# Rivet.dev vs RunPod

Rivet.dev enregistre 21 359 visites mensuelles avec une croissance mensuelle de -44,3 % et un modèle tarifaire Freemium, Tarifs sur demande. RunPod enregistre 2 881 043 visites mensuelles avec une croissance de +5,9 % et un modèle tarifaire Payant.

| Métrique | [Rivet.dev](https://openaitools.app/fr/tool/rivet-dev) | [RunPod](https://openaitools.app/fr/tool/runpod) |
| :--- | :--- | :--- |
| URL du site web | https://rivet.dev | https://runpod.io |
| Catégories | AI Agent, AI Workflow, Outils de développement IA, Générateur d'applications IA | Outils de développement IA, Modèles IA, Large Language Models (LLMs), AI API |
| Modèle tarifaire | Freemium, Tarifs sur demande | Payant |
| Visites mensuelles | 21 359 | 2 881 043 |
| Taux de croissance mensuel | -44,3 % | +5,9 % |
| Marché principal | États-Unis | États-Unis |
| Visites directes | 10 710 | 1 634 834 |
| Score d'avis | 4,5 | 4,7 |
| Nombre d'enregistrements | 0 | 4 |
| Plateformes prises en charge | Site web | Site web |

## Rivet.dev

Rivet is open-source infrastructure for running and scaling AI agents as "Actors" — durable, stateful compute units that live inside your own Node.js or Bun backend. Each Actor keeps persistent state, a filesystem, and a SQLite database, so agents survive restarts, share state, and run code written at runtime without a redeploy. Rivet ships as a single stateless Rust binary and can be self-hosted, run in your VPC, or used through a managed cloud.

**Tarifs et offres:** 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.

**Forces:** 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

**Limites:** 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/fr/tool/rivet-dev.md)

## RunPod

RunPod is a cloud platform for AI and machine learning workloads that rents GPU compute by the second. It offers Pods for persistent GPU instances, Serverless endpoints that autoscale inference from zero, and multi-node Clusters, plus a Hub of ready-to-deploy open-source models and templates.

**Tarifs et offres:** Paid, pay-as-you-go. GPU Pods are billed per second or per hour by card type, Serverless endpoints bill for active compute only with zero idle cost, and Clusters charge per GPU per hour. Storage starts at around $0.05/GB per month. A free tier and enterprise reserved-capacity contracts are also available.

- **On-demand GPU Pods:** Rent GPU instances with on-demand, interruptible or reserved capacity across more than 30 GPU SKUs, from RTX 4090s up to B200 and B300 class accelerators, deployed in 31 global regions.
- **Autoscaling Serverless endpoints:** Deploy any container as an API endpoint that scales from zero to thousands of workers on demand and bills only for the compute you actually use.
- **Multi-node Clusters:** Launch multi-node GPU clusters for distributed training and large inference jobs, with shared storage attachable and no long-term commitment required.
- **Model Hub and public endpoints:** Deploy popular open-source models from a curated hub, or use public endpoints for image, audio and text models without managing infrastructure.
- **Persistent storage:** Persistent network storage with standard and high-performance tiers, container and volume disks, and no egress fees for full AI pipelines.

**Forces:** Extremely broad GPU catalogue spanning consumer and datacentre cards; Per-second billing and scale-to-zero serverless endpoints keep idle costs near zero; Fast environment provisioning from templates or your own containers; Global region coverage with persistent storage and no egress fees

**Limites:** GPU availability for high-end cards can vary by region and time of day; Serverless cold starts and autoscaling behaviour require some tuning to get right; Costs can climb quickly if workloads are left running on idle Pods; Learning curve for container and handler configuration is steeper than fully managed model APIs

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

## Questions fréquentes

### Comment Rivet.dev et RunPod se comparent-ils en termes de trafic mensuel ?

Rivet.dev enregistre 21 359 visites mensuelles, tandis que RunPod enregistre 2 881 043. Les estimations de trafic décrivent la taille de l'audience, pas la qualité du produit.

### Comment leurs taux de croissance se comparent-ils ?

Rivet.dev a un taux de croissance mensuel de -44,3 % ; RunPod a +5,9 %.

### Comment les tarifs se comparent-ils ?

Rivet.dev : Freemium, Tarifs sur demande. 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. RunPod : Payant. Paid, pay-as-you-go. GPU Pods are billed per second or per hour by card type, Serverless endpoints bill for active compute only with zero idle cost, and Clusters charge per GPU per hour. Storage starts at around $0.05/GB per month. A free tier and enterprise reserved-capacity contracts are also available.

## Alternatives

| # | Nom de l'outil | Visites mensuelles | Taux de croissance mensuel | Modèle tarifaire | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [OpenRouter](https://openaitools.app/fr/tool/openrouter-ai) | 19 941 437 | -6,2 % | Payant | Provides a unified API gateway across hundreds of models, but entirely abstracts away underlying GPU infrastructure management. | [.md](https://openaitools.app/fr/tool/openrouter-ai.md) |
| 2 | [fal.ai](https://openaitools.app/fr/tool/fal-ai) | 3 093 684 | -3,7 % | Paid, pay-as-you-go usage-based pricing | Specializes in lightning-fast serverless execution for generative media models, but lacks general-purpose GPU pod rental options. | [.md](https://openaitools.app/fr/tool/fal-ai.md) |
| 3 | [Together AI](https://openaitools.app/fr/tool/together-ai) | 1 645 930 | +64,9 % | Freemium, Payant | Fournit une inférence de modèle sans serveur gérée et des clusters GPU, échangeant la personnalisation brute des pods sur métal nu contre un accès API simplifié. | [.md](https://openaitools.app/fr/tool/together-ai.md) |
| 4 | [Vast.ai](https://openaitools.app/fr/tool/vast-ai) | 1 257 554 | +2,8 % | Payant | Propose un marché de GPU pair-à-pair aux prix souvent plus bas, mais avec une fiabilité matérielle plus variable que RunPod. | [.md](https://openaitools.app/fr/tool/vast-ai.md) |
| 5 | [Modal](https://openaitools.app/fr/tool/modal-com) | 1 196 021 | +30,2 % | Freemium, Tarifs sur demande | Offre une exécution Python sans serveur et une mise à l'échelle instantanée des conteneurs, mais manque de contrôle direct de pod SSH persistant comme RunPod. | [.md](https://openaitools.app/fr/tool/modal-com.md) |
| 6 | [Nebius](https://openaitools.app/fr/tool/nebius) | 1 145 711 | +10,7 % | Payant, Tarifs sur demande | Offre des clusters GPU NVIDIA d'entreprise haute performance, mais se concentre davantage sur l'infrastructure de métal nu dédiée que sur les pods spot flexibles. | [.md](https://openaitools.app/fr/tool/nebius.md) |
| 7 | [Replicate AI](https://openaitools.app/fr/tool/replicate-ai) | 904 038 | -8,4 % | Payant | Offers a polished API and cloud platform for running open models, but provides less direct infrastructure-level control than RunPod. | [.md](https://openaitools.app/fr/tool/replicate-ai.md) |
| 8 | [Salad](https://openaitools.app/fr/tool/salad-gpu-cloud) | 713 519 | +10,4 % | Essai gratuit, Payant, Tarifs sur demande | Utilizes distributed consumer hardware to drastically lower inference costs, but cannot match enterprise GPU availability or SLA guarantees. | [.md](https://openaitools.app/fr/tool/salad-gpu-cloud.md) |
| 9 | [DeepInfra](https://openaitools.app/fr/tool/deep-infra) | 457 810 | -8,9 % | Payant | Fournit une inférence de modèle sans serveur exceptionnellement économique, mais ne fournit pas de location de conteneurs GPU bruts pour les charges de travail d'entraînement personnalisées. | [.md](https://openaitools.app/fr/tool/deep-infra.md) |
| 10 | [Mastra](https://openaitools.app/fr/tool/mastra) | 318 954 | -5 % | Freemium, Tarifs sur demande | Mastra is an open-source TypeScript framework for building, deploying, and observing AI agents and workflows. It gives JavaScript developers typed agents, durable workflows, memory, MCP tool support, and built-in observa | [.md](https://openaitools.app/fr/tool/mastra.md) |

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

More Markdown: [Catégories](https://openaitools.app/fr/categories.md) · [Classements de trafic](https://openaitools.app/fr/rankings.md) · [llms.txt](https://openaitools.app/fr/llms.txt)