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Compare GPU and LLM inference API pricing between Beam and Modal. Find the best rates for AI training, inference, and ML workloads.
Provider 1
Provider 2
Average Price Difference: $0.91/hour between comparable GPUs
| GPU Model ↑ | Beam Price | Modal Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
A10 24GB VRAM • BeamModal | ↑+$0.34(+48.5%) | |||
A100 SXM 80GB VRAM • BeamModal | ↑+$0.09(+7.3%) | |||
B200 192GB VRAM • Modal | Not Available | — | ||
B200 192GB VRAM • | ||||
H100 PCIe 80GB VRAM • Beam | Not Available | — | ||
H100 PCIe 80GB VRAM • | ||||
H100 SXM 80GB VRAM • Modal | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • Modal | Not Available | — | ||
H200 141GB VRAM • | ||||
L40S 48GB VRAM • Modal | Not Available | — | ||
L40S 48GB VRAM • | ||||
RTX 4090 24GB VRAM • Beam | Not Available | — | ||
RTX 4090 24GB VRAM • | ||||
RTX PRO 6000 96GB VRAM • BeamModal | ↓$2.29(68.8%) | |||
A10 24GB VRAM • BeamModal | ↑+$0.34(+48.5%) | |||
A100 SXM 80GB VRAM • BeamModal | ↑+$0.09(+7.3%) | |||
B200 192GB VRAM • Modal | Not Available | — | ||
B200 192GB VRAM • | ||||
H100 PCIe 80GB VRAM • Beam | Not Available | — | ||
H100 PCIe 80GB VRAM • | ||||
H100 SXM 80GB VRAM • Modal | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • Modal | Not Available | — | ||
H200 141GB VRAM • | ||||
L40S 48GB VRAM • Modal | Not Available | — | ||
L40S 48GB VRAM • | ||||
RTX 4090 24GB VRAM • Beam | Not Available | — | ||
RTX 4090 24GB VRAM • | ||||
RTX PRO 6000 96GB VRAM • BeamModal | ↓$2.29(68.8%) | |||
Explore how these providers compare to other popular GPU cloud services
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Compare Beam with another leading provider
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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
Run Python functions on NVIDIA GPUs without provisioning instances; cold starts in seconds
Pay for actual GPU runtime at sub-minute granularity, with scale-to-zero by default
Define environments in code, with automatic image building and caching
From T4 and L4 through A100, L40S, H100, H200 and B200
Deploy high-performance inference endpoints with custom models
Secure code execution environments for AI agents
Run large-scale workloads with distributed processing
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
Charged per second of GPU runtime, with scale-to-zero when idle
Monthly free credits for experimentation and personal projects
Volume commitments and enterprise support for production deployments
Sign up on the Beam platform
Create a virtual environment and install the Beam SDK
Configure your API token to connect to Beam
Run `pip install modal` and authenticate via the CLI
Decorate a Python function with the desired GPU and image specification
Invoke locally or deploy as a long-lived endpoint or scheduled job
Multi-region availability across North America and Europe
Documentation, community forum, and enterprise support for paid plans