# Groq vs Rivet.dev

Groq records 3,987,936 monthly visits with +10% month-over-month growth and Paid pricing. Rivet.dev records 21,359 monthly visits with -44.3% growth and Freemium, Contact for Pricing pricing.

| Metric | [Groq](https://openaitools.app/tool/groq) | [Rivet.dev](https://openaitools.app/tool/rivet-dev) |
| :--- | :--- | :--- |
| Website URL | https://groq.com | https://rivet.dev |
| Categories | AI API, Large Language Models (LLMs), Open Source AI Models | AI Agent, AI Workflow, AI Developer Tools, AI App Builder |
| Pricing Model | Paid | Freemium, Contact for Pricing |
| Monthly Visits | 3,987,936 | 21,359 |
| MoM Growth Rate | +10% | -44.3% |
| Primary Market | India | United States |
| Direct Visits | 1,702,515 | 10,710 |
| Review Score | 4.7 | 4.5 |
| Saved Count | 4 | 0 |
| Supported Platforms | Website | Website |

## Groq

Groq is an AI inference cloud that runs large language models and other AI models at exceptionally low latency. Instead of designing chips for training, Groq built custom silicon called the LPU, now joined by LPX, optimized specifically for inference, the stage where models actually serve users. The company positions itself as a 'neocloud' for fast inference and combines that hardware with a software stack and developer APIs.

Developers access Groq through an API that hosts popular open models such as Llama, Mixtral, Gemma, and Whisper speech models, along with text-to-speech capabilities. Because the platform is tuned for speed, it is often used for real-time chat, agents, and voice interfaces where response time matters. The API is broadly compatible with common OpenAI-style request formats, which lowers the cost of switching.

Groq has scaled aggressively, announcing a $350 million Series A and building hundreds of megawatts of inference capacity. It highlights reliability and cost alongside speed, arguing that fast and affordable no longer need to be a tradeoff for teams running AI workloads in production.

**Pricing & Plans:** Paid, usage-based inference API. Groq charges per token for hosted models, with free developer tiers and enterprise capacity options; check the official pricing page for current rates.

- **LPU and LPX inference hardware:** Custom accelerators designed specifically for inference rather than training, tuned for very low latency.
- **Open model catalog:** Hosted access to popular open models including Llama, Mixtral, Gemma, and Whisper speech models.
- **Fast developer API:** An API broadly compatible with common OpenAI-style request formats for quick integration.
- **Speech and audio models:** Automatic speech recognition with Whisper plus text-to-speech capabilities for voice applications.
- **Scales for production:** Capacity built for high-volume production workloads with an emphasis on reliability and cost.

**Strengths:** Very fast inference latency for real-time applications; Broad catalog of popular open-source models; OpenAI-compatible API reduces migration effort; Managed cloud removes the need to run your own GPUs

**Limitations:** Focus is inference only, not model training; Pricing is usage-based, so costs scale with traffic; Availability and model selection depend on the hosted catalog

[Profile (Markdown)](https://openaitools.app/tool/groq.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 Groq and Rivet.dev compare in monthly traffic?

Groq has 3,987,936 monthly visits, while Rivet.dev has 21,359. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Groq has a month-over-month growth rate of +10%; Rivet.dev has -44.3%.

### How does pricing compare?

Groq: Paid. Paid, usage-based inference API. Groq charges per token for hosted models, with free developer tiers and enterprise capacity options; check the official pricing page for current rates. 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 | [DeepSeek](https://openaitools.app/tool/deepseek) | 372,761,591 | +4.3% | Freemium | High-efficiency open-weight and hosted reasoning AI powered by DeepSeek-V4 and R1 at ultra-low token costs. | [.md](https://openaitools.app/tool/deepseek.md) |
| 2 | [OpenAI Platform](https://openaitools.app/tool/openai) | 234,678,639 | -9.6% | Paid | Proprietary frontier models with powerful reasoning and multimodal features, but lacking open-weight model hosting and custom inference speeds. | [.md](https://openaitools.app/tool/openai.md) |
| 3 | [Google AI Studio](https://openaitools.app/tool/google-ai-studio) | 112,620,020 | +2% | Freemium | Google's rapid prototyping IDE and developer API workbench for building multimodal applications with Gemini models. | [.md](https://openaitools.app/tool/google-ai-studio.md) |
| 4 | [OpenRouter](https://openaitools.app/tool/openrouter-ai) | 19,941,437 | -6.2% | Paid | Unified API gateway aggregating hundreds of models across providers, but acting as a router rather than direct hardware host. | [.md](https://openaitools.app/tool/openrouter-ai.md) |
| 5 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Robust cloud platform for open-source model inference, offering extensive fine-tuning support but slightly slower raw speeds. | [.md](https://openaitools.app/tool/together-ai.md) |
| 6 | [Cerebras](https://openaitools.app/tool/cerebras) | 701,013 | -12.6% | Contact for Pricing | Wafer-scale hardware cloud delivering ultra-fast token generation speeds comparable to Groq, but supporting a more specialized model catalog. | [.md](https://openaitools.app/tool/cerebras.md) |
| 7 | [Fireworks](https://openaitools.app/tool/fireworks-ai) | 659,687 | +6% | Contact for Pricing | High-throughput serverless inference for open models, featuring excellent speed and fine-tuning capabilities with broad API compatibility. | [.md](https://openaitools.app/tool/fireworks-ai.md) |
| 8 | [DeepInfra](https://openaitools.app/tool/deep-infra) | 457,810 | -8.9% | Paid | Low-cost serverless inference cloud hosting hundreds of open-weight models, but lacking specialized custom hardware accelerators like LPUs. | [.md](https://openaitools.app/tool/deep-infra.md) |
| 9 | [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) |
| 10 | [Novita AI](https://openaitools.app/tool/novita-ai) | 271,371 | -10.4% | Paid | AI cloud platform providing serverless model APIs and GPU instances, but with less emphasis on ultra-low-latency text generation. | [.md](https://openaitools.app/tool/novita-ai.md) |

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

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