# AgentSphere vs exe.dev

AgentSphere records 0 monthly visits with 0% month-over-month growth and Contact for Pricing pricing. exe.dev records 60,103 monthly visits with -26.4% growth and Freemium, Paid pricing.

| Metric | [AgentSphere](https://openaitools.app/tool/agentsphere) | [exe.dev](https://openaitools.app/tool/exe-dev) |
| :--- | :--- | :--- |
| Website URL | https://www.agentsphere.run | https://exe.dev |
| Categories | AI Agent, AI Developer Tools, AI Workflow, Large Language Models (LLMs) | AI Developer Tools, AI Agent, AI App Builder |
| Pricing Model | Contact for Pricing | Freemium, Paid |
| Monthly Visits | 0 | 60,103 |
| MoM Growth Rate | 0% | -26.4% |
| Primary Market | Global | United States |
| Direct Visits | 0 | 40,778 |
| Review Score | 4.3 | 4.3 |
| Saved Count | 1 | 0 |
| Supported Platforms | Website | Website |

## AgentSphere

AgentSphere is an AI-native cloud infrastructure service whose purpose is to run untrusted, machine-generated code safely. Rather than letting an agent touch a production system directly, you hand it an isolated cloud sandbox where it can execute Python or TypeScript, read and write files, and stream results back in real time. The platform advertises sub-second cold starts, in-region deployment, and isolation backed by lightweight virtual machines such as Firecracker, with SOC2 and GDPR compliance positioned as built-in rather than bolted on.

What differentiates AgentSphere is its MCP-first design. Rather than requiring a custom SDK for every use case, it exposes cloud sandboxes to MCP-capable clients, so an assistant or agent framework can request execution as just another tool. It also supports stateful workflows: sandboxes can persist storage, snapshot their state and be reactivated by events, which matters for long-running or multi-stage agent tasks. Typical scenarios include agent-driven DevOps and GitOps automation, large-scale model evaluation and fine-tuning experiments, secure data analysis, and rendering AI-generated dashboards or visuals inside an isolated environment.

AgentSphere targets developers and platform teams building AI products as well as enterprises that need governance. It is model- and language-agnostic, so it does not lock you to a single LLM provider or runtime, and it offers private deployment in your own AWS, GCP or on-prem environment with network isolation. Because it is developer infrastructure rather than a consumer app, adoption usually starts with a free trial and scales into usage-based or enterprise plans; the vendor does not publish fixed public price points, so commercial terms are typically discussed directly.

**Pricing & Plans:** No fixed public tiers. AgentSphere offers a free trial and positions itself around flexible, usage-based and enterprise plans (bursting compute, private deployment, SLAs); pricing is available on request.

- **MCP-integrated cloud sandboxes:** Connect MCP-capable clients and agents directly to isolated cloud sandboxes to execute AI-generated code and handle files securely.
- **Fast, isolated execution:** Cold-start latency advertised as low as roughly 100ms, with sandboxes deployed in-region and isolation backed by lightweight VMs such as Firecracker.
- **Stateful agents and multi-stage tasks:** Support for long-running workflows with storage persistence, snapshot recovery, streaming output and event-triggered reactivation.
- **Security and compliance posture:** SOC2 and GDPR compliance, access control, output tracing and full audit logging designed for running untrusted AI code in regulated environments.
- **Private deployment options:** Deploy inside your own AWS, GCP or on-prem infrastructure with VPC peering, identity controls and network isolation.

**Strengths:** Purpose-built for agentic workloads rather than retrofitted from a generic VM or container service; MCP-first integration lowers the effort to wire execution into existing AI assistants and frameworks; Strong isolation and compliance story (Firecracker-based VMs, SOC2/GDPR claims) suits regulated industries; Model- and language-agnostic, with private deployment in your own cloud and support for stateful, long-running tasks

**Limitations:** No transparent public pricing, which makes budgeting harder before a sales conversation; Feature set and claims lean enterprise-heavy, so simpler hobby projects may find it more than they need; Complex setup compared with a local code interpreter for very lightweight experimentation

[Profile (Markdown)](https://openaitools.app/tool/agentsphere.md)

## exe.dev

exe.dev is a Bay Area-built cloud computing platform aimed at a specific modern problem: developers increasingly run coding agents that need their own machines, and those machines need to behave like real servers rather than ephemeral containers. The product lets you buy a pool of vCPU and memory and then spin up as many VMs as you want inside it, fork them quickly, and SSH straight in with root access on Ubuntu-compatible images with apt and systemd available.

The platform positions itself as production-ready infrastructure, not just a scratchpad. VMs get fast, persistent, replicated NVMe storage, can be exposed publicly over HTTPS on *.exe.xyz subdomains, and can also host consumer-facing apps with authentication and secret management handled by the platform. A built-in LLM gateway can attach provider keys (OpenAI, Anthropic, xAI, Fireworks, Deepgram and others) to your machines so agents have model access without extra plumbing.

Pricing is transparent and published: a Personal plan starts at $15 per month for a 2 vCPU / 4 GiB pool, larger Personal pools scale up to 16 vCPU / 32 GiB, a Work plan adds SSO, unlimited users, larger VM counts per pool and hourly or monthly scaling, and Enterprise covers dedicated hardware and VPC connectivity. A seven-day trial is offered, and you can get started free through ChatGPT.

**Pricing & Plans:** Personal plans start at $15/month for 2 vCPU and 4 GiB of pooled memory, scaling to $155/month for 16 vCPU and 32 GiB. The Work plan is $75/month regular (intro $37.50/month for the first three months) with SSO, unlimited users and extra pool resources billed hourly. Enterprise pricing is custom, and a 7-day free trial is available.

- **Real persistent VMs, not sandboxes:** SSH into Ubuntu-compatible machines with root access, apt and systemd, then keep them running as long-lived servers instead of short-lived containers.
- **Pooled CPU and memory:** Buy vCPU and RAM once, then create as many VMs as you need inside the pool and fork them quickly for parallel agent work.
- **HTTPS and public hosting built in:** Expose internal apps privately or publish them publicly on *.exe.xyz subdomains, with auth and secret management handled for you.
- **LLM gateway for agents:** Attach OpenAI, Anthropic, xAI, Fireworks or Deepgram keys so agents running on your VMs have model access configured automatically.
- **Global regions and durable storage:** Deploy VMs across regions with fast, persistent and replicated NVMe storage, plus team features like SSO on higher-tier plans.

**Strengths:** Real root-access Linux VMs with persistent storage rather than ephemeral sandboxes; Transparent published pricing with a free trial and hourly scaling option; Built-in HTTPS exposure, auth, secrets and an LLM gateway for agent workloads; Fast VM creation and forking, useful for parallel agent tasks and preview environments

**Limitations:** Priced per resource pool, so heavy multi-VM usage can add up quickly; No free tier beyond the trial and ChatGPT-based signup path; Enterprise features such as VPC and dedicated hardware require contacting sales

[Profile (Markdown)](https://openaitools.app/tool/exe-dev.md)

## Frequently Asked Questions

### How do AgentSphere and exe.dev compare in monthly traffic?

AgentSphere has 0 monthly visits, while exe.dev has 60,103. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

AgentSphere has a month-over-month growth rate of 0%; exe.dev has -26.4%.

### How does pricing compare?

AgentSphere: Contact for Pricing. No fixed public tiers. AgentSphere offers a free trial and positions itself around flexible, usage-based and enterprise plans (bursting compute, private deployment, SLAs); pricing is available on request. exe.dev: Freemium, Paid. Personal plans start at $15/month for 2 vCPU and 4 GiB of pooled memory, scaling to $155/month for 16 vCPU and 32 GiB. The Work plan is $75/month regular (intro $37.50/month for the first three months) with SSO, unlimited users and extra pool resources billed hourly. Enterprise pricing is custom, and a 7-day free trial is available.

## 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 | [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) |
| 3 | [BLACKBOX.AI](https://openaitools.app/tool/blackbox-ai-1) | 622,975 | -27.2% | Free Trial, Paid | High-trust frontier inference, encrypted end to end | [.md](https://openaitools.app/tool/blackbox-ai-1.md) |
| 4 | [Browserbase](https://openaitools.app/tool/browserbase) | 283,597 | -8% | Freemium | Cloud browsers and web APIs for AI agents | [.md](https://openaitools.app/tool/browserbase.md) |
| 5 | [Zeabur](https://openaitools.app/tool/zeabur) | 275,642 | -15.9% | Free Trial, Paid | AI DevOps engineer that deploys and scales your apps | [.md](https://openaitools.app/tool/zeabur.md) |
| 6 | [Agent 37](https://openaitools.app/tool/agent-37) | 180,030 | +24.2% | Free Trial, Contact for Pricing | The low-cost cloud sandbox where AI agents actually live | [.md](https://openaitools.app/tool/agent-37.md) |
| 7 | [Coder](https://openaitools.app/tool/coder) | 149,417 | -12.8% | Free Trial, Contact for Pricing, Free | Self-hosted cloud development environments and AI coding agents for enterprise teams | [.md](https://openaitools.app/tool/coder.md) |
| 8 | [Thunder Compute](https://openaitools.app/tool/thunder-compute) | 102,147 | -29% | Paid (per-minute instances, per-second sandboxes) | Low-cost cloud GPUs with per-minute instances and per-second sandboxes for AI workloads. | [.md](https://openaitools.app/tool/thunder-compute.md) |
| 9 | [boat](https://openaitools.app/tool/boat) | 66,870 | +520.8% | Free Trial, Paid | Persistent Ubuntu cloud VMs built for AI agent factories | [.md](https://openaitools.app/tool/boat.md) |
| 10 | [InsForge](https://openaitools.app/tool/insforge) | 60,257 | -11.3% | Freemium, Contact for Pricing, Free | Agent-native cloud infrastructure that lets coding agents run the whole backend stack | [.md](https://openaitools.app/tool/insforge.md) |

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Source: https://openaitools.app/compare/agentsphere-vs-exe-dev

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)