Baseten vs FluidStack 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.
FluidStack
https://www.fluidstack.io
FluidStack is a cloud GPU infrastructure provider that aggregates underutilized GPU capacity from data centers worldwide to offer on-demand and reserved GPU compute at competitive prices. The platform enables AI companies, researchers, and developers to access large-scale GPU clusters for training and inference workloads, including support for high-performance interconnects like InfiniBand. FluidStack differentiates itself by sourcing capacity from a distributed network of partner data centers, providing cost-effective alternatives to hyperscale cloud providers for AI/ML workloads.
Quick Comparison
| Detail | Baseten | FluidStack |
|---|---|---|
| Category | AI Cloud Infrastructure | AI Cloud Infrastructure |
| Starting Price | Free | Contact Sales |
| Plans Available | 3 | 1 |
| Features Tracked | 14 | 16 |
| Founded | 2020 | 2019 |
| Headquarters | San Francisco, USA | London, United Kingdom |
Features
Detailed feature-by-feature comparison
Feature Comparison
| Feature | | |
|---|---|---|
| api | ||
| REST API Endpoints | ||
| compliance | ||
| SOC 2 Type II | ||
| core | ||
| Autoscaling | ||
| Dedicated GPU Clusters | ||
| Fully Managed Clusters | ||
| GPU/CPU Infrastructure | ||
| Global Scaling | ||
| H100/H200/B200/GB200 Support | ||
| Inference Optimization | ||
| InfiniBand Interconnects | ||
| Kubernetes Support | ||
| Low-Latency Inference | ||
| Model Deployment | ||
| Monitoring & Logging | ||
| Multi-Model Workflows | ||
| Rapid Deployment | ||
| Slurm Support | ||
| Transparent Pricing | ||
| Truss Deployment | ||
| custom | ||
| Custom Data Centers | ||
| Custom Environments | ||
| Hybrid Deployments | ||
| integration | ||
| Distributed Data Access | ||
| SDK Integration | ||
| security | ||
| API Key Access Control | ||
| Secure Access Controls | ||
| Single-Tenant Isolation | ||
| support | ||
| 15-Minute Response SLA | ||
| 99% Uptime SLA | ||
| Proactive 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.
FluidStack
Contact Sales
Best For
AI companies and researchers needing rapid, cost-effective, fully managed large-scale dedicated GPU clusters for training without hyperscaler lock-in.
Integrations
See which third-party services are supported
Supported Integrations
Coming Soon
Integration comparison data for Baseten, FluidStack 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.
FluidStack
AI companies and researchers needing rapid, cost-effective, fully managed large-scale dedicated GPU clusters for training without hyperscaler lock-in.
- Rapid deployment of multi-thousand GPU clusters in as little as 48 hours with zero-setup management.
- Single-tenant isolation at hardware, network, and storage levels eliminates noisy neighbors unlike hyperscalers.
- Supports latest NVIDIA H100/H200/B200/GB200 GPUs with InfiniBand and 99% uptime SLA.
- 24/7 engineering support via Slack with 15-minute response times and proactive monitoring.
- Enterprise-only pricing requires contacting sales, lacking transparent pay-as-you-go rates.
- Small team of 11-50 employees and seed funding may limit scalability versus larger competitors.
- Aggregated capacity from partner data centers could introduce variability in global availability.
Company Info
Company details and background
Baseten
FluidStack
Comparison FAQ
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