Replicate hosts OpenAI’s Whisper Large-v3 as a public prediction: you send a file or URL, pick a task (transcribe or classic Whisper translate-to-English), and pay for the Nvidia T4 seconds that prediction uses. The model page (checked November 1, 2026) shows a typical run around $0.00035–$0.00036, with predictions often finishing in about two seconds on sample audio. That figure is a sample-scale estimate — it is not a published real-time factor for hour-long lectures.
The LecSync Realtime Speech API is a managed WebSocket for live meeting and lecture captions: preview and final text, translation between any two of 60 languages, a speaker and audio-aligned timestamps on every final segment, and running minutes. It costs $0.006 per audio minute ($0.36 per hour) with those features included.
Figures below were checked on November 1, 2026 against Replicate’s openai/whisper model page, hardware pricing (T4 at $0.000225/sec / $0.81/hr), Replicate’s streaming predictions docs, and the LecSync developers page. Replicate does not publish a dollars-per-audio-minute rate for Whisper, so any $/min or 1,000-hour conversion below is labeled Estimated with the RTF assumption stated.
What is Replicate Whisper vs a realtime caption API?
Replicate Whisper is a batch / file ASR prediction: send a file or URL, get text, and pay Nvidia T4 GPU seconds. A realtime caption API such as LecSync keeps one managed socket open for live bilingual captions, speakers and minutes while people talk, billing accepted audio duration. Replicate “streaming” means SSE progressive tokens—not a mic live-caption WebSocket.
The short answer
If you want cheap hosted Whisper for files or URLs — short GPU-second bills, classic multilingual recognition, and English-only Whisper translate — Replicate fits. Typical playground-scale runs land near $0.00035 on T4; longer files scale with compute seconds, not a flat audio-minute SKU.
If you need live bilingual captions + speakers + digest on one flat minute bill, LecSync is the closer product. Replicate openai/whisper is not a managed live-caption WebSocket with any-to-any translation, speakers and minutes packaged into $0.006 per audio minute.
How each path works
LecSync. Your server calls POST https://api.lecsync.com/v1/realtime/connect with the audio format, a language pair and the features you want, then streams 16 kHz mono PCM. Preview text arrives while someone is still talking; a final segment settles once the sentence confirms. Translations share the segment ID. With speakers: true, each final carries a speaker and startMs/endMs on the recording clock. With digest: true, minutes arrive section by section. The first word shows up about 0.28 seconds after speech starts; translation adds roughly 88 ms. Seven gateway regions (dal, jp3, kc, nj, ru2, ru3, uk) keep audio near the capture point; backlog is capped at 2 seconds.
Replicate openai/whisper. Create a prediction against openai/whisper with an audio file or URL. The hosted build runs Whisper Large-v3 on Nvidia T4. Tasks follow classic Whisper: transcription in many languages, or translate into English only. Public models on Replicate are billed by hardware × time; the pricing page lists T4 at $0.000225 per second ($0.81 per hour). The model page’s ~$0.00035 typical cost and “typically complete within 2 seconds” note are estimates that vary with inputs — treat them as sample-scale, not a throughput SLA for long lectures.
Pricing: published GPU seconds vs audio minutes
| Path | Published figure (Nov 1, 2026) | What you actually buy |
|---|---|---|
| LecSync Realtime Speech API | $0.006 / audio minute all-in | Accepted audio duration; STT + MT + speakers + digest |
| Replicate Nvidia T4 (public models) | $0.000225 / sec ($0.81 / hr) | GPU seconds while the prediction runs |
| openai/whisper typical run (model page) | ~$0.00035–$0.00036 | Sample-scale estimate; varies by inputs |
Estimated audio-minute conversions (assumptions stated): Replicate publishes no Whisper $/audio-minute. Any $/audio-min or 1,000-hour figure is Estimated from GPU-seconds × real-time factor (RTF):
- Sample-scale short clips: model page ~$0.00035 per run finishing in ~2 seconds — useful for playground cost sense, not hour-long RTF.
- Batch faster than realtime (example RTF 0.1): 1,000 audio hours → ~100 T4 GPU hours → Est. ~$81 at $0.81/hr list. Effective Est. $/audio-min ≈ $0.00135 under that throughput — before queueing, retries or colder starts.
- Near-realtime coverage (example RTF 1.0): 1,000 audio hours → ~1,000 T4 hours → Est. ~$810. Effective Est. $/audio-min ≈ $0.0135.
LecSync stays $0.006/min whether translation, speakers and digest are on or off → 1,000 audio hours = $360.
Nearby Whisper unit-price posts (different vendors): Groq Whisper, Cloudflare Workers AI Whisper, Hugging Face Inference Endpoints Whisper. Self-host without a cloud $/min: Whisper.cpp.
Side-by-side facts (checked November 1, 2026)
| LecSync Realtime Speech API | Replicate openai/whisper | |
|---|---|---|
| Primary job | Live meeting/lecture captions + MT | Hosted Whisper Large-v3 file/URL ASR |
| Price model | $0.006/audio-min flat, all features | T4 $/sec; typical run ~$0.00035 (varies); no public $/audio-min |
| Delivery | Managed WebSocket, preview→final | Prediction API (file/URL in, text out) |
| Live any-to-any text MT | 60 languages, same socket | Whisper translate → English only |
| Speakers on live stream | Every final (speakers: true) | Not packaged; needs a separate diarization pipeline |
| Live minutes / digest | digest: true | Build yourself after the transcript returns |
| Languages | 60, auto-detected | Whisper-family multilingual recognition |
| Latency story | ~0.28 s first word; +~88 ms MT | Prediction completes after the file/URL job; sample ~2 s |
| “Streaming” on platform | Live PCM captions | SSE for progressive model tokens (LLM-oriented docs) |
| Regions | 7 gateways; 2 s backlog cap | Replicate-managed prediction capacity |
| Model control | Managed stack | Hosted Large-v3; also Docker/self-run noted on model page |
What 1,000 hours cost (Estimated where labeled)
| Workload | LecSync | Replicate openai/whisper |
|---|---|---|
| Same-language file / batch transcripts | Live API is not the cheapest file path | Estimated from T4 seconds × RTF; often cheap when GPU work is short |
| Continuous live caption coverage | $360 for 1,000 audio hours | Not the product shape; would be DIY streaming + many predictions |
| Translated live captions (arbitrary pair) | $360 | Whisper English-only translate + separate MT you operate |
| Speakers + timestamps during live session | Included | Separate pipeline / other models |
| Live minutes | Included | Post-process with your own summarizer |
| Predictable all-in $/audio-min for captions + MT + speakers | Yes ($0.006) | No published audio-minute SKU |
For flat-vs-add-on vendor math, see what 1,000 hours cost once translation, speakers and summaries are added. For stitching STT + MT yourself, see built-in translation vs a DIY pipeline.
When Replicate Whisper wins
- Short file or URL jobs where T4 seconds stay small and the model-page ~$0.00035 class of bill is attractive.
- Classic Whisper Large-v3 without standing up your own GPU replica.
- English-only Whisper translate from multilingual audio, when post-call text is enough.
- Batch pipelines that already use Replicate predictions, webhooks and Dockerized Cog models.
- Same-language transcripts only, with no need for live any-to-any captions on one socket.
When LecSync fits better
- Translated live captions on one socket — any pair of 60 languages, each translation tied to its segment.
- Speakers and recording-aligned timestamps during the live stream — meeting client with speakers and timestamps.
- Live minutes while the session runs (
digest: true) — live digest vs post-call summarization. - Predictable $0.006/audio-minute billing with no Estimated RTF math for the caption stack.
- Classroom / mixed-language lecture feeds that must keep captions current as the speaker switches languages.
Category winners
| Category | Winner | Why |
|---|---|---|
| Cheap hosted Whisper file/URL batch | Replicate openai/whisper | T4 $/sec; short runs often ~$0.00035 class |
| Published $/audio-min for live captions | LecSync | Flat $0.006 all-in |
| Live any-to-any captions + speakers + digest | LecSync | One WebSocket, one minute bill |
| Transparent public GPU list rate | Replicate | T4 $0.000225/sec ($0.81/hr) |
| Managed first-word latency for live captions | LecSync | Public ~0.28 s / +~88 ms MT |
| Classic Whisper translate→English on files | Replicate | Built into the hosted task |
FAQ
Does Replicate publish a Whisper price per audio minute?
No. Public models are billed by hardware × time. The pricing page lists Nvidia T4 at $0.000225/sec ($0.81/hr). The openai/whisper page shows a typical run around $0.00035, varying by inputs. Any $/audio-minute number is Estimated from GPU-seconds and an RTF assumption.
How does T4 $0.81/hr compare to LecSync’s $0.006 per audio minute?
They meter different things. LecSync charges accepted audio minutes. Replicate charges prediction GPU seconds on T4. At an example RTF of 0.1, Est. effective cost can land near $0.00135/audio-min — still same-language ASR without live MT, speakers or digest. At RTF 1.0, Est. ~$0.0135/audio-min. Label both Estimated.
Is Replicate streaming the same as live captions?
No. Replicate streaming docs cover SSE progressive tokens while a prediction runs; the examples are chat LLMs like Llama. That channel delivers model output as it generates. It is not a managed microphone WebSocket with preview→final bilingual captions, speakers and digest for meetings or lectures.
Does openai/whisper include speaker labels?
The hosted Whisper prediction returns classic Whisper-style text and related model fields. Managed live speaker labels like LecSync’s speakers: true on every final segment are not included in that prediction bill. If you need speaker turns, plan a separate diarization pipeline (another model or your own post-process) on top of the transcript.
When should a live-caption product still use Replicate?
Use Replicate when the heavy work is file or batch Whisper billed as T4 GPU seconds, or when your stack already standardizes on Replicate predictions and webhooks. For a managed realtime speech API at $0.006 per audio minute with translation, speakers and digest on one socket, start from the LecSync developers page.
Final verdict
Replicate openai/whisper wins when you want cheap hosted Whisper for files/URLs, billed as T4 compute at $0.000225/sec ($0.81/hr) with typical short runs near $0.00035. LecSync wins when the product is a managed realtime speech API at $0.006 per audio minute all-in, with live translation, speakers and digest on one connection.
Next step: open the LecSync developers page, create a connect session, and stream three seconds of PCM to see preview→final captions on one bill.