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Whisper for Real-Time Transcription: GPU Sizing and Latency Budget

Whisper Large-v3 is fast enough for real-time transcription on the right GPU. Here is what real-time means in practice, what the latency budget looks like, and which card hits which target.

"Real-time transcription" covers two distinct use cases. Live captioning of streaming audio is one (sub-second time-to-first-word). Transcribing pre-recorded audio faster than wall-clock is another (real-time factor >1×). The right GPU depends on which one you need.

TL;DR

For live captioning with sub-1s latency: RTX 5080 16 GB or larger using Whisper-Streaming. For batch transcription at 5-9× real-time: any 16+ GB Blackwell card. The cheapest credible real-time deployment is the RTX 5060 Ti 16 GB at £119/mo using faster-whisper-large-v3 INT8.

What "real-time" means for STT

Two definitions:

  1. Real-time factor (RTF): how many seconds of audio the model transcribes per second of wall time. RTF=1 = real-time. RTF=5 = 5× faster than real-time.
  2. Time-to-first-word (TTFW): how long after speech starts before the first word is emitted. The user-visible latency for live captioning.

For batch transcription you want high RTF. For live captioning you want low TTFW. The two have different optimal configurations.

Backends: faster-whisper, Whisper-Streaming, WhisperX

  • faster-whisper (CTranslate2) — 4× faster than reference Whisper, half the VRAM. Default for batch.
  • Whisper-Streaming — sliding-window streaming on top of Whisper. The right tool for live captioning. Sub-1s TTFW achievable.
  • WhisperX — Whisper + Silero VAD + pyannote diarization. Adds ~200ms but gives speaker labels.
  • Distil-Whisper — distilled small/medium variants. ~2× faster than Whisper Large-v3, English-only, <1% WER regression.

Real-time targets by GPU

GPUWhisper Large-v3 RTFTTFW (Whisper-Streaming)Concurrent streams
RTX 3050 6 GB~3×~1.2 s1-2
RTX 3060 12 GB~4×~900 ms2-3
RTX 5060 Ti 16 GB~5×~700 ms3-5
RTX 5080 16 GB~7×~500 ms5-8
RTX 5090 32 GB~9×~400 ms12-16
RTX 6000 Pro~9×~380 ms20+ (with multi-instance)

Latency budget breakdown

For a sub-1s TTFW live caption pipeline:

StageLatency
Audio capture buffer~100 ms
VAD endpoint detection~100 ms
Whisper inference (sliding window)~250-500 ms
Network return~50 ms
Total TTFW~500-750 ms

Verdict

  • Live captioning, sub-1s: RTX 5080 or 5090 with Whisper-Streaming.
  • Batch transcription, high throughput: any 16+ GB Blackwell card.
  • Voice agent (STT + LLM + TTS): RTX 5090 32 GB. Stack all three on one card.
  • Cheapest credible deployment: RTX 5060 Ti 16 GB.

Bottom line

Whisper is fast. Real-time is achievable on most modern GPUs. The right card depends on whether you need single-stream low-latency (5080/5090) or multi-stream high-throughput (5090/6000 Pro). See Whisper hosting for the deployment-side guide.

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