Deepgram vs Lambda Pricing (2026)
How do these two stack up on price? Here's what each one costs, what you get, and where the value sits.
Pay As You Go
- No minimums. No expiration.
- No credit card required.
- Free $200 Credit
- All endpoint in public models
- Up to 50 for the REST API (Speech-to-Text)
- Up to 150 for the WSS API (Speech-to-Text)
- Up to 5 for Deepgram Whisper Cloud
- Up to 45 for the REST API + WSS API (Text-to-Speech)
- Up to 45 for the WSS API (Voice Agent API)
- Up to 10 for the REST API (Audio Intelligence)
- Community & Discord
- Standard Uptime
Growth
- With pre-paid credits for the year.
- Credits are redeemed against actual usage.
- Free $200 Credit
- All endpoints in public models
- Up to 50 for the REST API (Speech-to-Text)
- Up to 225 for the WSS API (Speech-to-Text)
- Up to 5 for Deepgram Whisper Cloud
- Up to 60 for the REST API + WSS API (Text-to-Speech)
- Up to 60 for the WSS API (Voice Agent API)
- Up to 10 for the REST API (Audio Intelligence)
- Community & Discord
- Standard Uptime
Enterprise
- For businesses with large volumes, data or deployment requirements, or support needs.
NVIDIA B200 SXM6 (8x)
- VRAM/GPU: 180 GB
- vCPUs: 208
- RAM: 2900 GiB
- Storage: 22 TiB SSD
NVIDIA H100 SXM (8x)
- VRAM/GPU: 80 GB
- vCPUs: 208
- RAM: 1800 GiB
- Storage: 22 TiB SSD
NVIDIA A100 SXM 80GB (8x)
- VRAM/GPU: 80 GB
- vCPUs: 240
- RAM: 1800 GiB
- Storage: 19.5 TiB SSD
NVIDIA A100 SXM 40GB (8x)
- VRAM/GPU: 40 GB
- vCPUs: 124
- RAM: 1800 GiB
- Storage: 5.8 TiB SSD
NVIDIA Tesla V100 (8x)
- VRAM/GPU: 16 GB
- vCPUs: 88
- RAM: 448 GiB
- Storage: 5.8 TiB SSD
NVIDIA B200 SXM6 (4x)
- VRAM/GPU: 180 GB
- vCPUs: 104
- RAM: 1440 GiB
- Storage: 11 TiB SSD
NVIDIA H100 SXM (4x)
- VRAM/GPU: 80 GB
- vCPUs: 104
- RAM: 900 GiB
- Storage: 11 TiB SSD
NVIDIA A100 PCIe (4x)
- VRAM/GPU: 40 GB
- vCPUs: 120
- RAM: 900 GiB
- Storage: 1 TiB SSD
NVIDIA A6000 (4x)
- VRAM/GPU: 48 GB
- vCPUs: 56
- RAM: 400 GiB
- Storage: 1 TiB SSD
NVIDIA B200 SXM6 (2x)
- VRAM/GPU: 180 GB
- vCPUs: 52
- RAM: 720 GiB
- Storage: 5.5 TiB SSD
NVIDIA H100 SXM (2x)
- VRAM/GPU: 80 GB
- vCPUs: 52
- RAM: 450 GiB
- Storage: 5.5 TiB SSD
NVIDIA A100 PCIe (2x)
- VRAM/GPU: 40 GB
- vCPUs: 60
- RAM: 450 GiB
- Storage: 1 TiB SSD
NVIDIA A6000 (2x)
- VRAM/GPU: 48 GB
- vCPUs: 28
- RAM: 200 GiB
- Storage: 1 TiB SSD
NVIDIA B200 SXM6 (1x)
- VRAM/GPU: 180 GB
- vCPUs: 26
- RAM: 360 GiB
- Storage: 2.75 TiB SSD
NVIDIA GH200 (1x)
- VRAM/GPU: 96 GB
- vCPUs: 64
- RAM: 432 GiB
- Storage: 4 TiB SSD
NVIDIA H100 SXM (1x)
- VRAM/GPU: 80 GB
- vCPUs: 26
- RAM: 225 GiB
- Storage: 2.75 TiB SSD
NVIDIA H100 PCIe (1x)
- VRAM/GPU: 80 GB
- vCPUs: 26
- RAM: 225 GiB
- Storage: 1 TiB SSD
NVIDIA A100 SXM (1x)
- VRAM/GPU: 40 GB
- vCPUs: 30
- RAM: 220 GiB
- Storage: 512 GiB SSD
NVIDIA A100 PCIe (1x)
- VRAM/GPU: 40 GB
- vCPUs: 30
- RAM: 225 GiB
- Storage: 512 GiB SSD
NVIDIA A10 (1x)
- VRAM/GPU: 24 GB
- vCPUs: 30
- RAM: 226 GiB
- Storage: 1.3 TiB SSD
NVIDIA A6000 (1x)
- VRAM/GPU: 48 GB
- vCPUs: 14
- RAM: 100 GiB
- Storage: 512 GiB SSD
NVIDIA Quadro RTX 6000 (1x)
- VRAM/GPU: 24 GB
- vCPUs: 14
- RAM: 46 GiB
- Storage: 512 GiB SSD
Deepgram vs Lambda FAQ
- Which one is cheaper?
- One or both use custom pricing, so it depends on your specific needs.
- Can I use either one for free?
- Deepgram has a free plan. Lambda doesn't — you'll need to pay from day one.
- How do they charge?
- Both use a usage-based model, so the comparison is straightforward — it comes down to features and limits at each price point.
- Which one is a better deal?
- Depends on what you need. Deepgram: Deepgram positions as the developer-friendly, cost-efficient alternative to Google and AWS in the speech AI space — not the cheapest, but meaningfully cheaper than hyperscaler STT at scale. The no-credit-card free tier is a direct shot at winning developers before they default to an incumbent. Lambda: Lambda positions as a serious alternative to hyperscalers (AWS, GCP, Azure) for ML teams who want raw GPU access without cloud markup or complexity. They're not the cheapest bare-metal option, but the no-egress-fees policy and 1-Click Clusters are a direct shot at teams burned by AWS networking costs.
Still deciding? See the best Deepgram alternatives or the best Lambda alternatives, ranked with verified pricing.
Keep tabs on both.
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