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Open-weights 27B speech-to-text model from ServiceNow that adds a speech interface to a Gemma 4 backbone, with tool calling.

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Apriel Voice 27B at a glance

What is Apriel Voice 27B?
Apriel Voice 27B is a model from ServiceNow. Open-weights 27B speech-to-text model from ServiceNow that adds a speech interface to a Gemma 4 backbone, with tool calling.
Who makes Apriel Voice 27B?
Apriel Voice 27B is made by ServiceNow.
Does Apriel Voice 27B work in the EU?
Available in the EU. Weights are downloadable from Hugging Face under the MIT license, with no EU exclusion in the license or model card. The card also lists support for many EU languages. Last verified 14 Nov 2026.
How much does Apriel Voice 27B cost?
Open source. Weights free to download under MIT license; a hosted demo (Apriel Live) is available on Hugging Face Spaces. Licence: MIT.
Where was Apriel Voice 27B shown?
In 1 creator video by Matthew Berman. Most recently by Matthew Berman on 5 Nov 2026, at 14:19 in “Kimi K3.1 weights OUT, open source computer use, SOTA image model, science model, Pika H3: AI NEWS”.

Sources: the vendor's own pages (linked above) and creator videos at the linked timestamps. EU status is information, not legal advice; see how we check.

About

Apriel Voice 27B Preview is an open-weights model from ServiceNow that understands spoken requests and generates text responses and tool calls. It connects a Whisper large-v3-turbo speech encoder to a Gemma 4 26B-A4B backbone through a learned projector, and keeps the backbone's text and image input capabilities. The model card lists support for transcription, speech translation, spoken question answering, instruction following, multi-step reasoning and function calling.

The checkpoint outputs text and tool calls, not native speech. Voice assistants need an external speech synthesizer and application-managed turn-taking, and the application executes tools and returns results. Longer 16 kHz mono recordings are split into 30-second chunks. The authors report good performance up to about 30 minutes of audio, and recommend thinking mode for longer inputs.

The card reports 51.27% EVA-A, 74.13% EVA-X and 65.51% τ-Voice pass@1 with 1.91 s mean latency, plus LibriSpeech WER of 2.23% (test-clean) and 5.15% (test-other). These figures are the vendor's own, and it is labelled a preview. The weights are on Hugging Face under the MIT license and load via transformers with custom code. The card tags dozens of languages, including most EU languages.

Key features
  • Speech understanding: transcription, translation and spoken question answering
  • Function calling and multi-step reasoning over spoken requests
  • Text and image input alongside audio
  • Whisper large-v3-turbo encoder with Gemma 4 26B-A4B backbone
  • Long-audio handling with 30-second chunking, tested to about 30 minutes
  • Multilingual, with many languages listed including most EU languages
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