Whisper

Name: Whisper
Brand: OpenAI
Rating: 4.6 (18 reviews)

Whisper is OpenAI's automatic speech recognition (ASR) system that transcribes multilingual audio, performs language identification, and optionally translates speech into English via either hosted API endpoints or open-source model weights for local deployment.

Est 2015|Valuation $852B|Raised $186.4B

LinkedIn 11.4M|Website|Web traffic 508.0M|FTEs 4,500|HQ San Francisco, California, US

MarketsFoundation Models

01Competitive Landscape

| Aspect | Whisper (OpenAI) | Deepgram | AssemblyAI | |--------|------------------|---------|------------| | Starting Price | Published per-minute/unit pricing available from the vendor for hosted transcription | Usage-based plans (varies by feature set) | Usage-based pricing; promotional free credits available | | Primary Use Case | Batch and multilingual transcription; option for local self-hosting | Streaming/real-time transcription and voice platform features | Speech-to-text plus additional audio intelligence features and production packaging | | Key Strength | Availability of open-source weights and support for multilingual transcription | Streaming-first design and enterprise voice platform positioning | Broader feature set (language detection, timestamps, formatting, analytics) as a packaged offering | | Key Weakness | Sensitivity to non-speech segments (hallucinations); productized enterprise controls less visible for the model specifically | Pricing and plan complexity for some buyers | Costs and feature set may be heavier than needed for basic transcription | - Pricing comparison: value proposition vs alternatives - Whisper publishes a clear per-unit price for hosted transcription. Alternative vendors use usage-based pricing models; effective rates vary by chosen features, streaming vs batch modes, and volume commitments. - Feature comparison: strengths and limitations - Whisper strengths - Release of open-source model weights and inference code enables self-hosting and community tooling. - Designed for multilingual transcription with an optional translate-to-English capability. - Whisper limitations - Hallucination on non-speech segments is a documented failure mode that requires mitigation for high-stakes usage. - Product-scoped enterprise features (SLAs, admin controls, compliance attestations) were not clearly documented for Whisper as a standalone offering in the sources reviewed. - Comparative customer feedback - Community and reviewer comparisons tend to focus on latency/streaming needs, pricing tradeoffs, and the level of productization for enterprise features.

01Competitive Landscape

Aspect	Whisper (OpenAI)	Deepgram	AssemblyAI
Starting Price	Published per-minute/unit pricing available from the vendor for hosted transcription	Usage-based plans (varies by feature set)	Usage-based pricing; promotional free credits available
Primary Use Case	Batch and multilingual transcription; option for local self-hosting	Streaming/real-time transcription and voice platform features	Speech-to-text plus additional audio intelligence features and production packaging
Key Strength	Availability of open-source weights and support for multilingual transcription	Streaming-first design and enterprise voice platform positioning	Broader feature set (language detection, timestamps, formatting, analytics) as a packaged offering
Key Weakness	Sensitivity to non-speech segments (hallucinations); productized enterprise controls less visible for the model specifically	Pricing and plan complexity for some buyers	Costs and feature set may be heavier than needed for basic transcription

Pricing comparison: value proposition vs alternatives
- Whisper publishes a clear per-unit price for hosted transcription. Alternative vendors use usage-based pricing models; effective rates vary by chosen features, streaming vs batch modes, and volume commitments.
Feature comparison: strengths and limitations
- Whisper strengths
  - Release of open-source model weights and inference code enables self-hosting and community tooling.
  - Designed for multilingual transcription with an optional translate-to-English capability.
- Whisper limitations
  - Hallucination on non-speech segments is a documented failure mode that requires mitigation for high-stakes usage.
  - Product-scoped enterprise features (SLAs, admin controls, compliance attestations) were not clearly documented for Whisper as a standalone offering in the sources reviewed.
Comparative customer feedback
- Community and reviewer comparisons tend to focus on latency/streaming needs, pricing tradeoffs, and the level of productization for enterprise features.