# Groq vs OpenFlowKit Groq records 3,987,936 monthly visits with +10% month-over-month growth and Paid pricing. OpenFlowKit records 1,437 monthly visits with -70.3% growth and Free pricing. | Metric | [Groq](https://openaitools.app/tool/groq) | [OpenFlowKit](https://openaitools.app/tool/openflowkit) | | :--- | :--- | :--- | | Website URL | https://groq.com | https://openflowkit.com | | Categories | AI API, Large Language Models (LLMs), Open Source AI Models | AI Diagram Generator, AI Assistant, AI Code Assistant, Open Source AI Models | | Pricing Model | Paid | Free | | Monthly Visits | 3,987,936 | 1,437 | | MoM Growth Rate | +10% | -70.3% | | Primary Market | India | Vietnam | | Direct Visits | 1,702,515 | 614 | | Review Score | 4.7 | 4.6 | | 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) ## OpenFlowKit OpenFlowKit is an open-source diagramming studio built for engineers who think in systems. It supports three ways of working on one canvas: freehand drawing with shapes, connectors, ink, images and charts; writing the diagram as code in Mermaid, D2 or Structurizr; or letting an AI agent build and edit it live through the Model Context Protocol. Text and canvas stay in sync, so you can start with a snippet and finish with something visual. A standout v2 feature maps a public GitHub repository directly in the browser: paste an owner/repo URL and OpenFlowKit reads the files, produces boxes and connections, and cites each arrow back to the exact line of code it came from. Private repositories can be mapped locally through the CLI. The result is architecture documentation that reflects the code rather than someone's memory of it. OpenFlowKit is also practical for day-to-day diagramming: a toolset of 29 MCP tools for agents, C4 context/container/component views that stay connected to one underlying model, automatic matching of 2,000+ cloud and developer icons by node label, animated SVG/GIF/MP4 export, share links and self-hosting. It is MIT licensed, runs locally by default and needs no account. **Pricing & Plans:** Free and open source under the MIT licence. There is no paid tier on the site; you can start creating without signing up, and the code can be self-hosted. - **Repo-to-map generation:** Paste a public GitHub repository and OpenFlowKit reads its files in the browser to draw modules and connections, with every arrow cited to the source line it came from. - **Agent-native canvas over MCP:** 29 diagram tools for Claude Code, Codex, Cursor, VS Code, Windsurf or any MCP client, so an agent can draw on the diagram you have open, one undo away. - **Diagram as code:** Write or paste Mermaid, D2 or Structurizr; the text and the canvas remain the same diagram, so you can round-trip between syntax and visuals. - **Connected C4 model views:** Move from system context to containers to components in linked views that all stay grounded in a single architecture model. - **Icon matching and motion export:** Label a node 'PostgreSQL' or 'Kubernetes' and the right icon is matched automatically from 2,000+ cloud and developer icons; export animated SVG, GIF, MP4 or WebM for living documentation. **Strengths:** Free, MIT-licensed and local-first with no account required; Unique repo-to-diagram mapping that cites each connection back to code; Works equally well for hand drawing, diagram-as-code and AI-agent workflows; Strong ecosystem coverage with automatic matching of 2,000+ cloud and developer icons **Limitations:** No hosted paid support or managed cloud option is advertised, so teams self-host; Advanced MCP and CLI repo mapping assumes comfort with developer tooling; C4 model depth and multiple views can feel heavy for quick one-off sketches [Profile (Markdown)](https://openaitools.app/tool/openflowkit.md) ## Frequently Asked Questions ### How do Groq and OpenFlowKit compare in monthly traffic? Groq has 3,987,936 monthly visits, while OpenFlowKit has 1,437. Traffic estimates describe audience size, not product quality. ### How do their growth rates compare? Groq has a month-over-month growth rate of +10%; OpenFlowKit has -70.3%. ### 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. OpenFlowKit: Free. Free and open source under the MIT licence. There is no paid tier on the site; you can start creating without signing up, and the code can be self-hosted. ## 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 | [Eraser](https://openaitools.app/tool/eraser) | 534,396 | -23.6% | Freemium, Paid, Contact for Pricing | AI diagrams and technical design docs built from your code and systems | [.md](https://openaitools.app/tool/eraser.md) | | 9 | [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) | | 10 | [Edraw Software](https://openaitools.app/tool/edraw-software) | 436,337 | -2.8% | Freemium, Free Trial | AI diagramming, mind mapping and project tools with 50,000+ templates | [.md](https://openaitools.app/tool/edraw-software.md) | --- Source: https://openaitools.app/compare/groq-vs-openflowkit More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)