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Compare GPU and LLM inference API pricing between Beam and Paperspace. Find the best rates for AI training, inference, and ML workloads.
Provider 1
Provider 2
Average Price Difference: $1.81/hour between comparable GPUs
| GPU Model ↑ | Beam Price | Paperspace Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
A10 24GB VRAM • Beam | Not Available | — | ||
A10 24GB VRAM • | ||||
A100 SXM 80GB VRAM • BeamPaperspace | 4x GPU | ↓$1.81(58.2%) | ||
A100 SXM 80GB VRAM • $1.30/hour Updated: 7/16/2026 ★Best Price $3.11/hour 4x GPU configuration Updated: 7/16/2026 Price Difference:↓$1.81(58.2%) | ||||
H100 PCIe 80GB VRAM • Beam | Not Available | — | ||
H100 PCIe 80GB VRAM • | ||||
H100 SXM 80GB VRAM • Paperspace | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • Beam | Not Available | — | ||
H200 141GB VRAM • | ||||
L40S 48GB VRAM • Beam | Not Available | — | ||
L40S 48GB VRAM • | ||||
RTX 4090 24GB VRAM • Beam | Not Available | — | ||
RTX 4090 24GB VRAM • | ||||
RTX 5090 32GB VRAM • Beam | Not Available | — | ||
RTX 5090 32GB 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 • Beam | Not Available | — | ||
RTX PRO 6000 96GB VRAM • | ||||
Tesla V100 32GB VRAM • Paperspace | Not Available | 8x GPU | — | |
Tesla V100 32GB VRAM • | ||||
A10 24GB VRAM • Beam | Not Available | — | ||
A10 24GB VRAM • | ||||
A100 SXM 80GB VRAM • BeamPaperspace | 4x GPU | ↓$1.81(58.2%) | ||
A100 SXM 80GB VRAM • $1.30/hour Updated: 7/16/2026 ★Best Price $3.11/hour 4x GPU configuration Updated: 7/16/2026 Price Difference:↓$1.81(58.2%) | ||||
H100 PCIe 80GB VRAM • Beam | Not Available | — | ||
H100 PCIe 80GB VRAM • | ||||
H100 SXM 80GB VRAM • Paperspace | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • Beam | Not Available | — | ||
H200 141GB VRAM • | ||||
L40S 48GB VRAM • Beam | Not Available | — | ||
L40S 48GB VRAM • | ||||
RTX 4090 24GB VRAM • Beam | Not Available | — | ||
RTX 4090 24GB VRAM • | ||||
RTX 5090 32GB VRAM • Beam | Not Available | — | ||
RTX 5090 32GB 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 • Beam | 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 Beam with another leading provider
Compare Beam with another leading provider
Compare Beam with another leading provider
Compare Beam with another leading provider
Compare Beam with another leading provider
Compare Beam with another leading provider
Only charged when your code runs, no charges for cold starts or server spin-up
Ultrafast boot times with advanced container optimization
Run untrusted code safely in isolated environments for AI agents and code interpreters
Pause and resume sessions while maintaining filesystem, memory, and running processes
Scale to zero when idle, burst to thousands of containers in seconds
Bring your own Docker images for full environment control
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.
Deploy high-performance inference endpoints with custom models
Secure code execution environments for AI agents
Run large-scale workloads with distributed processing
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.
Only pay for actual compute time with no minimum charges
Developer plan free with usage, Team plan starts at monthly base fee plus usage
All plans include monthly free credits for getting started
Sign up on the Beam platform
Create a virtual environment and install the Beam SDK
Configure your API token to connect to Beam
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.
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.