# AgentSphere vs Rivet.dev

AgentSphere records 0 monthly visits with 0% month-over-month growth and Contact for Pricing pricing. Rivet.dev records 21,359 monthly visits with -44.3% growth and Freemium, Contact for Pricing pricing.

| Metric | [AgentSphere](https://openaitools.app/tool/agentsphere) | [Rivet.dev](https://openaitools.app/tool/rivet-dev) |
| :--- | :--- | :--- |
| Website URL | https://www.agentsphere.run | https://rivet.dev |
| Categories | AI Agent, AI Developer Tools, AI Workflow, Large Language Models (LLMs) | AI Agent, AI Workflow, AI Developer Tools, AI App Builder |
| Pricing Model | Contact for Pricing | Freemium, Contact for Pricing |
| Monthly Visits | 0 | 21,359 |
| MoM Growth Rate | 0% | -44.3% |
| Primary Market | Global | United States |
| Direct Visits | 0 | 10,710 |
| Review Score | 4.3 | 4.5 |
| 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)

## Rivet.dev

At its core Rivet replaces the container per agent with an in-process primitive. An Actor runs inside your existing Node.js or Bun backend rather than in its own container or VM, which is why Rivet reports cold starts measured in single-digit milliseconds and a footprint of tens of kilobytes per Actor instead of hundreds of megabytes. Each Actor carries a SQLite database for memory, can access a filesystem and shell, sleeps when idle, and wakes with its durable state ready for the next request.

The platform handles the operational pieces teams usually build themselves: fault tolerance that reschedules Actors when a node goes down, multi-region placement that routes requests to wherever an Actor currently lives, end-to-end type safety where Actor definitions generate client types, and scheduling via cron or self-set timestamps. Storage is pulled apart into two tiers — a fast SSD for instant writes and object storage that settles writes at a fraction of the cost — so running many small databases stays affordable.

Rivet positions itself as infrastructure for the "agentic era" and can be deployed as a managed cloud, inside your own VPC through a bring-your-own-cloud model, or fully self-hosted down to air-gapped networks. It is open source under Apache 2.0, backed by Y Combinator and a16z Speedrun, and integrates with popular coding agents and frameworks.

**Pricing & Plans:** Rivet Cloud uses a plan-plus-nodes model. The control plane is Free ($0) for prototyping, Hobby at $10/month, Team at $120/month, and Enterprise at $900/month, each raising control-plane redundancy, Actor Node caps, and support. Actor Nodes are billed per month on top, from $4.20 (R-5) to $94.50 (R-160). Self-hosting is free and open source under Apache 2.0, and startups from Y Combinator or a16z Speedrun get 50% off the Team plan for 12 months.

- **Durable actors with persistent state:** Every Actor gets a SQLite database and a filesystem, so an agent's memory and progress survive restarts and idle periods without a separate database.
- **Lightweight secure sandboxing:** Run untrusted or AI-generated code on your own infrastructure with fine-grained control over network access, filesystem permissions, and resource limits.
- **Fault tolerance and workflows:** A node failure reschedules its Actors elsewhere with state intact, and multi-step work replays after a crash — with no checkpointing harness to build yourself.
- **Realtime and multiplayer:** Address an Actor directly over HTTP or hold a live WebSocket, and use the React SDK to subscribe components to an Actor's state in real time.
- **One-binary deployment and observability:** Ship with a single stateless Rust binary, embeds storage in S3-compatible buckets, and emits OpenTelemetry traces, metrics, and logs to your existing collector.

**Strengths:** Four-digit millisecond cold starts and a very small per-Actor memory footprint let a single server host far more agents; Open source (Apache 2.0) with a single Rust binary, so it can be self-hosted, run in a VPC, or air-gapped; Durable state via per-Actor SQLite plus object-storage-backed tiers keeps agents restart-safe and cheap; Strong developer ergonomics: typed SDKs, a React SDK, WebSocket networking, and OpenTelemetry baked in

**Limitations:** Requires Node.js or Bun and a working Rust-based control plane deployment for self-hosting, so it favors backend engineers over no-code users; Advanced durability and sandboxing concepts (Actors, WarpDrive storage) carry a learning curve; Managed cloud cost scales with Actor Nodes, which can climb for many mid-sized/sized nodes; Enterprise features like multi-tenancy and hardened compliance guidance sit behind sales conversations

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

## Frequently Asked Questions

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

AgentSphere has 0 monthly visits, while Rivet.dev has 21,359. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

AgentSphere has a month-over-month growth rate of 0%; Rivet.dev has -44.3%.

### 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. Rivet.dev: Freemium, Contact for Pricing. Rivet Cloud uses a plan-plus-nodes model. The control plane is Free ($0) for prototyping, Hobby at $10/month, Team at $120/month, and Enterprise at $900/month, each raising control-plane redundancy, Actor Node caps, and support. Actor Nodes are billed per month on top, from $4.20 (R-5) to $94.50 (R-160). Self-hosting is free and open source under Apache 2.0, and startups from Y Combinator or a16z Speedrun get 50% off the Team plan for 12 months.

## 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 | [Mastra](https://openaitools.app/tool/mastra) | 318,954 | -5% | Freemium, Contact for Pricing | The TypeScript framework for building, deploying, and observing AI agents | [.md](https://openaitools.app/tool/mastra.md) |
| 5 | [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) |
| 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 | [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) |
| 9 | [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) |
| 10 | [exe.dev](https://openaitools.app/tool/exe-dev) | 60,103 | -26.4% | Freemium, Paid | Cloud Linux VMs built for developers and their AI agents | [.md](https://openaitools.app/tool/exe-dev.md) |

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

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