Deepgram vs Replicate: Token Pricing, Speed & Intelligence
Full comparison of Deepgram and Replicate — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.
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.
Replicate
Run any open-source AI model via API — FLUX 1.1 Pro, Llama 4, video, audio, and custom models
Replicate is a platform for running open-source AI models via a simple API. It hosts thousands of community models including FLUX 1.1 Pro, Llama 4, Stable Diffusion, Whisper, and video generation models. Pay per prediction with no infrastructure to manage. The 2026 catalog has expanded significantly with FLUX 1.1 Pro Ultra, Kling v2.1, and Llama 4 Scout/Maverick. Custom model deployment via Cog remains a core differentiator.
Key metric comparison
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Live token pricing
Strengths and weaknesses
Deepgram
Replicate
Key differentiators
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.
A broad catalog of community AI models — if a model exists on Hugging Face, it's likely on Replicate. Strong coverage for image, video, and audio model access, plus custom model deployment via Cog.
Frequently asked questions
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.
Replicate FAQs
What new models did Replicate add in 2026?
Replicate added FLUX 1.1 Pro Ultra, Kling v2.1 (video generation), Llama 4 Scout and Maverick, and many other models in 2026. The catalog is continuously updated as new community models are released.
How does Replicate pricing work?
Replicate charges per prediction based on compute time used. Pricing varies by model and GPU type. Text models are billed per token; image models per image; video models per second of output. Some models are free with rate limits.
Can I deploy my own model on Replicate?
Yes. Replicate lets you package and deploy custom models using Cog, their open-source model packaging tool. Once deployed, your model gets a public API endpoint with automatic scaling.
Provider resources
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.
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.
Replicate — Run any open-source AI model via API — FLUX 1.1 Pro, Llama 4, video, audio, and custom models
Replicate is a platform for running open-source AI models via a simple API. It hosts thousands of community models including FLUX 1.1 Pro, Llama 4, Stable Diffusion, Whisper, and video generation models. Pay per prediction with no infrastructure to manage. The 2026 catalog has expanded significantly with FLUX 1.1 Pro Ultra, Kling v2.1, and Llama 4 Scout/Maverick. Custom model deployment via Cog remains a core differentiator.
A broad catalog of community AI models — if a model exists on Hugging Face, it's likely on Replicate. Strong coverage for image, video, and audio model access, plus custom model deployment via Cog.
Key strengths compared
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
Replicate
- Broad catalog of community AI models — text, image, video, audio
- FLUX 1.1 Pro Ultra and Kling v2.1 in the 2026 catalog
- Llama 4 Scout and Maverick available
- Higher per-token cost than dedicated text inference APIs
- Cold start latency on less popular models
Key weaknesses compared
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
Replicate
- Higher per-token cost than dedicated text inference APIs
- Cold start latency on less popular models
- Less suitable for high-throughput text inference
Provider category context
Deepgram is a frontier lab, founded in 2015. Replicate is a inference api, founded in 2021. Deepgram as a frontier lab trains and serves its own proprietary models. Replicate as an inference API provider hosts open-weight models — typically offering lower prices for equivalent capability tiers but without access to proprietary frontier models.
How to choose between them
Choose Deepgram if you need Real-time transcription. Choose Replicate if you need broad catalog of community ai models — text, image, video, audio. 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.