Models / Deepgram

Deepgram

Deploy the latest Deepgram speech-to-text on Together AI. Accurate, real-time transcription co-located with your LLM and TTS for end-to-end voice latency under 500ms.

Why Deepgram on Together AI?

Designed for production workloads that need 
consistent performance and operational control.

Production-grade real-time transcription

Deepgram provides accurate, cost-effective speech-to-text, in real time or batch, cloud or self-hosted. It is the listening layer for voice agents, contact centers, and transcription pipelines.

One co-located voice stack

With native Deepgram integration, transcription runs on the same platform as your model and speech output. You manage one API, one vendor, and one bill instead of stitching separate STT, LLM, and TTS providers together.

Enterprise-ready from day one

SOC 2 Type II certified, HIPAA compliant, and deployed on US-based infrastructure. Full model ownership with no data retention by default.

Meet the Deepgram family

Explore top-performing models across text, image, video, code, and voice.

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New

Transcribe

Deepgram Flux

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Audio

Deepgram Aura-2

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Transcribe

Deepgram Nova-3

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Transcribe

Deepgram Nova-3 Multilingual

Deployment options

Run models using different deployment options depending on latency needs, traffic patterns, and infrastructure control.

  • Serverless Inference

  • Provisioned 
Throughput

  • Dedicated Model 
Inference

  • Dedicated Container 
Inference

Serverless Inference

A fully managed real-time or batch inference API with access to dozens of the most popular AI models.

Best for

Variable or unpredictable traffic

Rapid prototyping and iteration

Cost-sensitive or early-stage production workloads

Provisioned 
Throughput

Reserved token capacity with SLA guarantees. Priced in PTUs, a normalized throughput unit. 

Best for

Production workloads

Reliability guarantees

Predictable pricing

Dedicated Model 
Inference

An inference endpoint backed by reserved, isolated compute resources and Together AI inference research.

Best for

Predictable or steady traffic

Latency-sensitive applications

High-throughput production workloads

Dedicated Container 
Inference

Run inference with your own engine and model on fully-managed, scalable infrastructure.

Best for

Generative media models

Non-standard runtimes

Custom inference pipelines