Lambda Labs
GPU cloud platform and deep learning workstations for AI/ML training and inference
H100
Latest GPUs
$1.99
Per GPU/hr (A10)
2012
Founded
Overview
Lambda Labs is a GPU cloud and hardware company built specifically for deep learning and AI workloads. Unlike general-purpose cloud providers, Lambda focuses exclusively on machine learning infrastructure, offering on-demand cloud GPUs, pre-configured workstations, and servers optimized for training and inference. Their Lambda Stack provides a one-line installation of popular ML frameworks (PyTorch, TensorFlow, CUDA) that works seamlessly across their cloud and on-premise hardware. Known for competitive pricing and simplicity, Lambda is popular among AI researchers, startups, and enterprises who need GPU compute without the complexity of hyperscaler clouds.
The Verdict
Who Should Use Lambda Labs?
Best For
- ML researchers needing quick GPU access
- Startups training models without hyperscaler complexity
- Teams wanting consistent cloud + on-prem setup
- Budget-conscious AI projects
- Those who need pre-configured ML environments
Not Ideal For
- Production inference at massive scale (consider CoreWeave)
- Multi-cloud enterprise deployments
- Teams needing extensive managed services
- Non-ML general compute workloads
What's Great
- Competitive GPU pricing vs hyperscalers
- Lambda Stack: one-line ML framework install
- Same environment across cloud and hardware
- Simple, developer-focused interface
- Fast instance spin-up times
- No complex IAM or networking setup
- Good availability for popular GPU types
Watch Out For
- Smaller region footprint than AWS/GCP
- H100 availability can be limited
- Fewer managed services (no managed Kubernetes)
- Less enterprise compliance certifications
- Limited spot/preemptible options
Pricing
A10 (24GB)
$0.75/hr
Entry-level, inference workloads
A100 40GB
$1.29/hr
Training, fine-tuning LLMs
A100 80GB
$1.99/hr
Large model training
H100 80GB
$2.49/hr
Latest gen, fastest training
View all features & details
Cloud GPU Options
- NVIDIA H100 80GB SXM5
- NVIDIA A100 40GB/80GB
- NVIDIA A10 24GB
- Multi-GPU instances (1x, 2x, 4x, 8x)
- NVLink interconnect for multi-GPU
- Persistent storage options
Lambda Stack
- PyTorch (latest stable)
- TensorFlow 2.x
- CUDA Toolkit
- cuDNN
- Jupyter Lab pre-installed
- One-line install/update
Hardware Products
- Lambda Workstations (desktop)
- Lambda Servers (rack-mount)
- Lambda Hyperplane (multi-node)
- Pre-configured for deep learning
- 3-year warranty options
Features
- SSH access to instances
- Jupyter notebooks
- API for automation
- Persistent filesystems
- Private networking
- Team management
How It Compares
| Feature | Lambda Labs | RunPod | CoreWeave |
|---|---|---|---|
| H100 Pricing | ~$2.49/hr | ~$2.39/hr | ~$2.21/hr |
| A100 80GB | ~$1.99/hr | ~$1.89/hr | ~$2.06/hr |
| GPU Availability | Good | Variable | Enterprise focus |
| Spot/Preemptible | Limited | Yes, significant savings | Yes |
| ML Stack | Lambda Stack included | Manual setup | Manual setup |
| Regions | US (limited) | Global | US/EU |
| Managed K8s | No | No | Yes |
| On-prem Hardware | Workstations & servers | No | No |
| Best For | ML researchers, startups | Budget training | Enterprise inference |
User Reviews
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