ngram vs Whisper
ngram
ngram.com
Whisper
github.comSide by side
| Figure | ngram | Whisper |
|---|---|---|
| Price from | $29/mo | $0.01/mo |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Web | Yes | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | — | Yes |
| Plans published | 5 | 3 |
| Spec score · AI Video Caption Generators | 9.0 (#7) | 9.5 (#1) |
| Company founding | The media kit states that ngram was founded in 2020 in San Francisco, California, with a 10–50-person team. | OpenAI was founded in December 2015. |
| Company legal name | The terms identify the contracting entity as Ngram, a California corporation. | Crunchbase lists the legal name as OpenAI OpCo, LLC and also lists OpenAI LP and OpenAI Group PBC as alternate names. |
| Intended users | The product is presented for teams including product marketing, product management, customer success, founders, sales, educators, and HR. | OpenAI describes the open-sourced models and inference code as a foundation for building applications and further research on robust speech processing. |
| Rating on G2 | 4.5 out of 5 from 28 reviews. | 4.4 out of 5 from 52 reviews. |
| Translation | Translation tools translate scripts, captions and on-screen text and regenerate voiceover and lip synchronization. | Whisper can translate speech from multiple languages into English. |
| What it does | ngram turns prompts, documents, URLs, images, audio or recordings into scripts, storyboards, narrated videos and editable projects. | Whisper is a general-purpose speech-recognition model that supports multilingual transcription, speech translation and language identification. |
Plans
ngram
- FreeFree
- Basic$29 a month
- Premium$59 a month
- Ultimate$299 a month
- EnterprisePriced on request
Whisper
- Self-hosted WhisperFree
- Whisper (open-source code and model weights)Free
- Whisper API$0.01 a month
In their own words
ngram
ngram turns prompts and source material into planned, editable business videos. Inputs can include documents, URLs, screenshots, decks, and recordings. Before rendering, users can review the script, storyboard, scene plan, visual direction, timing, and call to action; afterward, they can revise drafts through chat, a script editor, canvas controls, or a timeline. Projects can include generated visuals, voiceover, captions, motion graphics, translation, and editing. The Free plan costs nothing and gives 600 one-time credits, up to 60 seconds of premium AI-generated footage, 720p exports, and a watermark; no credit card is required. Basic costs $23.20 a month, billed annually, and Premium costs $47.20 a month, billed annually. Ultimate costs $239.20 a month, billed annually. Paid plans include unlimited manual editing and exports, with quality from 720p to 4K depending on plan. ngram is available on the web and as an extension. Social publishing to LinkedIn, X, and YouTube is in beta. The maker was founded in 2020 and is based in San Francisco, California.
Whisper
Whisper is an open-source speech recognition model for transcription, speech translation, language identification, and voice activity detection. Its documented command-line and Python interfaces process audio files, and it can translate speech from multiple languages into English. The repository lists six model sizes—tiny, base, small, medium, large, and turbo—with different speed and memory tradeoffs; stated VRAM needs range from about 1 GB to 10 GB, depending on size. Installation is documented through pip and requires the ffmpeg command-line tool. Rust may be needed if a prebuilt tiktoken wheel is unavailable. The code and model weights are released under the MIT License, with local installation using Python and ffmpeg. Whisper is listed for Linux, macOS, Windows, and self-hosted deployment. OpenAI says it was trained on 680,000 hours of multilingual and multitask supervised data collected from the web. Performance varies widely by language, and it does not outperform models specialized for LibriSpeech. Turbo is not trained for translation; multilingual models are recommended for translating non-English speech into English.