Voxtral-Mini-4B-Realtime-2602-ONNX

Voxtral Mini 4B Realtime 2602#

Voxtral Mini 4B Realtime 2602 is a multilingual, realtime speech-transcription model and among the first open-source solutions to achieve accuracy comparable to offline systems with a delay of <500ms. It supports 13 languages and outperforms existing open-source baselines across a range of tasks, making it ideal for applications like voice assistants and live subtitling.

Built with a natively streaming architecture and a custom causal audio encoder - it allows configurable transcription delays (240ms to 2.4s), enabling users to balance latency and accuracy based on their needs. At a 480ms delay, it matches the performance of leading offline open-source transcription models, as well as realtime APIs.

As a 4B-parameter model, is optimized for on-device deployment, requiring minimal hardware resources. It runs in realtime with on devices minimal hardware with throughput exceeding 12.5 tokens/second.

This model is released in BF16 under the Apache-2 license, ensuring flexibility for both research and commercial use.

For more details, see our:

• Blog post
• Demo
• Technical report
• vLLM's blog on streaming input

Key Features#

Voxtral Mini 4B Realtime consists of two main architectural components:

• ≈3.4B Language Model
• ≈970M Audio Encoder
• The audio encoder was trained from scratch with causal attention enabling streaming capability
• Both the audio encoder as well as the LLM backbone use sliding window attention allowing for "infinite" streaming
• For more details, refer to the technical report

Image: Voxtral-Realtime Architecture

The Voxtral Mini 4B Realtime model offers the following capabilities:

• High-Quality Transcription: Transcribe audio to text with confidence.
• Multilingual: Supports dozens of languages, making it perfect for multilingual transcription tasks.
• Real-Time: Fast streaming ASR model, enabling real-time transcription use cases.
• Configurable Transcription Delays: Customize the transcription delay to balance quality and latency, from 80ms to 2.4s.

Use Cases#

Real-Time Transcription Purposes:

• Private meeting transcriptions
• Live subtitle creation
• Real-time assistants with speech understanding
• And more

Bringing real-time transcription capabilities to all.

Recommended Settings#

We recommend deploying with the following best practices:

• Always set the temperature to 0.0
• A single text-token is worth 80ms. Hence, make sure to set your --max-model-len accordingly. To live-record a 1h meeting, you need to set --max-model-len >= 3600 / 0.8 = 45000. In theory, you should be able to record with no limit; in practice, pre-allocations of RoPE parameters among other things limits --max-model-len. For the best user experience, we recommend to simply instantiate vLLM with the default parameters which will automatically set a maximum model length of 131072 (~ca. 3h).
• We strongly recommend using websockets to set up audio streaming sessions. For more info on how to do so, check Usage.
• We recommend using a delay of 480ms as we found it to be the sweet spot of performance and low latency. If, however, you want to adapt the delay, you can change the "transcription_delay_ms": 480 parameter in the tekken.json file to any multiple of 80ms between 80 and 1200, as well as 2400 as a standalone value.

Benchmark Results#

We compare Voxtral Mini 4B Realtime to similar models - both offline models and realtime. Voxtral Mini 4B Realtime is competitive to leading offline models and shows significant gains over existing open-source realtime solutions.

Fleurs#

Long-form English#

Short-form English#

License#

This model is licensed under the Apache 2.0 License.

You must not use this model in a manner that infringes, misappropriates, or otherwise violates any third party’s rights, including intellectual property rights.