Lambda vs AssemblyAI Pricing (2026)
How do these two stack up on price? Here's what each one costs, what you get, and where the value sits.
| Lambda | AssemblyAI | |
|---|---|---|
| Starts at | Custom | Custom |
| Number of plans | 22 | 2 |
| Free plan | — | |
| Free trial | — | |
| Pricing model | usage-based | usage-based |
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
Pay as you go
- Universal-3.5 Pro ($0.21/hr)
- Universal-2 ($0.15/hr)
- Universal-3.5 Pro Realtime ($0.45/hr)
- Universal-Streaming ($0.15/hr)
- Universal-Streaming Multilingual ($0.15/hr)
- Sync API ($0.45/hr)
- Voice Agent API ($4.50/hr)
- Speaker Diarization ($0.02/hr pre-recorded, $0.12/hr realtime)
- Medical Mode ($0.15/hr)
- Keyterms Prompting
- Prompting ($0.05/hr)
- Speaker Identification ($0.02/hr)
- Translation ($0.06/hr)
- Custom Formatting ($0.03/hr)
- Entity Detection ($0.08/hr)
- Sentiment Analysis ($0.02/hr)
- Auto Chapters ($0.08/hr)
- Key Phrases ($0.01/hr)
- Topic Detection ($0.15/hr)
- Summarization ($0.03/hr)
- Profanity Filtering ($0.01/hr)
- PII Audio Redaction ($0.05/hr)
- PII Text Redaction ($0.08/hr)
- Content Moderation ($0.15/hr)
- LLM Gateway
- No minimum commitments
- No credit card required to start
Custom
- Custom rate limits
- Enhanced concurrency
- Enterprise-grade flexibility
- Volume-based pricing
- Custom starting concurrency limits
Lambda vs AssemblyAI 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?
- AssemblyAI 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. 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. AssemblyAI: They're positioning as the developer-friendly, API-first alternative to Deepgram and Rev AI — competitive on price at scale but differentiated by the breadth of AI features (LLM Gateway, multichannel, etc.). The AWS Marketplace listing signals they're actively chasing enterprise procurement budgets.
Keep tabs on both.
We'll monitor pricing changes for Lambda and AssemblyAI and let you know when something moves.