Skip to main content
Pulse is a high-accuracy, low-latency speech-to-text model built for real-time transcription across 39 languages, with streaming and non-streaming support.

64ms

TTFT at 1 concurrency

300ms

TTFT at 100 concurrency

39 Languages

Streaming + Non-streaming

2 Modes

Streaming + Non-streaming

​
Model Overview

​
Key Capabilities

Real-Time Optimized

Ultra-low latency architecture delivering 64ms TTFT at 1 concurrency and 300ms at 100 concurrent requests — designed for live transcription and conversational AI.

Multi-Language

39 languages supported across streaming and non-streaming modes, with automatic language detection and code-switching within a single session.

PII / PCI Redaction

Built-in redaction of personal and payment card data, enterprise-ready for both streaming and non-streaming use cases.

Speaker Diarization

Automatic multi-speaker identification available across both modes. Streaming diarization is enterprise-ready; non-streaming is available with a cap of 4 speakers.

Noise Reduction

Background noise handling built into the model — enterprise-ready in streaming mode.

Code-Switching

Supports multi-language audio within a single session. Best used by setting the known primary language (e.g. es for Spanish handles English+Spanish automatically).

​
Performance & Benchmarks

Word Error Rate (WER) by language evaluated on the FLEURS dataset. Lower is better. NA = not available or not supported by that provider.
Evaluation. FLEURS dataset across 32 languages. Competitor numbers sourced from AssemblyAI published benchmarks and Deepgram internal benchmarks.

​
Streaming

​
Pre-recorded

​
Features — Non-streaming

​
Features — Streaming

​
Supported Languages — Non-streaming

​
Supported Languages — Streaming

​
Best Practices

​
Specify the language parameter when known

When the language of the audio is known in advance, always set it explicitly rather than relying on automatic detection. This yields better transcription accuracy because the model can optimize directly for that language without needing to first identify it. For example, setting the language parameter to es (Spanish) tells the model to expect Spanish audio, which also handles English+Spanish code-switching scenarios. This produces more accurate outputs compared to using the multi parameter.
When to use multi:
  • When the language is truly unknown beforehand
  • When processing audio from varied or unpredictable sources

​
Use features only when needed

Enable optional features (diarization, PII redaction, timestamps) only when the use case requires them. Unnecessary features add latency.

​
Use Cases

​
Direct use

  • Real-time call transcription
  • Voice assistant input
  • Meeting transcription
  • Accessibility and captioning
  • Customer support recording analysis

​
Downstream use

  • Multi-turn conversational agents
  • Voice-to-text pipelines
  • Telephony and IVR systems
  • Content indexing and search
  • Compliance and audit logging

​
Limitations & Safety

​
Known Limitations

Accuracy varies across languages. The following gaps are known and actively being addressed:
  • Hindi — still training on proper nouns and order IDs; not enterprise-ready for non-streaming
  • Low-resource languages — Kannada, Malayalam, Marathi, Gujarati, Telugu, Oriya, Bengali, Punjabi, Tamil, Japanese, Cantonese, Mandarin, Korean, Tagalog, Indonesian, and Malay are available but not yet enterprise-ready
  • Language detection (multi) — automatic language identification does not perform reliably enough for production workloads; specify the known language parameter instead
  • Non-streaming speaker diarization — capped at 4 speakers; known accuracy issues; contact support for higher speaker count requirements
  • Audio quality — transcription accuracy is directly affected by input audio quality; background noise, low bitrate, or overlapping speech may degrade results even with noise reduction enabled
  • Code-switching — works best when the primary language is explicitly set; fully automatic multi-language detection in a single audio stream is not enterprise-ready

​
Safety & Compliance

Pulse must not be used for:
  • Recording or transcribing individuals without their explicit consent
  • Surveillance, stalking, or any form of unauthorized monitoring
  • Any illegal or unethical purposes
Additionally:
  • Usage is monitored for policy compliance
  • For compliance documentation (GDPR, SOC2, HIPAA), contact support@smallest.ai

​
Contact