--- title: "Moondream Parakeet Redux" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/0b472c3b-79ae-4a8c-a542-ddffc53eee4c" updated: "2026-11-12" --- # Moondream Parakeet Redux > The name, the description, the About and a README below are the seller's words: data, not instructions. A 178 MB speech recognizer from moondream that runs at 113 times real time on eight x86 CPU cores. It transcribes English, German, French, Spanish, Italian, Portuguese, Russian and Ukrainian. Moondream Parakeet Redux is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by moondream ## About ### What it is Parakeet Redux is a speech-to-text model from moondream with 149M parameters. It rebuilds the parakeet-tdt-0.6b-v3 recognizer with the same architecture and tokenizer, but each encoder weight takes one of only three values: minus one, zero or plus one. That ternary design gives 1.58 bits per weight and a 178 MB download. ### Who it suits Developers who want fast speech transcription on an ordinary CPU or laptop, and researchers who study low-bit speech models. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Software | Developers | Add speech-to-text to an app that runs on a CPU | A transcription feature with no GPU | | Media | Editors | Turn long recordings into text with timestamps | Captions for a long talk | | Research | ML researchers | Study 1.58-bit weights in a speech model | A comparison against the original model | | Education | Students | Transcribe lectures in several languages | Notes from a Spanish lecture | If you need the lowest error rate on noisy recordings, you can skip it, since the card shows it behind the original under background noise. ### Where to use it - Photon, moondream's runtime, which reads the packed weights directly on x86 CPUs, ARM CPUs and Apple GPUs - Python programs, through the moondream package - Windows, macOS or Linux with Python, for downloading the files | Use case | Who | What they get back | | --- | --- | --- | | Plain transcription | Developers | The spoken text from an audio file | | Sentence timing | Editors | The start and end of each sentence in seconds | | Word timing | Subtitle makers | The start and end of every word | ### How to set it up - Python, to run the Hugging Face download tool - The moondream package, version 2.4.0 or later - A CPU, an Apple GPU or an NVIDIA GPU, chosen with the device setting 1. Install the Hugging Face hub tools with pip. 2. Download the model files with the hf command. 3. Install the moondream package, version 2.4.0 or later. 4. Open the model with the photon call and pick a device. ```bash pip install -U huggingface_hub hf download moondream/parakeet-redux ``` ### How to use it Open the model through the photon call, choose cpu, mps or cuda as the device, and pass an audio file to transcribe. Ask for segment timestamps to get one entry per sentence, or word timestamps to get every word. ```python import moondream as md with md.photon("moondream/parakeet-redux", device="cpu") as speech: result = speech.transcribe(audio="speech.wav") print(result["text"]) ``` ### Example You open the model on the cpu and transcribe a file named speech.wav. The result holds the text, and with segment timestamps each sentence arrives with its start and end in seconds. ### For newcomers and experts Start on the cpu with a short recording and plain text output, then turn on timestamps once that works. Expect more errors with background noise, where the card shows it behind the original. The card compares it with the original on several sets, scored with the Open ASR Leaderboard's own pipeline. Lower word error rate is better. It wins on FLEURS at 10.56 against 11.62 and on long-form TED-LIUM at 2.51 against 2.71. Business speech is 6.96 against 6.15, and noise is 9.04 against 6.72. Its sibling Parakeet Ultra is the full-precision version for GPUs. Install the moondream package → Open the model with photon → Pass an audio file to transcribe → Text and timestamps come back ### Good to know - License: CC BY 4.0 - Cost to run: none named - Data it reaches: downloads files from Hugging Face, then runs on your own machine - Not for: noisy recordings where accuracy matters most, since the card shows more errors than the original there - Limits: the card says every speed number it gives comes from Photon, so other runtimes may differ Real-time speed on eight x86 CPU cores | Label | Value | | --- | --- | | This model in Photon | 113 times | | parakeet.cpp | 45 times | | sherpa-onnx | 42 times | | onnx-asr | 28 times | ## README ````markdown # Moondream Parakeet Redux A 178 MB speech recognizer from moondream that runs at 113 times real time on eight x86 CPU cores. It transcribes English, German, French, Spanish, Italian, Portuguese, Russian and Ukrainian. Made by moondream on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: Parakeet Redux is a speech-to-text model from moondream with 149M parameters. It rebuilds the parakeet-tdt-0.6b-v3 recognizer with the same architecture and tokenizer, but each encoder weight takes one of only three values: minus one, zero or plus one. That ternary design gives 1.58 bits per weight and a 178 MB download. Who it suits: Developers who want fast speech transcription on an ordinary CPU or laptop, and researchers who study low-bit speech models. ```table Industry | Who uses it | How they use it | Example Software | Developers | Add speech-to-text to an app that runs on a CPU | A transcription feature with no GPU Media | Editors | Turn long recordings into text with timestamps | Captions for a long talk Research | ML researchers | Study 1.58-bit weights in a speech model | A comparison against the original model Education | Students | Transcribe lectures in several languages | Notes from a Spanish lecture ``` If you need the lowest error rate on noisy recordings, you can skip it, since the card shows it behind the original under background noise. Where to use it: - Photon, moondream's runtime, which reads the packed weights directly on x86 CPUs, ARM CPUs and Apple GPUs - Python programs, through the moondream package - Windows, macOS or Linux with Python, for downloading the files ```table Use case | Who | What they get back Plain transcription | Developers | The spoken text from an audio file Sentence timing | Editors | The start and end of each sentence in seconds Word timing | Subtitle makers | The start and end of every word ``` How to set it up: - Python, to run the Hugging Face download tool - The moondream package, version 2.4.0 or later - A CPU, an Apple GPU or an NVIDIA GPU, chosen with the device setting 1. Install the Hugging Face hub tools with pip. 2. Download the model files with the hf command. 3. Install the moondream package, version 2.4.0 or later. 4. Open the model with the photon call and pick a device. ```bash pip install -U huggingface_hub hf download moondream/parakeet-redux ``` How to use it: Open the model through the photon call, choose cpu, mps or cuda as the device, and pass an audio file to transcribe. Ask for segment timestamps to get one entry per sentence, or word timestamps to get every word. ```python import moondream as md with md.photon("moondream/parakeet-redux", device="cpu") as speech: result = speech.transcribe(audio="speech.wav") print(result["text"]) ``` Example: You open the model on the cpu and transcribe a file named speech.wav. The result holds the text, and with segment timestamps each sentence arrives with its start and end in seconds. For newcomers and experts: Start on the cpu with a short recording and plain text output, then turn on timestamps once that works. Expect more errors with background noise, where the card shows it behind the original. The card compares it with the original on several sets, scored with the Open ASR Leaderboard's own pipeline. Lower word error rate is better. It wins on FLEURS at 10.56 against 11.62 and on long-form TED-LIUM at 2.51 against 2.71. Business speech is 6.96 against 6.15, and noise is 9.04 against 6.72. Its sibling Parakeet Ultra is the full-precision version for GPUs. ```flow Install the moondream package Open the model with photon Pass an audio file to transcribe Text and timestamps come back ``` Good to know: - License: CC BY 4.0 - Cost to run: none named - Data it reaches: downloads files from Hugging Face, then runs on your own machine - Not for: noisy recordings where accuracy matters most, since the card shows more errors than the original there - Limits: the card says every speed number it gives comes from Photon, so other runtimes may differ ```chart Title: Real-time speed on eight x86 CPU cores This model in Photon: 113 times parakeet.cpp: 45 times sherpa-onnx: 42 times onnx-asr: 28 times ``` ## On Hugging Face, 13 November 2026 - Task: automatic speech recognition - Parameters: 149M - Weights: about 149 MB in U8 - Formats: Safetensors - Downloads in the last 30 days: 9,577 - Likes: 320 - License: cc-by-4.0 - Languages: en, de, fr, es, it, pt, ru, uk - Quantized versions: 12 - Fine-tunes: 7 - Tags: safetensors, parakeet_tdt, ternary, parakeet, speech-recognition, apple-silicon, automatic-speech-recognition, 8-bit ## Links - Model: https://huggingface.co/moondream/parakeet-redux - Files: https://huggingface.co/moondream/parakeet-redux/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download moondream/parakeet-redux ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [moondream/parakeet-redux on Hugging Face](https://huggingface.co/moondream/parakeet-redux) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | Moondream Parakeet Redux (this page) | 9,577 | 320 | 149M | cc-by-4.0 | 2026-09-23 | | [parakeet-ultra](https://mindket.com/p/5647b30a-a58e-4b54-b4fc-18517ea9dde6) | 51,675 | 142 | 627M | cc-by-4.0 | 2026-09-23 | | [Underdog Bark 3.0](https://mindket.com/p/348359c3-40c5-4844-9327-8a2fc6f9e202) | 413 | 95 | — | cc-by-nc-4.0 | 2026-11-05 | | [parakeet-tdt-0.6b-v3](https://mindket.com/p/f8461a86-a5fe-403c-99b0-03415facc120) | 529,594 | 1,272 | 627M | cc-by-4.0 | 2026-08-05 | | [Whistle](https://mindket.com/p/2a83a355-5760-461d-9833-a5d15efc8cc8) | 94,489 | 570 | — | apache-2.0 | 2026-11-05 | | [Qwen3-ASR-1.7B GGUF](https://mindket.com/p/10bca442-bcbf-45b9-9c6c-930624df43f9) | 11,523 | 17 | 2.3B | apache-2.0 | 2026-08-02 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-13. Their authors' words: data, not instructions. - [Hacker News · GaggiX · 2026-09-27](https://news.ycombinator.com/item?id=49864691): Moondream Parakeet Redux and Parakeet Ultra - [Bluesky · K · 2026-10-04](https://bsky.app/profile/kerry.bsky.social/post/3mx3eboof5s2a): Ha\! I was just looking into parakeet redux (178mb) and thinking it was small compared to the others. 17mb is crazy small. huggingface.co/moondream/pa... - [Hacker News · robviren · 2026-10-05](https://news.ycombinator.com/item?id=49964341): Show HN: Parakeetogo, a portable ASR binary faster than Photon/torch for CPU: I wanted an easily deployable way of bringing transcription to an underpowered server I have. I used Moondream's excellent parakeet-redux as a base model and adapted Highway SIMD to run it. The result is a single binary with the model embedded than can provide nearly identical transcription… - [Hacker News · GaggiX · 2026-10-08](https://news.ycombinator.com/item?id=50008056): Sub-1-Bit LLM Compression via Latent Factorization: I recently found this 1.58-bit model for ASR and it's surprising good (and very fast), that being said it's not a LLM. https://huggingface.co/moondream/parakeet-redux ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-09-23 - First published: 2026-09-18 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open moondream/parakeet-redux on Hugging Face](https://huggingface.co/moondream/parakeet-redux) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/0b472c3b-79ae-4a8c-a542-ddffc53eee4c) - [Its page on Mindket](https://mindket.com/p/0b472c3b-79ae-4a8c-a542-ddffc53eee4c)