Model reference · open weights
kugelaudio-0-open is an open-weight audio or speech model from kugelaudio. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Released by | kugelaudio |
|---|---|
| Type | Audio & music |
| Task | Text→speech |
| Parameters (lead) | 9.3B |
| Released | 2026-01-11 |
| Popularity | 2k downloads / month |
| Licence | Open weights |
About
Open-source text-to-speech for European languages 7B parameter model powered by an AR + Diffusion architecture
License: MIT Python 3.10+ Hosted API
KugelAudio KI-Servicezentrum Berlin-Brandenburg Gefördert durch BMFTR
Open-source text-to-speech models for European languages are significantly lagging behind. While English TTS has seen remarkable progress, speakers of German, French, Spanish, Polish, and dozens of other European languages have been underserved by the open-source community.
KugelAudio aims to change this. Building on the excellent foundation laid by the VibeVoice team at Microsoft, we've trained a model specifically focused on European language coverage, using approximately 200,000 hours of highly pre-processed and enhanced speech data from the YODAS2 dataset.
KugelAudio achieves state-of-the-art performance, beating industry leaders including ElevenLabs in rigorous human preference testing. This breakthrough demonstrates that open-source models can now rival - and surpass - the best commercial TTS systems.
We conducted extensive A/B testing with 339 human evaluations to compare KugelAudio against leading TTS models. Participants listened to a reference voice sample, then compared outputs from two models and selected which sounded more human and closer to the original voice.
The evaluation specifically focused on German language samples with diverse emotional expressions and speaking styles:
These diverse test cases demonstrate the model's capability to handle a wide range of speaking styles beyond standard narration.
| Rank | Model | Score | Record | Win Rate |
|---|---|---|---|---|
| 🥇 1 | KugelAudio | 26 | 71W / 20L / 23T | 78.0% |
| 🥈 2 | ElevenLabs Multi v2 | 25 | 56W / 34L / 22T | 62.2% |
| 🥉 3 | ElevenLabs v3 | 21 | 64W / 34L / 16T | 65.3% |
| 4 | Cartesia | 21 | 55W / 38L / 19T | 59.1% |
| 5 | VibeVoice | 10 | 30W / 74L / 8T | 28.8% |
| 6 | CosyVoice v3 | 9 | 15W / 91L / 8T | 14.2% |
Based on 339 evaluations using Bayesian skill-rating system (OpenSkill)
Listen to KugelAudio's diverse voice capabilities across different speaking styles and languages:
| Sample | Description | Audio Player |
|---|---|---|
| Whispering | Soft whispering voice | |
| Female Narrator | Professional female reader voice | |
| Angry Voice | Irritated and frustrated speech | |
| Radio Announcer | Professional radio broadcast voice |
All samples are generated using pre-encoded voice embeddings.
This model supports the following European languages:
| Language | Code | Flag | Language | Code | Flag | Language | Code | Flag |
|---|---|---|---|---|---|---|---|---|
| English | en | 🇺🇸 | German | de | 🇩🇪 | French | fr | 🇫🇷 |
| Spanish | es | 🇪🇸 | Italian | it | 🇮🇹 | Portuguese | pt | 🇵🇹 |
| Dutch | nl | 🇳🇱 | Polish | pl | 🇵🇱 | Russian | ru | 🇷🇺 |
| Ukrainian | uk | 🇺🇦 | Czech | cs | 🇨🇿 | Romanian | ro | 🇷🇴 |
| Hungarian | hu | 🇭🇺 | Swedish | sv | 🇸🇪 | Danish | da | 🇩🇰 |
| Finnish | fi | 🇫🇮 | Norwegian | no | 🇳🇴 | Greek | el | 🇬🇷 |
| Bulgarian | bg | 🇧🇬 | Slovak | sk | 🇸🇰 | Croatian | hr | 🇭🇷 |
| Serbian | sr | 🇷🇸 | Turkish | tr | 🇹🇷 |
📊 Language Coverage Disclaimer: Quality varies significantly by language. Spanish, French, English, and German have the strongest representation in our training data (~200,000 hours from YODAS2). Other languages may have reduced quality, prosody, or vocabulary coverage depending on their availability in the training dataset.
| Property | Value |
|---|---|
| Parameters | 7B |
| Architecture | AR + Diffusion (Qwen2.5-7B backbone) |
| Base Model | Microsoft VibeVoice |
| Audio Sample Rate | 24kHz |
| Audio Format | Mono, float32 |
| VRAM Required | ~19GB |
| Training Hardware | 8x NVIDIA H100 |
| Training Duration | 5 days |
| Training Data | ~200,000 hours from YODAS2 |
# Install with pip
pip install kugelaudio-open
# Or with uv (recommended)
uv pip install kugelaudio-open
from kugelaudio_open import (
KugelAudioForConditionalGenerationInference,
KugelAudioProcessor,
)
import torch
# Load model
device = "cuda" if torch.cuda.is_available() else "cpu"
model = KugelAudioForConditionalGenerationIFrom the published model card. Full card on the HuggingFace links in the sidebar.
Benchmarks
As published on the model card — the maker's own numbers, not measured by AxForge.
| Task | Dataset | Metric | Score |
|---|---|---|---|
| text-to-speech | YODAS2 | Human Preference vs ElevenLabs | 78 |
Using it via the API
Once AxForge deploys kugelaudio-0-open for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (kugelaudio-0-open below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/audio/transcriptions \ -H "Authorization: Bearer $AXFORGE_API_KEY" \ -F model="kugelaudio-0-open" -F file=@audio.mp3
Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.