# Gladia vs Whisper (OpenAI)

Gladia records 232,451 monthly visits with +6.4% month-over-month growth and Freemium, Contact for Pricing pricing. Whisper (OpenAI) records 0 monthly visits with — growth and Free pricing.

| Metric | [Gladia](https://openaitools.app/tool/gladia) | [Whisper (OpenAI)](https://openaitools.app/tool/whisper-github) |
| :--- | :--- | :--- |
| Website URL | https://www.gladia.io | https://github.com/openai/whisper |
| Categories | AI Speech-to-Text, AI API, AI Transcription, Audio To Text AI | AI Speech Recognition, AI Speech-to-Text, AI Transcriber, AI Translate |
| Pricing Model | Freemium, Contact for Pricing | Free |
| Monthly Visits | 232,451 | 0 |
| MoM Growth Rate | +6.4% | — |
| Primary Market | Brazil | Global |
| Direct Visits | 128,515 | 0 |
| Review Score | 4.4 | 4.8 |
| Saved Count | 6 | 3 |
| Supported Platforms | Website | Open Source |

## Gladia

Gladia provides the speech-to-text layer underneath voice products rather than a consumer transcription app. Teams capture audio from live streams, uploads, or real-time microphone input via WebSocket streaming or REST, then receive a clean transcript with timestamped segments. The platform reports hundreds of thousands of users and enterprise teams, and claims top accuracy on conversational audio benchmarks along with leading speaker detection powered by pyannoteAI.

On top of transcription, Gladia bundles native audio intelligence features that are billed only when enabled: speaker diarization, automatic language detection across 100+ languages, code-switching for conversations that mix languages, named entity recognition, PII redaction, sentiment analysis, and summarization. An audio-to-LLM pipeline lets you push transcripts into a large language model, either Gladia-hosted or your own (BYOM).

Integration options include Python and Node.js SDKs, webhooks, Zapier, and 50+ native integrations, plus native meeting-bot support for Zoom, Google Meet, and Microsoft Teams. The company emphasizes enterprise readiness with SOC 2 Type II, GDPR, HIPAA, and ISO 27001 compliance, 99.9% uptime SLA, EU and US hosting, and data-training opt-out by default. A playground, changelog, status page, and benchmark tools are available for evaluation.

**Pricing & Plans:** Gladia uses a freemium model: new developers can start with around €50 in transcription credits that do not expire, and add-on features are billed only when switched on. Enterprise and high-volume plans require contacting sales for custom pricing and SLA terms.

- **Real-time and async speech-to-text:** Stream audio over WebSocket for live captioning or submit files via REST for batch transcription, supporting MP3, WAV, FLAC, Opus, and most other formats.
- **Multilingual with code-switching:** Automatic, accent-sensitive language detection across 100+ languages, including code-switching for conversations that move between languages mid-sentence.
- **Native audio intelligence:** Speaker diarization, named entity recognition, PII redaction, sentiment analysis, and summarization, each billed only when you enable it.
- **Audio-to-LLM pipeline:** Feed transcripts directly into a large language model, either Gladia-hosted or a model you bring yourself (BYOM), to generate summaries and structured outputs.
- **Developer tooling and integrations:** Python and Node.js SDKs, webhooks, Zapier, 50+ integrations, plus meeting-bot support for Zoom, Google Meet, and Microsoft Teams.

**Strengths:** Broad language coverage with real-time code-switching, which many STT vendors lack; Audio intelligence features like diarization, sentiment, and PII redaction are built in rather than chained from multiple providers; Strong compliance posture with SOC 2 Type II, GDPR, HIPAA, and ISO 27001 plus EU hosting; Free starting credits and a public playground make evaluation straightforward

**Limitations:** Developer-focused API product: no simple consumer app for one-off transcription; Enterprise features such as on-premise deployment and some hosting controls are gated behind sales conversations

[Profile (Markdown)](https://openaitools.app/tool/gladia.md)

## Whisper (OpenAI)

Whisper was introduced by OpenAI as a general-purpose speech recognition model trained on a very large, diverse dataset of web audio. Instead of stacking separate acoustic, language and punctuation modules, it treats every speech task as a token prediction problem: transcription, translation, language identification and voice activity detection all share one Transformer encoder-decoder and are distinguished by special task tokens. That single-model design is why a straightforward `pip install` is enough to get multilingual transcription running on a laptop, and why Whisper has become a de facto baseline for open speech-to-text work.

The repository ships six model sizes — tiny, base, small, medium, large and a faster turbo variant — trading accuracy for memory and speed. Each size also has an English-only `.en` counterpart that tends to score better on English audio, while the multilingual checkpoints are the ones to use when translating non-English speech into English. Practical VRAM needs range from roughly 1 GB for tiny up to about 10 GB for large, so the smaller checkpoints run comfortably on consumer hardware or even CPU, while large models are usually paired with a GPU.

Because Whisper is a model and a Python package rather than a hosted product, there is no dashboard, account or quota. You install it, point the command line at audio files, and write your own integration on top. It supports many audio formats through ffmpeg, and its per-language accuracy varies widely — strong for high-resource languages, weaker for low-resource ones — which is worth knowing before adopting it for production transcription.

**Pricing & Plans:** Free and open source. The code and weights are published on GitHub under the MIT license with no usage fees or per-minute charges, though you pay for whatever compute you run it on and any OpenAI API usage if you pair it with their hosted services.

- **Multitask single model:** One Transformer handles transcription, speech translation into English, language identification and voice activity detection, selected through special task tokens.
- **Multiple model sizes:** Choose from tiny, base, small, medium, large and turbo checkpoints, with English-only .en variants, to balance accuracy against VRAM and speed.
- **Broad language coverage:** Multilingual checkpoints transcribe and translate dozens of languages, with automatic language detection on mixed-language audio.
- **Command-line and Python API:** Install via pip with openai-whisper and transcribe files from the terminal or from your own Python code, with ffmpeg handling audio decoding.
- **Permissive MIT license:** Freely embed, modify and redistribute the code and weights in commercial and personal projects without licensing fees.

**Strengths:** Completely free and open source under a permissive MIT license; Strong multilingual accuracy across many languages with automatic detection; Runs locally, so audio never has to leave your hardware; Several model sizes let you match accuracy to available compute

**Limitations:** No hosted UI, account or support — you must install and operate it yourself; Large models need substantial VRAM and a GPU for reasonable speed; Accuracy drops noticeably on low-resource languages and noisy audio; Setup requires Python, PyTorch and ffmpeg, which can be fiddly for non-developers

[Profile (Markdown)](https://openaitools.app/tool/whisper-github.md)

## Frequently Asked Questions

### How do Gladia and Whisper (OpenAI) compare in monthly traffic?

Gladia has 232,451 monthly visits, while Whisper (OpenAI) has 0. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Gladia has a month-over-month growth rate of +6.4%; Whisper (OpenAI) has —.

### How does pricing compare?

Gladia: Freemium, Contact for Pricing. Gladia uses a freemium model: new developers can start with around €50 in transcription credits that do not expire, and add-on features are billed only when switched on. Enterprise and high-volume plans require contacting sales for custom pricing and SLA terms. Whisper (OpenAI): Free. Free and open source. The code and weights are published on GitHub under the MIT license with no usage fees or per-minute charges, though you pay for whatever compute you run it on and any OpenAI API usage if you pair it with their hosted services.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [OpenAI Platform](https://openaitools.app/tool/openai) | 234,678,639 | -9.6% | Paid | Provides Whisper via API for robust speech-to-text, but lacks specialized real-time streaming audio intelligence pipelines. | [.md](https://openaitools.app/tool/openai.md) |
| 2 | [Happy Scribe](https://openaitools.app/tool/happyscribe-com) | 4,088,330 | +8% | Freemium, Free Trial, Paid | AI transcription and meeting notes in 150+ languages | [.md](https://openaitools.app/tool/happyscribe-com.md) |
| 3 | [Cartesia](https://openaitools.app/tool/cartesia-ai) | 1,782,707 | +49.7% | Contact for Pricing | Specializes in ultra-low latency streaming voice infrastructure, though heavily optimized for voice synthesis. | [.md](https://openaitools.app/tool/cartesia-ai.md) |
| 4 | [Video Transcriber AI](https://openaitools.app/tool/video-transcriber-ai) | 1,320,064 | +11% | Freemium | Turn any video or audio into text in seconds | [.md](https://openaitools.app/tool/video-transcriber-ai.md) |
| 5 | [Deepgram Voice AI](https://openaitools.app/tool/deepgram-voice-ai) | 863,852 | +31.8% | Free Trial | Real-time speech-to-text, text-to-speech and voice agents in one API platform | [.md](https://openaitools.app/tool/deepgram-voice-ai.md) |
| 6 | [Salad Transcription API](https://openaitools.app/tool/salad-transcription-api) | 713,519 | +10.4% | Free Trial, Paid | Offers cost-effective batch transcription APIs powered by distributed cloud hardware rather than dedicated streaming infrastructure. | [.md](https://openaitools.app/tool/salad-transcription-api.md) |
| 7 | [Transkriptor](https://openaitools.app/tool/transkriptor-com) | 628,671 | -3.6% | Free Trial, Paid | AI transcription that turns audio and video into searchable text | [.md](https://openaitools.app/tool/transkriptor-com.md) |
| 8 | [AssemblyAI](https://openaitools.app/tool/assemblyai) | 453,591 | -6.9% | Freemium, Contact for Pricing | Speech-to-text and voice intelligence APIs for developers | [.md](https://openaitools.app/tool/assemblyai.md) |
| 9 | [Tongyi Tingwu](https://openaitools.app/tool/tongyi-tingwu) | 425,484 | -10% | Free | Your AI assistant for work and study. | [.md](https://openaitools.app/tool/tongyi-tingwu.md) |
| 10 | [Soniox](https://openaitools.app/tool/soniox) | 335,647 | +2.2% | Paid | Offers highly accurate real-time speech recognition and translation APIs, but features distinct developer tooling. | [.md](https://openaitools.app/tool/soniox.md) |

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Source: https://openaitools.app/compare/gladia-vs-whisper-github

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