Deepgram vs SambaNova Cloud: Token Pricing, Speed & Intelligence
Full comparison of Deepgram and SambaNova Cloud — 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.
SambaNova Cloud
High-throughput inference on SambaNova RDU chips — gpt-oss-120b, GLM-5.3, Llama
SambaNova Cloud runs inference on SambaNova's proprietary Reconfigurable Dataflow Unit (RDU) chips, delivering very high throughput (800+ tokens/sec on gpt-oss-120b). The catalog covers gpt-oss-120b, GLM-5.3, MiniMax-M3, DeepSeek-V3.2, Meta-Llama-3.3-70B, and Gemma 4 31B. Pricing is PAYG with prompt caching on select models.
Key metric comparison
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Live token pricing
Strengths and weaknesses
Deepgram
SambaNova Cloud
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.
Proprietary RDU chips deliver industry-leading throughput on open-weight models at competitive per-token rates.
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.
SambaNova Cloud FAQs
What makes SambaNova Cloud different?
SambaNova runs inference on its own Reconfigurable Dataflow Unit (RDU) chips rather than NVIDIA GPUs. This delivers very high throughput — over 800 tokens/sec on gpt-oss-120b — at competitive per-token rates.
What models does SambaNova Cloud offer?
As of October 2026: gpt-oss-120b ($0.22/$0.59), GLM-5.3 ($1.40/$4.40, cached $0.14), MiniMax-M3 ($0.60/$2.40, cached $0.06), DeepSeek-V3.2 ($3.00/$4.50), Meta-Llama-3.3-70B ($0.60/$1.20), and Gemma 4 31B ($0.38/$1.15). See cloud.sambanova.ai/plans/pricing for current rates.
Does SambaNova offer prompt caching?
Yes, on GLM-5.3 (cached input $0.14/1M vs $1.40/1M standard) and MiniMax-M3 (cached input $0.06/1M vs $0.60/1M standard).
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.
SambaNova Cloud — High-throughput inference on SambaNova RDU chips — gpt-oss-120b, GLM-5.3, Llama
SambaNova Cloud runs inference on SambaNova's proprietary Reconfigurable Dataflow Unit (RDU) chips, delivering very high throughput (800+ tokens/sec on gpt-oss-120b). The catalog covers gpt-oss-120b, GLM-5.3, MiniMax-M3, DeepSeek-V3.2, Meta-Llama-3.3-70B, and Gemma 4 31B. Pricing is PAYG with prompt caching on select models.
Proprietary RDU chips deliver industry-leading throughput on open-weight models at competitive per-token rates.
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
SambaNova Cloud
- Proprietary RDU chips deliver very high throughput — 800+ tokens/sec on gpt-oss-120b
- Competitive pricing on gpt-oss-120b ($0.22/$0.59 per 1M)
- Prompt caching on GLM-5.3 (cached input at $0.14/1M)
- Smaller model catalog vs OpenRouter or Together AI
- No proprietary frontier models — inference-only platform
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
SambaNova Cloud
- Smaller model catalog vs OpenRouter or Together AI
- No proprietary frontier models — inference-only platform
- RDU architecture may behave differently from GPU inference for some workloads
Provider category context
Deepgram is a frontier lab, founded in 2015. SambaNova Cloud is a inference api, founded in 2017. Deepgram as a frontier lab trains and serves its own proprietary models. SambaNova Cloud 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 SambaNova Cloud if you need High-throughput inference. 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.