Whisper or Parakeet: which to choose for business

Both handle Russian, run on a CPU and scale to a single GPU. Whisper is MIT with commercial use allowed, recognizes 99 languages and ranges from 39M to 1.5B. The NVIDIA line includes streaming models for real-time use, ranges from 110M to 2.5B, and supports Russian in Parakeet TDT v3 and Nemotron 3.5 ASR; licenses vary (CC-BY-4.0, NVIDIA Open Model License, OpenMDW), and the first Canary-1B is non-commercial. NVIDIA's latest release is 2026-05, Whisper's is 2025-03.

Comparison based on catalog data

ParameterWhisperNVIDIA Parakeet / Canary / Nemotron Speech
CategorySpeech to textSpeech to text
DeveloperOpenAI, USANVIDIA, USA
ReleasesSep 2022 – Mar 2025Dec 2023 – May 2026
Sizes39M – 1,5B110M – 2.5B
HardwareLaptop, 1 GPULaptop, 1 GPU
Commercial useCommercial use allowedCommercial use with conditions
LicenseMITMixed: Parakeet and Canary mostly CC-BY-4.0 (the first Canary-1B is non-commercial), Parakeet Unified and Nemotron Speech Streaming under the NVIDIA Open Model License, Nemotron 3.5 ASR under OpenMDW
RussianSupportedSupported
OllamaNoNo
Without GPUYesYes
Tasks
  • Transcription of calls and video meetings
  • Video subtitles
  • Voice messages to text
  • Meeting minutes
  • Transcribing calls and meetings
  • Video subtitles
  • Real-time voice input
  • Tagging audio archives

Choose Whisper if

  • You want one simple MIT license across all versions
  • Your recordings are in many languages: Whisper covers 99
  • You need the smallest model, from 39M
Whisper

Choose NVIDIA Parakeet / Canary / Nemotron Speech if

  • You need real-time voice input: streaming versions are available
  • You are building a voice bot where streaming transcription matters
  • You want a current line-up with 2026 releases
NVIDIA Parakeet / Canary / Nemotron Speech

Other comparisons

Need a model for your task?

An open model can run on your own server: data stays in-house, there is no per-request fee, and the model can be fine-tuned on your documents.

  1. SelectThe model and size for your task and hardware budget
  2. DeployOn your server or in a closed network, with an API
  3. Fine-tuneOn your data, or connect a knowledge base
  4. IntegrateInto your CRM, ERP, bot, website or team chat
Discuss deployment