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Compare GPU and LLM inference API pricing between Beam and DigitalOcean. Find the best rates for AI training, inference, and ML workloads.
Provider 1
Provider 2
| GPU Model ↑ | Beam Price | DigitalOcean Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
H100 PCIe 80GB VRAM • Beam | Not Available | — | ||
H100 PCIe 80GB VRAM • | ||||
H100 SXM 80GB VRAM • DigitalOcean | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • DigitalOcean | Not Available | — | ||
H200 141GB VRAM • | ||||
HGX B300 288GB VRAM • DigitalOcean | Not Available | — | ||
HGX B300 288GB VRAM • | ||||
L40S 48GB VRAM • DigitalOcean | Not Available | — | ||
L40S 48GB VRAM • | ||||
MI300X 192GB VRAM • DigitalOcean | Not Available | — | ||
MI300X 192GB VRAM • | ||||
MI325X 256GB VRAM • DigitalOcean | Not Available | — | ||
MI325X 256GB VRAM • | ||||
MI355X 288GB VRAM • DigitalOcean | Not Available | — | ||
MI355X 288GB VRAM • | ||||
RTX 4000 Ada 20GB VRAM • DigitalOcean | Not Available | — | ||
RTX 4000 Ada 20GB VRAM • | ||||
RTX 4090 24GB VRAM • Beam | Not Available | — | ||
RTX 4090 24GB VRAM • | ||||
RTX 5090 32GB VRAM • Beam | Not Available | — | ||
RTX 5090 32GB VRAM • | ||||
RTX 6000 Ada 48GB VRAM • DigitalOcean | Not Available | — | ||
RTX 6000 Ada 48GB VRAM • | ||||
H100 PCIe 80GB VRAM • Beam | Not Available | — | ||
H100 PCIe 80GB VRAM • | ||||
H100 SXM 80GB VRAM • DigitalOcean | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • DigitalOcean | Not Available | — | ||
H200 141GB VRAM • | ||||
HGX B300 288GB VRAM • DigitalOcean | Not Available | — | ||
HGX B300 288GB VRAM • | ||||
L40S 48GB VRAM • DigitalOcean | Not Available | — | ||
L40S 48GB VRAM • | ||||
MI300X 192GB VRAM • DigitalOcean | Not Available | — | ||
MI300X 192GB VRAM • | ||||
MI325X 256GB VRAM • DigitalOcean | Not Available | — | ||
MI325X 256GB VRAM • | ||||
MI355X 288GB VRAM • DigitalOcean | Not Available | — | ||
MI355X 288GB VRAM • | ||||
RTX 4000 Ada 20GB VRAM • DigitalOcean | Not Available | — | ||
RTX 4000 Ada 20GB VRAM • | ||||
RTX 4090 24GB VRAM • Beam | Not Available | — | ||
RTX 4090 24GB VRAM • | ||||
RTX 5090 32GB VRAM • Beam | Not Available | — | ||
RTX 5090 32GB VRAM • | ||||
RTX 6000 Ada 48GB VRAM • DigitalOcean | Not Available | — | ||
RTX 6000 Ada 48GB VRAM • | ||||
| Model ↑ | Beam | DigitalOcean | Input Diff ↕ |
|---|---|---|---|
Anthropic | Not available | $10.00 in $50.00 out | — |
Anthropic | Not available | $10.00 in $50.00 out | — |
Anthropic | Not available | $1.00 in $5.00 out | — |
Anthropic | Not available | $5.00 in $25.00 out | — |
Anthropic | Not available | $5.00 in $25.00 out | — |
Anthropic | Not available | $5.00 in $25.00 out | — |
Anthropic | Not available | $5.00 in $25.00 out | — |
Anthropic | Not available | $5.00 in $25.00 out | — |
Anthropic | Not available | $3.00 in $15.00 out | — |
Anthropic | Not available | $3.00 in $15.00 out | — |
Anthropic | Not available | $2.00 in $10.00 out | — |
DeepSeek | Not available | $0.250 in $0.800 out | — |
DeepSeek | Not available | $0.068 in $0.168 out | — |
DeepSeek | Not available | $0.870 in $1.74 out | — |
Google | Not available | $0.180 in $0.500 out | — |
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
Memory snapshots and GPU checkpoint restore bring containers back in seconds, which Beam reports as up to 35x faster than a traditional cold boot
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, including running the Docker daemon inside containers
On-demand NVIDIA and AMD GPU instances with per-hour billing and no long-term contracts.
Pre-configured images with PyTorch, TensorFlow, and CUDA for immediate productivity.
GPU Droplets work seamlessly with DigitalOcean's networking, storage, and managed databases.
Transparent per-hour pricing with no hidden fees or complex instance families.
Deploy high-performance inference endpoints with custom models
Secure code execution environments for AI agents
Run large-scale workloads with distributed processing
Serverless GPU, CPU, and sandbox usage billed by the millisecond with no minimum charges
Serverless access to GPUs beyond the RTX 4090 is arranged through a committed-spend agreement
Flat hourly price per machine that already includes the vCPU, RAM, and NVMe storage
Multi-node InfiniBand clusters reserved monthly or yearly, quoted through sales
Per-vCPU and per-GB management fee on top of compute billed directly by your own cloud provider
Persistent volumes and snapshots included up to a capacity threshold, then billed per GB per month
Developer plan free with usage, Team plan with a monthly base fee plus usage, and a contact-sales Growth tier
All plans include monthly free credits that refresh each month
Discounts available for high monthly usage, arranged through sales
Sign up on the Beam platform to receive monthly free credits
Create a virtual environment and install the Beam SDK
Configure your API token to connect to Beam
Run a function locally, then deploy it as a web endpoint with the Beam CLI
Sign up at digitalocean.com and verify your account.
Select GPU Droplets from the Create menu, choose your GPU type and configuration.
Select a pre-configured AI/ML image or a base OS image.
Launch your GPU Droplet and connect via SSH to start working.
30+ regions spanning the US, EU, Asia-Pacific, and Canada, with workloads routed across clouds and regions in real time
Documentation, public Slack community, and a status page; live chat support on paid plans and a private Slack channel on the top tier
GPU Droplets are available in select US data centers with expansion planned.
24/7 support via ticket system, extensive documentation, and active community forums.