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ultravox-v0_4_1-llama-3_1-8b

A speech-language model from Fixie AI that pairs Llama 3.1 8B with a Whisper encoder, enabling direct audio understanding and speech-to-text reasoning.

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about

Fixie AI's Ultravox replaces the traditional ASR-then-LLM pipeline by fusing a frozen Whisper large-v3-turbo encoder with Llama 3.1 8B through a trained multi-modal adapter. Audio embeddings are injected directly into the LLM's input space via a special <|audio|> pseudo-token, achieving roughly 150ms time-to-first-token on A100 hardware without requiring a separate transcription step.

LicenseMIT
Context window(in thousands)8000

Use cases for ultravox-v0_4_1-llama-3_1-8b

  1. Low-latency voice agents: By fusing audio directly into the LLM embedding space, Ultravox eliminates the separate ASR step and achieves roughly 150ms time-to-first-token for spoken input.
  2. Spoken language understanding: The Whisper encoder processes audio semantics rather than just transcription, enabling the model to interpret tone, emphasis, and intent alongside words.
  3. Audio-grounded retrieval: The special audio token mechanism allows it to answer questions about spoken content without generating an intermediate transcript.

Quality

Arena EloN/A
MMLUN/A
MT BenchN/A

Ultravox v0.4 is a speech-language model, so standard text benchmarks like MMLU do not apply directly. Its Llama 3.1 8B backbone scores 69.4% on MMLU (5-shot), but the model's value is in audio processing: it achieves roughly 150ms time-to-first-token on spoken input by fusing Whisper and Llama without a separate ASR step, unlike traditional cascaded pipelines.

Claude-Opus-4-6

1501

GLM-5

1456

gpt-5.1

1455

Kimi-K2.5

1454

gpt-5.2

1440

pricing

The cost of running Ultravox v0.4 with Telnyx Inference is $0.0002 per 1,000 tokens for the text component. The Whisper encoder processes audio at $0.003 per minute. A voice agent handling 100,000 one-minute calls would cost approximately $300 for audio processing plus $200 for text generation.

What's Twitter saying?

  • Developers praise Ultravox's low latency and human-like conversations, with benchmarks showing it matches Whisper Large v3 + Llama 3.1 8B and outperforms GPT-4o Realtime in speech understanding and accuracy.
  • Tech reviewers highlight superior voice quality and vast options (over 1,000 models), calling it the best platform with amazing support and community.
  • Commentators note limited LLM customization and control as a downside, though its end-to-end audio understanding excels in real-time interaction.

Explore Our LLM Library

Discover the power and diversity of large language models available with Telnyx. Explore the options below to find the perfect model for your project.

Organizationdeepseek-ai
Model NameDeepSeek-R1-Distill-Qwen-14B
Taskstext generation
Languages SupportedEnglish
Context Length43,000
Parameters14.8B
Model Tiermedium
Licensedeepseek

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faqs

What is Ultravox?

Ultravox is a speech-language model from Fixie AI that directly understands spoken audio without requiring a separate speech-to-text step. It pairs a Llama 3.1 8B backbone with a Whisper encoder to process audio input and generate text responses in a single model.

How does Ultravox work?

Ultravox uses a frozen Whisper large v3 turbo encoder to process audio and a multi-modal adapter to translate audio features into the Llama 3.1 8B language model's embedding space. Only the adapter is trained while both Whisper and Llama remain frozen, making training efficient.

What is Ultravox good for?

Ultravox is designed for real-time voice agent applications, speech-to-speech translation, and spoken audio analysis. Its time-to-first-token of approximately 150ms makes it suitable for low-latency voice interactions where traditional STT-then-LLM pipelines would be too slow.

How fast is Ultravox?

Ultravox v0.4.1 achieves a time-to-first-token of approximately 150ms and generates 50-100 tokens per second on an A100 40GB GPU. This speed makes it practical for real-time conversational applications that require immediate audio understanding.