Baseten vs Lambda Labs Comparison
Detailed comparison of features, pricing, and capabilities
Last updated May 1, 2026
Overview
Compare key metrics and features at a glance
Baseten
https://www.baseten.co
Baseten is a machine learning infrastructure platform that enables developers and ML engineers to deploy, serve, and scale AI models in production. It provides tools for building model pipelines, creating model-backed applications, and managing inference workloads with support for popular frameworks like PyTorch, TensorFlow, and Hugging Face. Baseten focuses on simplifying the MLOps workflow by offering features such as autoscaling, GPU support, and a Python-native SDK called Truss for packaging and deploying models.
Lambda Labs
https://lambdalabs.com
Lambda Labs (also known as Lambda) is a cloud computing and hardware company specializing in GPU-based infrastructure for AI and machine learning workloads. The company offers on-demand and reserved GPU cloud instances, as well as on-premise GPU servers and workstations, designed for training and deploying deep learning models. Lambda serves researchers, startups, and enterprises seeking high-performance compute at competitive pricing compared to hyperscale cloud providers.
Quick Comparison
| Detail | Baseten | Lambda Labs |
|---|---|---|
| Category | AI Cloud Infrastructure | AI Cloud Infrastructure |
| Starting Price | Free | $496.8/mo |
| Plans Available | 3 | 9 |
| Features Tracked | 14 | 15 |
| Founded | 2020 | 2012 |
| Headquarters | San Francisco, USA | San Francisco, USA |
Features
Detailed feature-by-feature comparison
Feature Comparison
| Feature | ||
|---|---|---|
| api | ||
| API Monitoring | ||
| REST API Endpoints | ||
| compliance | ||
| SOC 2 Type II | ||
| core | ||
| 1-Click Clusters | ||
| Autoscaling | ||
| Bare Metal Instances | ||
| Block Storage | ||
| GPU Instances | ||
| GPU/CPU Infrastructure | ||
| Global Scaling | ||
| Inference Optimization | ||
| Lambda Stack | ||
| Model Deployment | ||
| Monitoring & Logging | ||
| Multi-Model Workflows | ||
| NVIDIA InfiniBand | ||
| No Egress Fees | ||
| Pay by the Minute | ||
| Private Cloud | ||
| Superclusters | ||
| Truss Deployment | ||
| Zero Throttling | ||
| custom | ||
| Custom Environments | ||
| Hybrid Deployments | ||
| integration | ||
| SDK Integration | ||
| security | ||
| API Key Access Control | ||
| Biometric Access | ||
| Single-Tenant Clusters | ||
| support | ||
| Dashboard Monitoring | ||
Pricing
Compare pricing plans and value for money
Baseten
From $0/mo
Price Components
- Monthly Subscription: $0/month
- DeepSeek V4 Input: $0.00000174/token
- DeepSeek V4 Output: $0.00000348/token
- GPU Compute T4: $0.01052/minute
- GPU Compute A100: $0.06667/minute
Best For
ML engineers and AI teams deploying production-scale open-source or custom models needing fast autoscaling, GPU optimization, and compliance without managing infrastructure.
Lambda Labs
From $496.8/mo
Price Components
- GPU Hour: $9.86/hour
- Reserved Capacity: $0/cluster
- GPU Hour: $6.16/hour
- GPU Hour: $6.69/hour
- GPU Hour: $3.99/hour
Best For
ML researchers and startups running large-scale distributed training jobs who prioritize cost efficiency and hardware control over managed service breadth.
Integrations
See which third-party services are supported
Supported Integrations
Coming Soon
Integration comparison data for Baseten, Lambda Labs is being collected and will be available soon.
Strengths & Limitations
Key strengths and limitations of each service
Baseten
ML engineers and AI teams deploying production-scale open-source or custom models needing fast autoscaling, GPU optimization, and compliance without managing infrastructure.
- Truss SDK enables Python-native packaging and deployment of models from PyTorch, TensorFlow, and Hugging Face, simplifying MLOps beyond general cloud ML services.
- Autoscaling to zero with global multi-cloud GPU capacity supports massive inference scale and cost efficiency unmatched by broader hyperscalers.
- OpenAI-compatible APIs and Baseten Chains optimize latency/throughput 2x+ faster than competitors like Fireworks or Modal.
- SOC 2 Type II, HIPAA/GDPR compliance with no input/output storage and hybrid self-host options for secure enterprise AI.
- Smaller scale (51-200 employees, Series B) limits global infra compared to hyperscalers like AWS SageMaker or GCP Vertex AI.
- Pro and Enterprise tiers require volume commitments for discounts and custom SLAs, less ideal for tiny teams on strict budgets.
Lambda Labs
ML researchers and startups running large-scale distributed training jobs who prioritize cost efficiency and hardware control over managed service breadth.
- Per-second billing with no egress fees undercuts hyperscale providers on total cost of ownership for GPU workloads
- Bare metal access and Quantum-2 InfiniBand networking enable efficient distributed training across hundreds of GPUs
- Lambda Stack pre-installation eliminates environment setup friction, reducing time-to-training from days to minutes
- Smaller scale and regional availability compared to AWS, Google Cloud, and Azure limits enterprise multi-region deployments
- Limited managed services ecosystem; users handle more infrastructure complexity than with hyperscale competitors
Company Info
Company details and background
Baseten
Lambda Labs
Comparison FAQ
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