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Deepgram vs Stability AI: Token Pricing, Speed & Intelligence

Full comparison of Deepgram and Stability AI — 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.

TranscriptionReal-time captionsVoice agentsMedical documentationCall analytics
Proprietary models

Stability AI

Stable Diffusion 3.5 Large and Stable Image Ultra — open-weight image generation

Stability AI is the creator of Stable Diffusion, the most widely deployed open-weight image generation model family. The 2026 API offers Stable Diffusion 3.5 Large (highest quality), SD 3.5 Medium (balanced), and Stable Image Ultra for photorealistic output. All SD 3.5 models are open-weight and available for self-hosting. Stability AI also offers Stable Video Diffusion for short video generation.

Image generationImage editingInpaintingVideo generationSelf-hosted AI artFine-tuning
Proprietary modelsHosts open weights

Key metric comparison

Cheapest input ($/1M)

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Cheapest output ($/1M)

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Peak throughput

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Best latency (TTFT)

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Intelligence score

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Context window

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Live token pricing

Strengths and weaknesses

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
Supports 30+ languages and automatic language detection
Whisper Large available for open-weights baseline comparisons
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

Stability AI

Open-weight SD 3.5 models — self-host on any GPU cloud
Largest community ecosystem of fine-tuned variants and LoRAs
Stable Image Ultra for photorealistic output
Stable Video Diffusion for short video generation
Competitive API pricing vs DALL-E 3
Inpainting and outpainting support
Image quality trails FLUX 1.1 Pro and Midjourney on photorealism benchmarks
Company has faced financial challenges and leadership changes
SD 3.5 adoption slower than FLUX in the community

Key differentiators

Deepgram

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.

Stability AI

Stable Diffusion 3.5 models are open-weight and self-hostable — enabling the largest fine-tuning and LoRA ecosystem of any image generation model family, with full control over the generation pipeline.

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.

Stability AI FAQs

What is Stable Diffusion 3.5?

Stable Diffusion 3.5 is Stability AI's latest generation of open-weight text-to-image models. SD 3.5 Large offers the highest quality; SD 3.5 Medium is a balanced option for production use. Both are available for self-hosting.

How does Stability AI compare to FLUX?

FLUX 1.1 Pro generally outperforms SD 3.5 on photorealism and prompt adherence benchmarks. However, SD 3.5 has a much larger community ecosystem of fine-tuned variants and LoRAs, making it more flexible for specialised use cases.

Can I self-host Stable Diffusion 3.5?

Yes. SD 3.5 Large and Medium weights are publicly available under the Stability AI Community License. You can run them on any GPU with sufficient VRAM — SD 3.5 Medium requires ~8GB VRAM; SD 3.5 Large requires ~24GB.

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.

Stability AI — Stable Diffusion 3.5 Large and Stable Image Ultra — open-weight image generation

Stability AI is the creator of Stable Diffusion, the most widely deployed open-weight image generation model family. The 2026 API offers Stable Diffusion 3.5 Large (highest quality), SD 3.5 Medium (balanced), and Stable Image Ultra for photorealistic output. All SD 3.5 models are open-weight and available for self-hosting. Stability AI also offers Stable Video Diffusion for short video generation.

Stable Diffusion 3.5 models are open-weight and self-hostable — enabling the largest fine-tuning and LoRA ecosystem of any image generation model family, with full control over the generation pipeline.

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

Stability AI

  • Open-weight SD 3.5 models — self-host on any GPU cloud
  • Largest community ecosystem of fine-tuned variants and LoRAs
  • Stable Image Ultra for photorealistic output
  • Image quality trails FLUX 1.1 Pro and Midjourney on photorealism benchmarks
  • Company has faced financial challenges and leadership changes

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

Stability AI

  • Image quality trails FLUX 1.1 Pro and Midjourney on photorealism benchmarks
  • Company has faced financial challenges and leadership changes
  • SD 3.5 adoption slower than FLUX in the community

Provider category context

Deepgram is a frontier lab, founded in 2015. Stability AI is a frontier lab, founded in 2020. Both are frontier lab providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.

How to choose between them

Both Deepgram and Stability AI are frontier labs with proprietary models. Choose based on benchmark performance for your specific task: Deepgram leads on nova-3 delivers industry-leading accuracy with ~300 ms p50 latency for real-time streaming, while Stability AI leads on open-weight sd 3.5 models — self-host on any gpu cloud. For cost-sensitive workloads, compare the cheapest model tier from each provider in the pricing table above — the gap between efficient-tier models is often larger than between flagship models.