Lambda vs Beam Cloud
A detailed comparison to help you choose between Lambda and Beam Cloud.
Quick Verdict
3.7/5
Lambda
0 reviews
3.6/5
Beam Cloud
0 reviews
Lambda is rated higher (3.7 vs 3.6). Lambda is a GPU cloud for training and running AI models, offering on-demand NVIDIA GPU instances and reserved clusters for AI teams and researchers. Beam Cloud provides serverless GPU and CPU compute for AI model serving and data pipelines. Scale to zero when not running. Python SDK for easy integration. Pay only for compute used.
Lambda On-demand GPU cloud for ML training and inference | Beam Cloud Serverless GPU infrastructure with per-second billing and instant scaling | |
|---|---|---|
| Overview | ||
| Rating | 3.7 (0 reviews)✓ | 3.6 (0 reviews) |
| Pricing model | usage-based | freemium |
| Starting price | From $0.69/mo | Free tier available✓ |
| Best for | ML researchers and engineering teams optimizing cost per GPU-hour for training, fine-tuning, and batch inference who can tolerate best-effort capacity. | Teams shipping AI inference, agent sandboxes, and spiky GPU workloads who want per-second pricing and the option to self-host or run on their own cloud credits. |
| Specifications (entry plan) | ||
| CPU cores | 14 vCPU | — |
| RAM | 46 GB | — |
| Storage | — | — |
| Bandwidth | — | — |
| SLA uptime | — | — |
| Data-center count | 14 | — |
| €/vCPU/mo | €0.05 | — |
| €/GB RAM/mo | €0.01 | — |
| Features | ||
| IPv6 | ✓ | |
| DDoS protection | ✓ | |
| Automated backups | ||
| Snapshots | ✓ | |
| Managed option | ||
| Bare metal | ||
| GPU available | ||
| S3-compatible | ||
| Hourly billing | ||
| Free tier | ✓ | |
| Data-center locations | ||
| Regions | [US x10 regions, Tokyo, Osaka, India, Germany, Israel] | — |
| Tags | ||
| Tags | hourly billinggpu availableus datacenterapi access | free tiergpu availableus datacenterapi access |
| Visit Lambda → | Visit Beam Cloud → | |
Lambda
Pros
- + Published per-minute GPU pricing with no egress fees
- + Preinstalled ML stack (Lambda Stack) on all images
- + Full cloud API for instance automation
- + Free egress keeps large checkpoint downloads cheap
- + Cluster tier scales from 16 to 2,000+ GPUs for distributed training
Cons
- - No published uptime SLA for on-demand instances
- - Popular H100 configurations sell out regularly
- - One European region (Germany); no Latin America or Australia
- - No managed databases, snapshots, or backup products
- - Filesystem billing continues after instance deletion
Beam Cloud
Pros
- + Aggressive GPU pricing: H100 PCIE from $1.83/hr on-demand, RTX 4090 serverless at $0.000192/sec
- + Free Developer tier with $30 compute credits every month and no mandatory production subscription
- + Open-source beta9 runtime (AGPL-3.0) with self-host and BYOC on AWS/GCP/Azure
- + Millisecond billing with scale-to-zero; sandboxes with GPU support and GPU checkpoint restore
- + Published per-second and per-hour rates with a transparent cost calculator
Cons
- - No published uptime SLA; young company with a small team behind it
- - Multiple billing units (per-second, per-hour, per-core-second, management fees) make comparison hard
- - Cold-start figures are vendor claims; uncached large images and weight downloads are slower
- - Managed fleet's regional footprint is not published; BYOC assumes you already run a cloud account
- - Container platform, not a VPS — no bare-metal root or kernel-level control on the serverless line
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