go allows two active tts requests at once through the india endpoint, compared with five in us-east. higher capacity comes under enterprise terms. these rates cover speech generation, with studio and managed voice agents priced separately.

when should you choose murf?

• assamese is part of your audience. falcon has voices that support it alongside hindi, bengali, and other languages. check the languages available for the voice you want to use.

• your app keeps getting a name wrong. a pronunciation dictionary gives you a saved reading for a company name or product term, rather than leaving each request to interpret it.

• you want to use an india api endpoint. murf gives you that regional option. its two-request pay-as-you-go limit is worth accounting for if several users will need speech at the same time.

bottom line

if you need assamese speech, murf is a sarvam ai alternative with voices beyond bulbul's current language list. murf also offers enterprise voice cloning.

5. bodhai.ai indic-speak

• product type: text-to-speech api and an open-weight speech model

• recommended users: teams building educational audio and indian-language apps

• pricing options: pay-as-you-go api pricing in rupees, or self-hosting under a custom license

what is indic-speak?

indic-speak is a text-to-speech model developed by bodhan ai and ai4bharat. you can use it through bodhan's hosted api or run the released model on your own infrastructure. it was developed with education in mind, particularly lessons that mix an indian language with english technical terms.

key features

• production and preview languages: production support covers 13 languages, including english, hindi, tamil, assamese, and urdu. another ten, such as bodo, konkani, and sanskrit, are in preview.

• delivery styles: the hosted api has options for educational lectures, news, and audiobook narration. the downloadable model also accepts style directions, though that release's style control is still preview-quality.

• your own deployment: the released weights let your team run and modify the model, subject to its license. you take care of the computing resources, capacity, and model updates.

how does indic-speak compare to sarvam ai?

indic-speak's production language set includes assamese and urdu, which aren't in bulbul's current stock-voice catalog. sarvam offers voice cloning through a separate api, while indic-speak uses existing catalog voices. its hosted delivery styles change how a selected speaker reads, rather than create a speaker from a description.

streaming is available through indic-speak's self-hosted server, over websocket or http. bodhan's hosted api documents wav output. indic-speak supplies speech generation, with conversation logic and call handling built separately.

indic-speak pricing

bodhan's indic-speak api pricing is ₹6 per 10,000 input characters. you add credit in rupees and pay for what you generate, with no subscription or minimum spend. new accounts start with ₹10 in credit.

running the model yourself has no model royalty under its custom license, subject to the license conditions. your costs are the computing resources and the work of keeping it running. third-party model hosting generally requires a separate agreement, with exceptions for eligible public-interest uses and qualifying open releases. the license also prohibits robocalls and auto-dialers.

when should you choose indic-speak?

• you're making lessons with mixed-language explanations. english scientific terms can sit within hindi or tamil text. indic-speak's educational focus makes it a model to try with those passages.

• your audience needs assamese or urdu. both are in its production language set. the preview languages need a separate evaluation before you depend on them.

• you have a reason to run the model yourself. your team can manage the deployment and modify the released weights. that route makes sense when control over the model is worth the ongoing hosting work.

bottom line

if you want to run indian-language tts yourself, indic-speak is a sarvam ai alternative with released model weights and an education focus. sarvam handles hosting.

6. cartesia

• product type: text-to-speech api, speech recognition, and managed voice agents

• recommended users: developers building hinglish conversations and apps that need indian and international languages

• pricing options: monthly credit plans, optional usage-based overages, and custom enterprise pricing

what is cartesia?

cartesia offers speech generation through sonic, speech recognition through ink, and a managed platform for voice agents. sonic 3.6 is its current text-to-speech model. it streams audio for conversations and supports languages including hindi, tamil, telugu, bengali, marathi, and urdu, alongside english and international languages such as french and japanese.

key features

• romanized hindi: sonic 3.6 reads hindi written in latin letters, including replies such as "aapka order confirm ho gaya hai". english can sit alongside romanized hindi or devanagari hindi. mixing devanagari hindi with romanized hindi in the same generation isn't supported.

• separate number-reading settings: the speaking language and the conventions for reading dates, times, and numbers can be set independently. a hindi reply can use indian english conventions for those details.

• cloned voices: instant cloning creates a voice from a short recording, while professional cloning uses longer recordings. additional language accents can be added through a separate voice-customization workflow.

how does cartesia compare to sarvam ai?

sonic's language set includes urdu, which isn't in bulbul's current stock-voice catalog. sarvam also offers cloning through a separate api, so a cloned voice is an option on both platforms.

cartesia bills extra usage through optional overages on a paid subscription and managed agents use a separate balance from tts credits.

cartesia pricing

cartesia's paid plans start at $5 (about ₹475) a month for pro. you get 100,000 credits, with one sonic credit covering one character, plus commercial use and instant cloning. professional cloning starts on the startup plan.

when should you choose cartesia?

• your app already writes hindi in latin letters. sonic 3.6 supports that form of hindi with english words mixed in. keep the supported text combinations in mind when preparing replies.

• you want to test model updates before adopting them. a dated release lets you keep the current version running while you listen to how the next one handles your app's content.

• you want to adapt a recorded voice for more languages. cartesia has cloning and added language accents, with access and allowances tied to the plan you choose.

bottom line

if your app uses romanized hindi and you want to choose when its speech model changes, cartesia is a sarvam ai alternative with both controls. its paid plans use credits and optional overages, while sarvam offers pay-as-you-go access.

7. elevenlabs

• product type: text-to-speech api, voice creation, speech recognition, and managed voice agents

• recommended users: teams creating indian-language narration, character dialogue, and conversational apps

• pricing options: pay-as-you-go, monthly subscriptions, and custom enterprise plans

what is elevenlabs?

elevenlabs offers speech generation, voice design and cloning, transcription through scribe, and managed conversations through elevenagents. its eleven v4 model supports expressive narration and multi-speaker dialogue. eleven v4 turbo streams speech for live conversations through a separate text-to-dialogue websocket.

key features

• a voice you can save and reuse: voice design generates previews from a written description of the speaker. you choose one and save it for later speech requests. the feature is still experimental, and results vary with the description and use case.

• delivery within a line: v4 supports audio tags such as [whispering] and [laughing]. these guide the selected voice's performance at particular points in the text.

• two cloning options: instant cloning uses a short recording. professional cloning trains on more audio and requires verification that the voice is your own.

how does elevenlabs compare to sarvam ai?

voice design is a separate step in elevenlabs: you select a preview, save it, and use that voice's id in speech requests. audio tags then guide its delivery. sarvam also offers cloning through a separate api.

the v4 family adds languages such as nepali and sindhi beyond bulbul's current stock-voice language list. for hindi-english conversations, hinglish mode is configured through elevenagents.

elevenlabs pricing

elevenlabs' api pricing is $0.08 (about ₹7.61) per 1,000 characters for v4 and $0.04 (about ₹3.80) for v4 turbo [approximate inr equivalents at 27 october 2026 exchange rates]. you can pay by usage or choose a subscription. instant cloning is available on starter plan, while professional cloning requires creator plan or above.

when should you choose elevenlabs?

• you want to create a voice once and keep using it. voice design lets you try a speaker description, listen to the previews, and save the one you want for later narration or app replies.

• your content has several speaking roles. text to dialogue gives each role its own voice, which is useful for lessons, audiobooks, and character conversations.

• you need languages beyond bulbul's catalog. the v4 family includes nepali and sindhi alongside hindi, tamil, and other indian languages. select a voice that suits the audience and listen to it in each language you need.

bottom line

if you want a saved custom voice for indian-language narration and multi-speaker dialogue, elevenlabs is a sarvam ai alternative for that workflow.

which sarvam ai alternative should you choose?

choose based on what you need to change in your current setup:

• rumik silk if you want affordable unlimited text to speech with expressive voice models, starting at ₹9,999 a month.

• smallest.ai if you need indian-language voices alongside french, japanese, or arabic through lightning v3.1 pro.

• gnani.ai if you want text-to-speech, transcription, and cloning under a custom enterprise agreement.

• murf if assamese is part of your audience and you want a hosted speech api with pronunciation dictionaries.

• indic-speak if you're making mixed-language educational audio and want a choice between hosted access and running the model yourself.

• cartesia if your app uses romanized hindi and you want to test dated model releases before adopting them.

• elevenlabs if you want to create a saved custom voice or give several speaking roles their own voices in v4 dialogue.

keep sarvam if its voices, supported languages, and costs already work for your app. you can try another provider on a small part of the workload before deciding whether to move more of it.

is rumik silk right for you?

rumik silk is a sarvam ai alternative i'd recommend if:

• you want a team that takes initiative. rumik is a small, hands-on team that makes your company's needs a priority, takes ownership of your questions, and works with you to get things moving.

• you want to judge the voice for yourself. try your own text in the rumik playground before changing your app's integration.

• you want an easier switch. the api quickstart and sdk give you integration examples to build from, so you can try silk in your app before committing to a full migration.

start with the api quickstart to make your first speech request.