# Sesterce Cloud vs Thunder Compute

Sesterce Cloud records 2,158 monthly visits with -82% month-over-month growth and Paid pricing. Thunder Compute records 102,147 monthly visits with -29% growth and Paid (per-minute instances, per-second sandboxes) pricing.

| Metric | [Sesterce Cloud](https://openaitools.app/tool/sesterce-cloud) | [Thunder Compute](https://openaitools.app/tool/thunder-compute) |
| :--- | :--- | :--- |
| Website URL | https://cloud.sesterce.com | https://thundercompute.com |
| Categories | AI Developer Tools | AI Developer Tools, AI Models, Large Language Models (LLMs) |
| Pricing Model | Paid | Paid (per-minute instances, per-second sandboxes) |
| Monthly Visits | 2,158 | 102,147 |
| MoM Growth Rate | -82% | -29% |
| Primary Market | Netherlands | United States |
| Direct Visits | 594 | 40,743 |
| Review Score | 4.3 | 4.4 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## Sesterce Cloud

Sesterce Cloud is a GPU-focused cloud platform that lets teams rent high-performance accelerators by the hour instead of buying hardware. Its catalog covers datacenter and consumer GPUs — H200, H100, A100 (40GB and 80GB), GAUDI2, RTX Pro 6000, RTX 5090, RTX 4090, L40/L40S, A6000, A5000, A4000, A40, L4, A10 and V100 among them — alongside CPU-only instances for lighter jobs.

Beyond single machines, the platform supports bare-metal servers, spot offers and multi-GPU cluster configurations, with combinations such as 8x H100, 8x A100, 1x to 8x RTX 5090 and 8x GAUDI2 listed with their combined vRAM, vCPU and system RAM. Pricing is displayed per hour of compute, and persistent volumes let you keep datasets and checkpoints between sessions. Documentation and an API reference support programmatic provisioning.

The positioning is a European, high-performance and energy-conscious alternative to hyperscaler GPU capacity, aimed at AI training, inference, generative AI and HPC workloads. Because the platform publishes hardware, region and hourly rate together, it suits teams that want to compare cost and location before committing.

**Pricing & Plans:** Hourly, on-demand pricing without commitment for standard instances, with rates published per GPU model on the compute page. Cluster and bare-metal configurations are quoted by their combined hardware. Check the platform for current rates.

- **On-Demand GPU Instances:** Deploy single-GPU or multi-GPU instances in minutes from a public catalog of H200, H100, A100, GAUDI2, RTX and L40S hardware.
- **Bare Metal and Clusters:** Reserve bare-metal nodes and multi-GPU clusters with dedicated vRAM, vCPU and RAM for large training runs.
- **Transparent Hourly Pricing:** Every GPU class is listed with an hourly rate and available regions, so you can compare cost before launching.
- **Persistent Storage and API:** Attach persistent volumes, use the documented API and manage everything from a single web console.
- **Broad Hardware Selection:** Choose from consumer and datacenter accelerators including Gaudi and RTX cards to match budget and workload.

**Strengths:** Wide accelerator selection from RTX consumer cards up to H200 and GAUDI2; Hourly on-demand pricing with rates shown up front; Bare-metal and multi-GPU clusters for large training runs; European provider positioning with API and documentation available

[Profile (Markdown)](https://openaitools.app/tool/sesterce-cloud.md)

## Thunder Compute

Thunder Compute is a cloud GPU provider that markets itself as the GPU sandbox company. Rather than a single generic VM offering, it splits its product into two shapes. Instances are long-lived GPU machines for hands-on development and training, available with RTX A6000, L40, A100 80GB, or H100 SXM GPUs, configurable across GPU count, vCPU, RAM, and disk, and billable per minute only while running. Sandboxes are isolated, short-lived Ubuntu microVMs designed for agent workloads: reinforcement-learning environments, evaluation sweeps, and CI jobs that need a GPU for a few minutes and can then disappear.

The company leans on price and developer ergonomics. Its published rates list H100 SXM instances at $3.20 per GPU-hour, A100 80GB at $1.09, L40 at $0.79, and RTX A6000 at $0.35, with per-second sandbox pricing of $2.95 per GPU-hour for H100 and $1.95 for A100. Storage is metered per GB-month with monthly snapshot pricing, and there are no data egress fees. Thunder Compute says it keeps costs down by scheduling workloads efficiently and reducing idle time, and passes those savings on.

The workflow is designed to be scriptable rather than click-heavy. A CLI handles instance creation and connection, a VS Code extension supports in-editor iteration, and an MCP server plus REST API let agents and internal platforms provision GPUs programmatically. Snapshots preserve disk state between sessions, and neither instances nor sandboxes can be preempted. The company raised a $13 million Series A in 2026 to expand the platform, and documents the stack through guides, quickstarts, and API references.

**Pricing & Plans:** Thunder Compute bills instances per minute while running and sandboxes per second. Published instance rates: RTX A6000 $0.35/GPU-hour, L40 $0.79, A100 80GB $1.09, H100 SXM $3.20, with extra vCPUs at $0.04/vCPU-hour. Sandbox rates are $2.95/GPU-hour for H100 SXM and $1.95/GPU-hour for A100 80GB plus vCPU, memory, and storage components. Instance disk storage is $0.219/GB per month (first 100 GB per GPU included), snapshots are $0.05/GB per month, and data egress is free. Grilled specifically: rates change over time, so verify on the pricing page.

- **Persistent GPU instances:** Launch RTX A6000, L40, A100 80GB, or H100 SXM machines, often ready to SSH into within minutes, and pay only while they run.
- **Per-second GPU sandboxes:** Spin up isolated Ubuntu VMs with or without a GPU for RL rollouts, evals, and CI, billed per second and scaled to zero between runs.
- **Developer-first tooling:** A CLI, VS Code extension, MCP server, and REST API let you drive infrastructure from a terminal, an editor, an AI agent, or your own services.
- **Snapshots and persistent storage:** Save an instance disk as a snapshot and restore it later, so you can pause experiments without leaving machines running.
- **No preemption, no egress fees:** Instances and sandboxes are never preempted, and outbound data transfer is not billed.

**Strengths:** Aggressive pricing versus hyperscalers: published H100 rates around $3.20/GPU-hour against $6+ at major clouds.; Two billing models that match two real workloads: per-minute persistent instances and per-second ephemeral sandboxes.; No egress fees and no preemption, which removes two common sources of surprise cost and interruption.; Real developer surface area: CLI, VS Code extension, MCP server, REST API, and templates.

**Limitations:** GPU availability can fluctuate, so a particular type may be sold out when you try to launch it.; Sandbox access is requested through sales rather than being fully self-serve at sign-up.; The platform's GPU catalog is narrower than the largest hyperscalers, which offer a wider range of accelerator families.

[Profile (Markdown)](https://openaitools.app/tool/thunder-compute.md)

## Frequently Asked Questions

### How do Sesterce Cloud and Thunder Compute compare in monthly traffic?

Sesterce Cloud has 2,158 monthly visits, while Thunder Compute has 102,147. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Sesterce Cloud has a month-over-month growth rate of -82%; Thunder Compute has -29%.

### How does pricing compare?

Sesterce Cloud: Paid. Hourly, on-demand pricing without commitment for standard instances, with rates published per GPU model on the compute page. Cluster and bare-metal configurations are quoted by their combined hardware. Check the platform for current rates. Thunder Compute: Paid (per-minute instances, per-second sandboxes). Thunder Compute bills instances per minute while running and sandboxes per second. Published instance rates: RTX A6000 $0.35/GPU-hour, L40 $0.79, A100 80GB $1.09, H100 SXM $3.20, with extra vCPUs at $0.04/vCPU-hour. Sandbox rates are $2.95/GPU-hour for H100 SXM and $1.95/GPU-hour for A100 80GB plus vCPU, memory, and storage components. Instance disk storage is $0.219/GB per month (first 100 GB per GPU included), snapshots are $0.05/GB per month, and data egress is free. Grilled specifically: rates change over time, so verify on the pricing page.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [RunPod](https://openaitools.app/tool/runpod) | 2,881,043 | +5.9% | Paid | The AI developer cloud for GPU pods, serverless inference and clustering | [.md](https://openaitools.app/tool/runpod.md) |
| 2 | [Vast.ai](https://openaitools.app/tool/vast-ai) | 1,257,554 | +2.8% | Paid | Rent cloud GPUs by the second from a global marketplace | [.md](https://openaitools.app/tool/vast-ai.md) |
| 3 | [Modal](https://openaitools.app/tool/modal-com) | 1,196,021 | +30.2% | Freemium, Contact for Pricing | Serverless cloud infrastructure for AI and data workloads | [.md](https://openaitools.app/tool/modal-com.md) |
| 4 | [Nebius](https://openaitools.app/tool/nebius) | 1,145,711 | +10.7% | Paid, Contact for Pricing | An AI-native cloud built from silicon to API for training, tuning, and serving models | [.md](https://openaitools.app/tool/nebius.md) |
| 5 | [Salad](https://openaitools.app/tool/salad-gpu-cloud) | 713,519 | +10.4% | Free Trial, Paid, Contact for Pricing | Distributed GPU cloud that orchestrates the world's idle consumer GPUs | [.md](https://openaitools.app/tool/salad-gpu-cloud.md) |
| 6 | [Lightning AI](https://openaitools.app/tool/lightning-ai) | 272,562 | -12.3% | Freemium, Paid, Contact for Pricing | The AI cloud built by the creators of PyTorch Lightning | [.md](https://openaitools.app/tool/lightning-ai.md) |
| 7 | [Novita AI](https://openaitools.app/tool/novita-ai) | 271,371 | -10.4% | Paid | One cloud for 200+ model APIs, agent sandboxes and GPU compute | [.md](https://openaitools.app/tool/novita-ai.md) |
| 8 | [FluidStack](https://openaitools.app/tool/fluidstack) | 154,620 | +7.3% | Paid, Contact for Pricing | Gigawatt-scale AI compute, built and operated end to end | [.md](https://openaitools.app/tool/fluidstack.md) |
| 9 | [Lium](https://openaitools.app/tool/lium-io) | 58,483 | -13.9% | Paid | Agent-first GPU cloud: rent NVIDIA pods by the second from your terminal or API | [.md](https://openaitools.app/tool/lium-io.md) |
| 10 | [Cirrascale](https://openaitools.app/tool/cirrascale-com) | 27,190 | +17.5% | Paid | Private AI cloud for training and inference workloads | [.md](https://openaitools.app/tool/cirrascale-com.md) |

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Source: https://openaitools.app/compare/sesterce-cloud-vs-thunder-compute

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