# Groq vs Charm (Mods)

Groq records 3,987,936 monthly visits with +10% month-over-month growth and Paid pricing. Charm (Mods) records 286 monthly visits with 0% growth and Free pricing.

| Metric | [Groq](https://openaitools.app/tool/groq) | [Charm (Mods)](https://openaitools.app/tool/mods) |
| :--- | :--- | :--- |
| Website URL | https://groq.com | https://charm.sh |
| Categories | AI API, Large Language Models (LLMs), Open Source AI Models | AI Developer Tools, Large Language Models (LLMs), AI Code Assistant, No-Code&Low-Code |
| Pricing Model | Paid | Free |
| Monthly Visits | 3,987,936 | 286 |
| MoM Growth Rate | +10% | 0% |
| Primary Market | India | Global |
| Direct Visits | 1,702,515 | 112 |
| Review Score | 4.7 | 4.8 |
| 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)

## Charm (Mods)

Charm started as a library vendor for developers who care about how the terminal feels. Its component stack — Bubble Tea for interface architecture, Lip Gloss for styling and layout, Huh for forms, Bubbles for widgets, Wish for SSH apps, Glamour for markdown rendering, and Harmonica for physics-based animation — is the foundation many people use to build modern TUIs in Go. Standalone utilities such as gum, glow, vhs, skate, and Pop round out the set, covering shell scripting, markdown reading, terminal GIF recording, key-value storage, and command-line email.

More recently the company expanded in two directions. Crush is its AI coding agent, designed to wire your existing tools, code, and workflows into the language model of your choosing, and it ships for macOS, Linux, Windows, and BSD. Hyper is the infrastructure side: coding-optimized, high-availability, cost-efficient inference with a platform to run it, aimed at teams that want to power CLI-based AI products without building the serving layer themselves.

Charm is also known for its open-source commitment — the company states that its own work is open-sourced, and it claims its technology appears in over 40,000 applications, from community projects to business-critical infrastructure. Operations are fully distributed across the United States, Germany, Brazil, Georgia, and Egypt, and the company maintains blog, alpha/beta access, and Discord channels for the community.

**Pricing & Plans:** The libraries and many utilities are free and open source. Crush is available to download, and Hyper is a commercial inference platform — the site directs teams to get in touch for pricing rather than publishing tiers.

- **Crush AI coding agent:** A terminal-based coding agent that connects your tools, code, and workflows to the LLM of your choice, available on macOS, Linux, Windows, and BSD.
- **Bubble Tea and TUI libraries:** The Go framework behind a large share of modern terminal interfaces, complemented by Lip Gloss for styling, Huh for forms, Bubbles for widgets, and Wish for SSH apps.
- **Standalone CLI utilities:** Small, focused tools including gum for shell scripts, glow for markdown, vhs for terminal GIFs, skate for key-value storage, and Pop for command-line email.
- **Hyper inference platform:** Coding-optimized, high-availability, cost-efficient hosting for open-source models, with a platform layer for production CLI workloads.
- **Open source by default:** The ecosystem is built on open-source technology and the company open-sources its own work, with public repos, a blog, and a Discord community.

**Strengths:** Deep, battle-tested open-source ecosystem with adoption across tens of thousands of applications; Consistent design philosophy that treats terminal UX as a first-class concern; Spans both developer libraries and a commercial inference platform for production use

**Limitations:** Go-centric stack, so it is less applicable if you build in another language; Hyper pricing is quote-based rather than publicly listed; Documentation is spread across many separate project sites

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

## Frequently Asked Questions

### How do Groq and Charm (Mods) compare in monthly traffic?

Groq has 3,987,936 monthly visits, while Charm (Mods) has 286. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Groq has a month-over-month growth rate of +10%; Charm (Mods) has 0%.

### 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. Charm (Mods): Free. The libraries and many utilities are free and open source. Crush is available to download, and Hyper is a commercial inference platform — the site directs teams to get in touch for pricing rather than publishing tiers.

## 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 | [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) |
| 6 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Together AI is the AI Native Cloud — a full-stack platform for running, fine-tuning and training open-source models. It spans serverless inference APIs, dedicated endpoints, GPU clusters, post-training and storage, all b | [.md](https://openaitools.app/tool/together-ai.md) |
| 7 | [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) |
| 8 | [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) |
| 9 | [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) |
| 10 | [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) |

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Source: https://openaitools.app/compare/groq-vs-mods

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