Lambda vs Vast.ai
A detailed comparison to help you choose between Lambda and Vast.ai.
Quick Verdict
3.7/5
Lambda
0 reviews
3.7/5
Vast.ai
0 reviews
Both Lambda and Vast.ai are equally rated at 3.7/5. 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. P2P GPU marketplace connecting researchers and developers with spare compute capacity. Offers rented GPUs at lower rates than centralized cloud providers, ideal for ML training, rendering, and batch processing.
Lambda On-demand GPU cloud for ML training and inference | Vast.ai Rent GPUs from individuals for 2-10x cheaper compute | |
|---|---|---|
| Overview | ||
| Rating | 3.7 (0 reviews) | 3.7 (0 reviews) |
| Pricing model | usage-based | usage-based |
| Starting price | From $0.69/mo | From $0.03/mo✓ |
| 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. | ML researchers, rendering studios, and budget-conscious teams running checkpointable training, fine-tune, and batch workloads who are willing to vet hosts themselves |
| 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] | Global — distributed hosts |
| Tags | ||
| Tags | hourly billinggpu availableus datacenterapi access | hourly billinggpu availableeu datacenterus datacenterapac datacenter |
| Visit Lambda → | Visit Vast.ai → | |
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
Vast.ai
Pros
- + Cheapest public GPU-hour rates anywhere; per-second billing with no minimum charge
- + Always-on capacity across 81 GPU types and hosts in 52 countries — no 'capacity coming soon'
- + Interruptible bidding and reserved discounts give real pricing levers per workload
- + Dense, useful search filters: reliability score, DLPerf, network speed, host tier
- + SOC 2 Type II and HIPAA attestations at the platform level, per third-party comparisons
Cons
- - No SLA, no owned datacenters, and no recourse when an independent host disappears
- - Host variance is real: measured ±11.7% throughput spread on identical H100 SXM specs
- - Storage bills continue on stopped instances; bandwidth is host-set and can be expensive
- - Interruptible preemption risk demands checkpointing discipline
- - Verification and reliability-score formulas are only partially disclosed
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