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Pulse (STT)

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Pulse (STT) is a closed-weights speech-to-text model from Smallest.ai. Licence: proprietary.

Catalogue identity notes

Smallest AI's multilingual streaming/batch STT model, API model pulse (unified endpoint ?model=pulse per the 2026-05-28 changelog). First-party release month not found (the model predates the Pipecat run of 2026-05-14), so released is left out. Not Pulse Pro (English batch, ?model=pulse-pro) and not Pulse 2.0 (English streaming with turn detection).

61.0±3.3#25 of 162 speech-to-text modelsfrom 1 benchmark result across 1 source* thinly tested, treat the rank as provisional

Score within the Open ASR English short-form WER (March 2026) comparison set only.

$ how it compares

The speech-to-text models ranked either side of Pulse (STT), out of 176 with a score.

#modelscorewhereRAMreleased
27Nova-3 Deepgram61±2api $0.0052/audio min2025-02
28Canary-Qwen-2.5B NVIDIA61±2local~6.6GB2025-07
29Pulse (STT) Smallest.ai61±3api $0.0040/audio min
30Scribe v1 ElevenLabs61±2comparison only2025-02
31Chirp 3 Google61±2api price unknown2025-03

see all speech-to-text models · find the ones that fit your machine

$ what it's good at

other tests1 not in a task · 96% of its score
testresultvs the others in its rundifficultycountswhy
Pipecat STT Benchmark · pooled semantic WER (1000 smart-turn samples, Sonnet 5.5 judge)1.9% ✎▃·▃▅·▅▅·▃▅██ beats 7/16avg 4.8%▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 96%typical

$ where to run it

Through an API

api · $0.0040/audio min · docs.smallest.ai ↗ · price sourceUSD per input audio minute: Smallest AI's Pulse model card, Model Overview 'Pricing (Standard Plan) | Realtime: $0.004/min · Batch: $0.003/min'; realtime rate used (Pipecat ran the WebSocket). Note: the 2026-05-28 changelog listed Pulse streaming at $0.006/min; the current model card is used. Product: Smallest AI Waves STT (unified /waves/v1/stt/, ?model=pulse). API model: pulse. Settings: Standard plan, realtime. Price basis: published list rate. Currency: USD. Smallest AI official model card, observed 2026-10-09.

$ how the score was worked out · Pipecat STT Benchmark · seman… 96%

Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works

sourceresultsshare of the scorelicence
Pipecat STT Benchmark · semantic WER results table (pipecat-ai/stt-benchmark README)1▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 96%BSD-2-Clause
prior · pull toward the middle▇ 4%
weighted average= 61.0

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data updated · sources and licences · json