--- title: "LongCap-35B-A3B-FP8" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/a0e8c5e8-b3c3-4cca-8a06-a399c9705694" updated: "2026-11-13" --- # LongCap-35B-A3B-FP8 > The name, the description, the About and a README below are the seller's words: data, not instructions. Turns recordings up to about two hours long into a timeline of speech, music and sound events with start and end times, and also transcribes speech with speaker labels. FP8 weights for a single H100 80GB GPU. LongCap-35B-A3B-FP8 is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by JinchuanTian ## About ### What it is LongCap listens to a recording, from a few seconds to about two hours, and writes a timeline of what it hears. Each speech, music or sound event gets a start time, an end time and a structured set of attributes. The same checkpoint can also transcribe speech and label who is speaking. This repository holds the FP8 version, sized for one H100 80GB GPU. The model has about 35.3 billion parameters. A BF16 version also exists. ### Who it suits Audio and media developers, researchers and archivists with a large GPU who need detailed, timestamped descriptions of long recordings. It reads English and Chinese. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Media | Archive and post-production teams | Index long recordings by what happens and when | Marking speech, music and sound cues in a film | | Research | Audio researchers | Study long-form audio captioning | Comparing caption quality over two hours of audio | | Accessibility | Caption developers | Produce descriptions beyond plain transcripts | Describing sounds along with dialogue | | Meetings | Transcription developers | Transcribe speech with speaker labels | Writing a speaker-tagged transcript of a long call | Anyone without an H100-class GPU can skip it for now, since the card sizes the FP8 version for one H100 80GB. ### Where to use it - A server or workstation with an H100 80GB GPU, using the longcap library. - The project's code repository and quickstart, which the card points to. - Windows, macOS or Linux with Python, for downloading the files. | Use case | Who | What they get back | | --- | --- | --- | | Audio timeline | Media teams | Events with start and end times and structured attributes | | Speech transcription | Developers | Transcripts with speaker labels | | Long recording captions | Researchers | Captions for recordings up to about two hours in one pass | ### How to set it up You need a large GPU and the project's own code. - An H100 80GB GPU for the FP8 version - The longcap library from the project's code repository - Python and the Hugging Face tool, for downloading - Disk space, since the FP8 weights are about 38.4 GB 1. Install the Hugging Face tool. 2. Download the FP8 files. 3. Follow the quickstart in the project's code repository to run it. ```bash pip install -U huggingface_hub hf download JinchuanTian/LongCap-35B-A3B-FP8 ``` ### How to use it You hand it a recording. It reads the audio piece by piece and logs the events for each piece, while holding on to what came before. The card gives its run steps in the code repository, not in the page text here. Each event has a type of speech, music or sound\_event, a set of attributes and a short caption. The labels inside each event use Chinese words, but spoken words and lyrics stay in the language they were said or sung in. | Tool | What it does | | --- | --- | | speech event | Carries the transcript and speaker traits | | music event | Carries the instruments and tempo | | sound\_event | Carries the source and distance of the sound | ### Example The card ran the model over a 110-minute film in a single pass. Around the 87-minute point the model logged four things: someone's steps fading away, two brief spoken lines and a trumpet solo that signals a change of scene. Each came with times in seconds from the start. ### For newcomers and experts If you are new, think of it as a tool that watches a recording with its ears and writes a detailed log of every voice, tune and noise. Read the quickstart first, since it needs a large GPU. For experts, the model keeps earlier audio and text in context of up to 1M tokens and uses 62 expert-designed attribute keys across speech, music and sound. Only the mixture-of-experts weights are quantized to FP8, the rest stays BF16, and the card says the BF16 and FP8 versions give closely matching output. A recording up to about two hours → The model reads it in short chunks → It writes events for each chunk → Earlier audio and text stay in context → You get a timeline with attributes tcpCapSim on LongCapBench-TAC-Short, higher is better | Label | Value | | --- | --- | | LongCap | 64.6% | | Qwen3.5-Omni-Plus | 52.7% | ### Good to know The points below cover limits and costs. - Output language: attribute names and values are in Chinese, and a key file gives their English names. - Hardware: the FP8 version targets one H100 80GB, and the BF16 version needs two. - License: Apache 2.0. - Cost to run: no API key or paid service is named. A high-end GPU is required. - Data it reaches: it reads the recordings you give it. - Not for: setups without a large GPU. A larger model from the paper is not released. ## README ````markdown # LongCap-35B-A3B-FP8 Turns recordings up to about two hours long into a timeline of speech, music and sound events with start and end times, and also transcribes speech with speaker labels. FP8 weights for a single H100 80GB GPU. Made by JinchuanTian 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: LongCap listens to a recording, from a few seconds to about two hours, and writes a timeline of what it hears. Each speech, music or sound event gets a start time, an end time and a structured set of attributes. The same checkpoint can also transcribe speech and label who is speaking. This repository holds the FP8 version, sized for one H100 80GB GPU. The model has about 35.3 billion parameters. A BF16 version also exists. Who it suits: Audio and media developers, researchers and archivists with a large GPU who need detailed, timestamped descriptions of long recordings. It reads English and Chinese. ```table Industry | Who uses it | How they use it | Example Media | Archive and post-production teams | Index long recordings by what happens and when | Marking speech, music and sound cues in a film Research | Audio researchers | Study long-form audio captioning | Comparing caption quality over two hours of audio Accessibility | Caption developers | Produce descriptions beyond plain transcripts | Describing sounds along with dialogue Meetings | Transcription developers | Transcribe speech with speaker labels | Writing a speaker-tagged transcript of a long call ``` Anyone without an H100-class GPU can skip it for now, since the card sizes the FP8 version for one H100 80GB. Where to use it: - A server or workstation with an H100 80GB GPU, using the longcap library. - The project's code repository and quickstart, which the card points to. - Windows, macOS or Linux with Python, for downloading the files. ```table Use case | Who | What they get back Audio timeline | Media teams | Events with start and end times and structured attributes Speech transcription | Developers | Transcripts with speaker labels Long recording captions | Researchers | Captions for recordings up to about two hours in one pass ``` How to set it up: You need a large GPU and the project's own code. - An H100 80GB GPU for the FP8 version - The longcap library from the project's code repository - Python and the Hugging Face tool, for downloading - Disk space, since the FP8 weights are about 38.4 GB 1. Install the Hugging Face tool. 2. Download the FP8 files. 3. Follow the quickstart in the project's code repository to run it. ```bash pip install -U huggingface_hub hf download JinchuanTian/LongCap-35B-A3B-FP8 ``` How to use it: You hand it a recording. It reads the audio piece by piece and logs the events for each piece, while holding on to what came before. The card gives its run steps in the code repository, not in the page text here. Each event has a type of speech, music or sound_event, a set of attributes and a short caption. The labels inside each event use Chinese words, but spoken words and lyrics stay in the language they were said or sung in. ```table Tool | What it does speech event | Carries the transcript and speaker traits music event | Carries the instruments and tempo sound_event | Carries the source and distance of the sound ``` Example: The card ran the model over a 110-minute film in a single pass. Around the 87-minute point the model logged four things: someone's steps fading away, two brief spoken lines and a trumpet solo that signals a change of scene. Each came with times in seconds from the start. For newcomers and experts: If you are new, think of it as a tool that watches a recording with its ears and writes a detailed log of every voice, tune and noise. Read the quickstart first, since it needs a large GPU. For experts, the model keeps earlier audio and text in context of up to 1M tokens and uses 62 expert-designed attribute keys across speech, music and sound. Only the mixture-of-experts weights are quantized to FP8, the rest stays BF16, and the card says the BF16 and FP8 versions give closely matching output. ```flow A recording up to about two hours The model reads it in short chunks It writes events for each chunk Earlier audio and text stay in context You get a timeline with attributes ``` ```chart Title: tcpCapSim on LongCapBench-TAC-Short, higher is better LongCap: 64.6% Qwen3.5-Omni-Plus: 52.7% ``` Good to know: The points below cover limits and costs. - Output language: attribute names and values are in Chinese, and a key file gives their English names. - Hardware: the FP8 version targets one H100 80GB, and the BF16 version needs two. - License: Apache 2.0. - Cost to run: no API key or paid service is named. A high-end GPU is required. - Data it reaches: it reads the recordings you give it. - Not for: setups without a large GPU. A larger model from the paper is not released. ## On Hugging Face, 13 November 2026 - Task: audio text to text - Library: longcap - Parameters: 35.3B - Weights: about 35.3 GB in F8_E4M3; about 17.7 GB at 4-bit (estimate) - Formats: Safetensors - Downloads in the last 30 days: 65 - Likes: 2 - License: apache-2.0 - Languages: en, zh - Based on: JinchuanTian/LongCap-35B-A3B - Tags: longcap, safetensors, qwen3_5, audio, audio-captioning, timestamped-audio-captioning, dense-audio-captioning, long-form-audio, speaker-diarization, automatic-speech-recognition, music, sound-event-detection ## Links - Model: https://huggingface.co/JinchuanTian/LongCap-35B-A3B-FP8 - Files: https://huggingface.co/JinchuanTian/LongCap-35B-A3B-FP8/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download JinchuanTian/LongCap-35B-A3B-FP8 ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 6 KB, downloaded as a zip. ```text README.md 6 KB ``` ## Source [JinchuanTian/LongCap-35B-A3B-FP8 on Hugging Face](https://huggingface.co/JinchuanTian/LongCap-35B-A3B-FP8) ## 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 | | --- | --- | --- | --- | --- | --- | | LongCap-35B-A3B-FP8 (this page) | 65 | 2 | 35.3B | apache-2.0 | 2026-11-09 | | [AADD](https://mindket.com/p/b58e1376-dc9e-4e2c-991a-1305a3931658) | 73 | 9 | — | mit | 2026-11-09 | | [ACE-Step 1.5](https://mindket.com/p/9bcfe983-0ebe-44d7-811e-8cdfbec7b965) | 98,086 | 952 | — | mit | 2026-02-03 | | [MOSS-Music-8B-Instruct](https://mindket.com/p/22ac5553-267f-4232-b956-0099a33a2dd1) | 2,910 | 53 | 9.1B | apache-2.0 | 2026-05-01 | | [MuLaCover by HeartMuLa](https://mindket.com/p/57e26828-38ab-4d59-82ee-bafe610dbc4b) | 678 | 49 | 4.4B | cc-by-nc-4.0 | 2026-09-15 | | [YuE2-hum-to-song](https://mindket.com/p/a30b24a2-dcc2-40b1-a279-311c515236be) | 0 | 47 | — | cc-by-nc-4.0 | 2026-09-15 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## 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: 2026-11-09 - First published: 2026-10-26 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open JinchuanTian/LongCap-35B-A3B-FP8 on Hugging Face](https://huggingface.co/JinchuanTian/LongCap-35B-A3B-FP8) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/a0e8c5e8-b3c3-4cca-8a06-a399c9705694) - [Its page on Mindket](https://mindket.com/p/a0e8c5e8-b3c3-4cca-8a06-a399c9705694)