The cheapest Sarvam AI alternative — measured, not asserted.
Word error rate (WER), speech-to-text (STT / ASR), text-to-speech (TTS), and a real-time voice agent for AI calling — every claim below is a measurement against Sarvam AI, on real Indian-language audio, with the methodology and sample size stated next to the number.
- 20.6% vs 35.4%
- hearing WER on real calls
- 81.1 vs 73.1
- blind-judged reply score
- ₹65.74 vs ₹166.7
- per call-hour, published rates
- ₹20 vs ₹30
- speech-to-text, per hour
A voice agent that hears right, judged blind against Sarvam.
Osprey Live takes the caller's speech in and speaks back on one WebSocket, calling your tools in between. Measured against Sarvam's own speech-to-text, LLM and text-to-speech on the same real phone calls.
Osprey LiveSarvam stack- Reply quality, blind judge81.173.1+8.0 points
- Word error on the caller's speech20.6%35.4%14.8 points lower
- Price per call-hour, all in₹65.74≈₹166.7061% less
- First audio after the caller stops2.4–3.1 s4–6 sOsprey Live faster
2 real Marathi phone calls, 58 turns — directional. The judge was never told which stack answered, and the order was shuffled twice. Prices are published list rates. Sarvam's first audio is with its LLM's thinking on (≈1.1 s with it off).
- Your own tools, mid-callDescribe the agent and its tools once; it calls them while the caller is still on the line.Live · session.configure, your own tool list
- Both languages, one socketHindi and English on the same WebSocket and the same brief.Live today
The same accuracy, for a third less.
Lark is built and measured on the audio Indian products actually have: 8 kHz phone calls, code-mixed, mostly not in English.
Lark miniSarvam- Price per hour of audio₹20₹3033% less
- Speaker labels, per hour+₹3.50+₹1577% less
- Accuracy on 102 real 8 kHz calls82.380.8Level
Accuracy is level: 1.5 points on 102 calls is inside the noise. The claim is the same accuracy for less, never “more accurate”.
- Telephone audio costs nothing8 kHz calls were measured twice against wideband audio: zero accuracy lost.Measured twice · 8 kHz vs wideband
- Code-mix comes back in the script it was spoken inCode-mixed speech comes back in the script it was spoken in, and the response says which.Live · stated default
- A hint you can send, that cannot hijack the jobSend name spellings or domain terms; they are added to the instruction, never swapped for it.Live · appended, not substituted
- Indian languages, first classEvery accuracy number here was taken on Indian-language call audio.Live today
- Speaker labels with a timestamped timelinediarize=true adds who spoke when for ₹3.50 an hour, skipped and free on pre-split stereo.Live · diarize=true
ComingTranscribe and translate in one call.Not available today.
Three voice tiers, from ₹21 an hour.
Pica speaks Hindi and English. nano has seven emotions, small adds 25 voices, and large is the most natural. Every tier is billed per second of audio.
PicaSarvam- pica-nano, per hour of audio₹21≈₹15186% less
- pica-small, per hour of audio₹32≈₹15179% less
- pica-large, most natural₹60≈₹15160% less
Sarvam publishes ₹30 per 10,000 characters; its column is that rate at 14 characters a second, about as slowly as our slower Hindi voices read. Pica is billed per second of audio received.
{
"model": "pica-nano",
"input": "…",
"voice": "ankita",
"lane": "expressive",
"emotion": "neutral"
}Seven emotions, enforced, on the expressive (Hindi) lane. The standard lane covers both languages and has none.
- Seven emotions, on the expressive laneSeven emotions on the Hindi lane; an unknown one is a 400, not a flat reading billed anyway.Live · lane=expressive
- Eleven voices, live todaySeven Hindi and four English, each pinned to a reference clip so it never drifts.Live · GET /v1/audio/voices
ComingBring your own voice: designed from a description or cloned from a clip.Not available today.
Sarvam AI alternative — frequently asked
Is MiniCrow cheaper than Sarvam AI?
For speech-to-text (Lark vs Sarvam's transcription), yes — ₹20 against Sarvam's published ₹30 per hour of audio, about a third less, at level accuracy on 102 real 8 kHz Marathi calls. For a full calling agent (Osprey Live vs Sarvam's own speech-to-text, LLM and text-to-speech stack), MiniCrow's published rate works out to about ₹66 per call-hour against roughly ₹167 for Sarvam's own per-unit rates on the same call shape.
Is MiniCrow more accurate than Sarvam?
For text (Lark's speech-to-text), the two are level — 82.3 against 80.8 on 102 real calls, inside the noise; the honest claim is the same accuracy for less, never “more accurate.” For calling, Osprey Live's hearing measured a lower word error rate (20.6% against 35.4%) and its replies scored higher on a blind judge (81.1 against 73.1) on the same two real calls — a small, directional sample, stated as such.
Does MiniCrow support speaker diarization?
Yes. Lark's diarize=true returns who spoke when — a speaker number with start and end times per turn — for ₹3.50 per hour of audio on top of the tier, and it is not billed if the speaker pass fails. A stereo call recorded one party per channel is already separated and the pass is skipped. Sarvam publishes batch transcription with diarization at ₹45 an hour against ₹30 without it — ₹15 an hour for the same step.
Which is faster, MiniCrow or Sarvam, for a live phone call?
It depends on Sarvam's thinking setting. With its LLM's thinking on, Sarvam's calling stack takes 4–6 seconds to first audio and Osprey Live, at 2.4–3.1 seconds, is faster. With thinking off, Sarvam's realtime stack answers in about 1.1 seconds, which is faster than Osprey Live. The case for Osprey Live is hearing accuracy, reply quality and price.
What languages does MiniCrow support?
Lark (speech-to-text) covers 21 languages including Hindi, Marathi and code-mixed Hinglish. Osprey Live (the voice agent) supports Hindi and English today, with more Indian languages measured before they ship.
Full methodology, sample sizes and every number's source: the API reference and /agent.md. Sarvam is a named third party for comparison only; MiniCrow is not affiliated with Sarvam AI.