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Compare GPU and LLM inference API pricing between fal.ai and Paperspace. Find the best rates for AI training, inference, and ML workloads.
Provider 1
Provider 2
Average Price Difference: $4.06/hour between comparable GPUs
| GPU Model ↑ | fal.ai Price | Paperspace Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
A100 SXM 80GB VRAM • Paperspace | Not Available | 4x GPU | — | |
A100 SXM 80GB VRAM • | ||||
B200 192GB VRAM • fal.ai | Not Available | — | ||
B200 192GB VRAM • | ||||
H100 SXM 80GB VRAM • fal.aiPaperspace | ↓$4.06(68.2%) | |||
H100 SXM 80GB VRAM • $1.89/hour Updated: 7/5/2026 ★Best Price $5.95/hour Updated: 7/16/2026 Price Difference:↓$4.06(68.2%) | ||||
H200 141GB VRAM • fal.ai | Not Available | — | ||
H200 141GB VRAM • | ||||
HGX B300 288GB VRAM • fal.ai | Not Available | — | ||
HGX B300 288GB VRAM • | ||||
RTX A4000 16GB VRAM • Paperspace | Not Available | — | ||
RTX A4000 16GB VRAM • | ||||
RTX A5000 24GB VRAM • Paperspace | Not Available | — | ||
RTX A5000 24GB VRAM • | ||||
RTX A6000 48GB VRAM • Paperspace | Not Available | 8x GPU | — | |
RTX A6000 48GB VRAM • | ||||
RTX PRO 6000 96GB VRAM • fal.ai | Not Available | — | ||
RTX PRO 6000 96GB VRAM • | ||||
Tesla V100 32GB VRAM • Paperspace | Not Available | 8x GPU | — | |
Tesla V100 32GB VRAM • | ||||
A100 SXM 80GB VRAM • Paperspace | Not Available | 4x GPU | — | |
A100 SXM 80GB VRAM • | ||||
B200 192GB VRAM • fal.ai | Not Available | — | ||
B200 192GB VRAM • | ||||
H100 SXM 80GB VRAM • fal.aiPaperspace | ↓$4.06(68.2%) | |||
H100 SXM 80GB VRAM • $1.89/hour Updated: 7/5/2026 ★Best Price $5.95/hour Updated: 7/16/2026 Price Difference:↓$4.06(68.2%) | ||||
H200 141GB VRAM • fal.ai | Not Available | — | ||
H200 141GB VRAM • | ||||
HGX B300 288GB VRAM • fal.ai | Not Available | — | ||
HGX B300 288GB VRAM • | ||||
RTX A4000 16GB VRAM • Paperspace | Not Available | — | ||
RTX A4000 16GB VRAM • | ||||
RTX A5000 24GB VRAM • Paperspace | Not Available | — | ||
RTX A5000 24GB VRAM • | ||||
RTX A6000 48GB VRAM • Paperspace | Not Available | 8x GPU | — | |
RTX A6000 48GB VRAM • | ||||
RTX PRO 6000 96GB VRAM • fal.ai | Not Available | — | ||
RTX PRO 6000 96GB VRAM • | ||||
Tesla V100 32GB VRAM • Paperspace | Not Available | 8x GPU | — | |
Tesla V100 32GB VRAM • | ||||
Explore how these providers compare to other popular GPU cloud services
Compare fal.ai with another leading provider
Compare fal.ai with another leading provider
Compare fal.ai with another leading provider
Compare fal.ai with another leading provider
Compare fal.ai with another leading provider
Compare fal.ai with another leading provider
Production endpoints for image, video and audio models billed per call or per second
Run private models on dedicated NVIDIA GPUs with autoscaling and scale-to-zero
Inference engines tuned for diffusion and audio workloads
Interactive Jupyter notebooks with a free tier, pre-configured templates, and access to powerful GPUs.
Serve machine learning models as scalable API endpoints.
High-performance virtual machines with a wide variety of NVIDIA GPUs for demanding workloads.
Features for teams to collaborate on projects, including shared drives and SSO.
Offers persistent storage that can be shared across different machines and notebooks.
Programmatic access to the Paperspace platform to automate workflows.
Virtual machines with a wide range of NVIDIA GPUs for various workloads.
Managed Jupyter notebooks for interactive development and experimentation.
A serverless product for deploying trained models as REST APIs.
Hosted model endpoints billed per request or per generated unit
Custom deployments billed per second of GPU runtime, with scale-to-zero
Volume commitments and dedicated capacity for high-throughput customers
Sign up and generate an API key
Choose from the catalog or define a custom GPU-backed deployment
Invoke endpoints from any language using the REST or SDK clients
Sign up for a Paperspace account. You can start with a free plan.
Select the product that best fits your needs, such as Gradient Notebooks for interactive development or Core Machines for more control.
Choose a pre-configured template for your desired framework and select a GPU or CPU instance.
Launch your machine or notebook and begin building, training, or deploying your AI applications.
Multi-region serverless infrastructure
Documentation, community channels and enterprise support for paid customers
Data centers are located in the US (Secaucus, NJ and Santa Clara, CA) and Europe (Amsterdam, NL).
Support is available through a community forum, extensive documentation, and a support ticket system.