Braintrust 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.
| Braintrust | Lambda | |
|---|---|---|
| Starts at | $249/mo | Custom |
| Number of plans | 3 | 22 |
| Free plan | — | |
| Free trial | — | — |
| Pricing model | hybrid | usage-based |
Starter
- $10 credits
- 1 GB processed data
- 10k scores
- 14-day retention
- Unlimited users, projects, datasets, playgrounds, and experiments
Pro
Popular- $249 credits
- 5 GB processed data
- 50k scores
- 30-day retention
- Custom charts, environments, priority support, RBAC, and more
Enterprise
- Custom data retention and export, RBAC, and premium support with on-prem or hosted deployment for high volume or privacy-sensitive data.
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
Braintrust 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?
- Braintrust has a free plan. Lambda doesn't — you'll need to pay from day one.
- How do they charge?
- Different approach here. Braintrust uses hybrid pricing, while Lambda goes with usage-based. That changes the math depending on your team size and usage.
- Which one is a better deal?
- Depends on what you need. Braintrust: At $249/mo flat for Pro, Braintrust sits mid-to-premium compared to open-source or DIY logging stacks, but it undercuts the fully custom enterprise observability players by keeping a transparent starting price public. They're clearly courting AI-native teams who've outgrown free tools but aren't ready for an enterprise sales cycle yet. 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.
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