# AssemblyAI vs Whisper (OpenAI)

AssemblyAI records 453,591 monthly visits with -6.9% month-over-month growth and Freemium, Contact for Pricing pricing. Whisper (OpenAI) records 0 monthly visits with — growth and Free pricing.

| Metric | [AssemblyAI](https://openaitools.app/tool/assemblyai) | [Whisper (OpenAI)](https://openaitools.app/tool/whisper-github) |
| :--- | :--- | :--- |
| Website URL | https://www.assemblyai.com | https://github.com/openai/whisper |
| Categories | AI Speech-to-Text, AI Transcription, AI Speech Recognition, AI Developer Tools | AI Speech Recognition, AI Speech-to-Text, AI Transcriber, AI Translate |
| Pricing Model | Freemium, Contact for Pricing | Free |
| Monthly Visits | 453,591 | 0 |
| MoM Growth Rate | -6.9% | — |
| Primary Market | Brazil | Global |
| Direct Visits | 281,472 | 0 |
| Review Score | 4.6 | 4.8 |
| Saved Count | 9 | 3 |
| Supported Platforms | Website | Open Source |

## AssemblyAI

AssemblyAI builds speech AI models and the infrastructure to run them, aimed at developers and product teams adding voice to an application. Its core offering is speech-to-text: an asynchronous API for pre-recorded audio, a realtime API for streaming and voice agents, and a synchronous API for short clips and dictation. The company's flagship accuracy model is marketed as top of independent benchmarks, with strong speaker diarization and native code-switching across dozens of languages.

On top of transcription, AssemblyAI offers a Speech Understanding API that layers tasks such as summarization, sentiment, topic detection, PII redaction, content moderation and guardrails onto transcripts. It has also released its first text-to-speech model, AssemblyAI-TTS-1, built for voice agents on live calls, plus an LLM Gateway for routing model calls and a Dictation API. Models can run on AssemblyAI's managed inference cloud, or self-hosted in a customer's own VPC or on-premises environment.

Pricing is pay-as-you-go after a free trial: for example, pre-recorded transcription is billed per audio hour, with optional add-ons such as speaker diarization, keyterms prompting and medical or veterinary modes priced separately. Enterprise plans offer custom rate limits, higher concurrency and compliance features including SOC 2 Type 2, HIPAA and GDPR.

**Pricing & Plans:** Free trial to start, then pay-as-you-go per audio hour and per add-on feature — for example around $0.15/hr for the Universal-2 model and around $0.21/hr for the more accurate Universal-3.5 Pro model, with extras like diarization billed individually. Enterprise and custom-rate-limit plans are available via sales.

- **Async, realtime and sync speech-to-text:** Choose pre-recorded transcription for files, a realtime API for live streams and voice agents, or a synchronous endpoint for short clips and dictation.
- **Audio intelligence and Speech Understanding:** Layer summarization, sentiment, topic detection, PII redaction, content moderation and guardrails onto transcripts without building your own models.
- **Text-to-speech for voice agents:** AssemblyAI-TTS-1 is trained on real phone calls for natural, low-latency speech, targeted at IVR and voice-agent use cases.
- **High accuracy with diarization:** Flagship models emphasise exact transcription, speaker labels and native code-switching across many languages, supported by published benchmarks.
- **Flexible deployment:** Run models on AssemblyAI's managed cloud with unlimited concurrency, or self-host in your own VPC or on-prem for full data control.

**Strengths:** One API family covering transcription, understanding and text-to-speech; Transparent per-hour pay-as-you-go pricing with a free trial; Self-hosting option for teams with strict data-residency requirements; Strong accuracy and diarization performance backed by published benchmarks

**Limitations:** Costs scale with volume and add-ons can raise the effective per-hour rate; Some advanced features are model-specific and not available on every model; Heavier product surface than a simple transcription API may be overkill for basic needs

[Profile (Markdown)](https://openaitools.app/tool/assemblyai.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 AssemblyAI and Whisper (OpenAI) compare in monthly traffic?

AssemblyAI has 453,591 monthly visits, while Whisper (OpenAI) has 0. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

AssemblyAI has a month-over-month growth rate of -6.9%; Whisper (OpenAI) has —.

### How does pricing compare?

AssemblyAI: Freemium, Contact for Pricing. Free trial to start, then pay-as-you-go per audio hour and per add-on feature — for example around $0.15/hr for the Universal-2 model and around $0.21/hr for the more accurate Universal-3.5 Pro model, with extras like diarization billed individually. Enterprise and custom-rate-limit plans are available via sales. 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 | Enterprise developer platform and API for deploying GPT-6 Astra, Sol, Luna, and realtime multimodal agents. | [.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 | Excels at ultra-low latency text-to-speech generation, but focuses less on comprehensive asynchronous audio intelligence and summarization. | [.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 | [Vapi](https://openaitools.app/tool/vapi) | 662,301 | -11.4% | Freemium | Specializes in orchestrating complete conversational voice agent pipelines rather than raw standalone transcription APIs. | [.md](https://openaitools.app/tool/vapi.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 | [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) |
| 9 | [Soniox](https://openaitools.app/tool/soniox) | 335,647 | +2.2% | Paid | Delivers high-accuracy speech-to-text and translation across numerous languages, but with a more streamlined feature set. | [.md](https://openaitools.app/tool/soniox.md) |
| 10 | [OpenWhispr](https://openaitools.app/tool/openwhispr) | 291,756 | -13.3% | Free | Free open-source dictation that runs speech-to-text on your own machine | [.md](https://openaitools.app/tool/openwhispr.md) |

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

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