Baseten vs Deepgram: Token Pricing, Speed & Intelligence
Full comparison of Baseten and Deepgram — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.
Baseten
Production ML infrastructure — deploy any model with custom serving, autoscaling, and GPU selection
Baseten is a production ML infrastructure platform for deploying custom and open-weight models with full control over serving configuration, GPU selection, autoscaling, and cold-start behavior. Unlike managed inference APIs, Baseten lets you bring your own model weights, custom preprocessing, and serving logic. It supports Truss (Baseten's open-source model packaging format), vLLM, TensorRT-LLM, and custom Python serving code. Ideal for teams that need more control than a managed API but less overhead than raw Kubernetes.
Deepgram
Nova-3 speech-to-text API — real-time and batch transcription at low latency
Deepgram is a speech-to-text API provider specialising in low-latency audio transcription. Its Nova-3 model delivers real-time streaming transcription with high accuracy across accents and domains. Nova-3 Medical is tuned for clinical vocabulary. Deepgram also hosts Whisper Large for teams that need an open-weights baseline. Pricing is per audio hour rather than per token.
Key metric comparison
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Live token pricing
Strengths and weaknesses
Baseten
Deepgram
Key differentiators
The production ML platform that gives you managed-API convenience with custom-serving flexibility — deploy any model with your own preprocessing logic, GPU selection, and autoscaling without managing Kubernetes.
Purpose-built speech-to-text API with Nova-3 at ~300 ms latency and a medical-domain variant — priced per audio hour rather than per token.
Frequently asked questions
Baseten FAQs
What is Baseten?
Baseten is a production ML infrastructure platform for deploying AI models with custom serving logic, GPU selection, and autoscaling. It supports any open-weight model or custom fine-tune via the Truss packaging format.
How does Baseten differ from Together AI or Replicate?
Baseten gives you full control over the serving stack — custom preprocessing, postprocessing, GPU selection, and autoscaling behavior. Together AI and Replicate are managed APIs with fixed serving; Baseten is for teams that need custom model serving logic.
What GPUs does Baseten support?
Baseten supports H100 SXM, H100 PCIe, A100 80GB, A10G, and T4 GPUs with per-second billing. You select the GPU type per deployment based on your model's memory and throughput requirements.
Deepgram FAQs
How is Deepgram priced?
Deepgram charges per audio hour rather than per token. Nova-3 is $0.218/hour, Nova-3 Medical is $0.435/hour, and Whisper Large is $0.218/hour. See deepgram.com/pricing for current rates.
What is Deepgram Nova-3?
Nova-3 is Deepgram's latest speech recognition model, offering high accuracy with approximately 300 ms P50 latency for real-time streaming. It supports 30+ languages and is optimised for conversational and call-centre audio.
Does Deepgram support real-time transcription?
Yes. Deepgram's streaming API delivers transcription results with ~300 ms latency, making it suitable for live captions, voice agents, and real-time call analytics.
Provider resources
Key strengths compared
Baseten
- Full control over model serving: custom preprocessing, postprocessing, and business logic
- Bring your own weights — deploy any HuggingFace model or custom fine-tune
- GPU selection: H100, A100, A10G, T4 with per-second billing
- More setup required than managed APIs — not a drop-in OpenAI replacement
- Cold starts on scale-to-zero deployments (configurable warm pool available)
Deepgram
- Nova-3 delivers industry-leading accuracy with ~300 ms P50 latency for real-time streaming
- Nova-3 Medical tuned for clinical and healthcare vocabulary
- Per-audio-hour pricing is predictable for high-volume transcription workloads
- Speech-to-text only — no LLM chat, image, or embedding models
- No per-token pricing; cost structure differs from general-purpose LLM APIs
Key weaknesses compared
Baseten
- More setup required than managed APIs — not a drop-in OpenAI replacement
- Cold starts on scale-to-zero deployments (configurable warm pool available)
- Pricing is higher than shared inference APIs for low-volume workloads
Deepgram
- Speech-to-text only — no LLM chat, image, or embedding models
- No per-token pricing; cost structure differs from general-purpose LLM APIs
- Smaller ecosystem than general-purpose providers
Provider category context
Baseten is a inference api, founded in 2019. Deepgram is a frontier lab, founded in 2015. Baseten as an inference API provider hosts open-weight models — typically offering lower prices for equivalent capability tiers. Deepgram as a frontier lab trains and serves proprietary models with capabilities not available elsewhere.
How to choose between them
Choose Baseten if you need full control over model serving: custom preprocessing, postprocessing, and business logic. Choose Deepgram if you need Real-time transcription. For high-volume production workloads, run a cost comparison using the token pricing table above with your actual prompt/completion token ratio — the cheapest provider depends heavily on your input-to-output token ratio.