# Citable vs Groq

Citable records 0 monthly visits with 0% month-over-month growth and Free Trial, Paid pricing. Groq records 3,987,936 monthly visits with +10% growth and Paid pricing.

| Metric | [Citable](https://openaitools.app/tool/citable) | [Groq](https://openaitools.app/tool/groq) |
| :--- | :--- | :--- |
| Website URL | https://citable.xyz | https://groq.com |
| Categories | AI SEO Tools, AI Marketing, AI Monitor, AI Digital Marketing | AI API, Large Language Models (LLMs), Open Source AI Models |
| Pricing Model | Free Trial, Paid | Paid |
| Monthly Visits | 0 | 3,987,936 |
| MoM Growth Rate | 0% | +10% |
| Primary Market | Global | India |
| Direct Visits | 0 | 1,702,515 |
| Review Score | 4 | 4.7 |
| Saved Count | 1 | 4 |
| Supported Platforms | Website | Website |

## Citable

Citable addresses a problem that classic SEO tools were never built for: a growing share of buying questions are now answered inside AI assistants rather than in a page of search results. When someone asks ChatGPT, Perplexity, Gemini, Claude or Grok for a recommendation, the model returns a short answer with a handful of cited sources — and brands that are absent from that answer are effectively invisible, however well they rank on Google.

Citable monitors that layer. It tracks where your brand is mentioned and cited across the major generative engines, records which prompts and topics trigger a mention, and compares your presence with competitors as a share of voice. The platform's tag set also points to breakdowns by audience persona and by geography, which matters for brands whose relevance varies by market or customer segment.

The result is trend reporting that marketing, SEO and brand teams can act on: understanding which content AI systems are actually drawing on, and where a competitor is being recommended instead.

Note: our audit crawler could not reach citable.xyz during this pass, so the details above reflect the product category and its documented focus rather than a freshly verified page. Verify current plan details on the official site before purchase.

**Pricing & Plans:** Citable lists both a free trial and paid plans, according to its directory classification. Our audit could not reach the pricing page during this pass, so specific prices and tier names are not quoted here — check the official site for current figures.

- **AI citation monitoring:** Monitor how often your brand is named or cited in answers from generative engines including ChatGPT, Perplexity, Gemini, Claude and Grok, rather than only in classic search results.
- **Prompt and topic coverage:** See which prompts, topics and questions trigger a mention of your brand, so you can tell where you already appear in AI answers and where you are absent.
- **Competitor share of voice:** Compare your citation volume and presence against named competitors to understand relative share of voice inside AI answers.
- **Persona and geographic targeting:** Break visibility down by audience persona and by geography, so localised or niche-specific gaps in AI recommendations are easier to spot.
- **Reporting and analytics:** Trend reporting over time so marketing and content teams can see whether AI visibility is improving after publishing or optimisation work.

**Strengths:** Targets a genuinely new channel — AI answer engines — rather than repackaging classic rank tracking; Covers multiple engines including ChatGPT, Perplexity, Gemini, Claude and Grok in one view; Competitor share-of-voice reporting makes the abstract idea of AI visibility concrete; Persona and geographic segmentation supports localised and segment-specific content planning

**Limitations:** The site could not be reached during this audit, so current pricing and feature details are unverified; AI answer engines change how and when they cite sources, so visibility metrics can shift for reasons outside your control; Brand monitoring only helps if the resulting insights feed back into content and positioning work; Category coverage is broad and overlaps with other AI-visibility and SEO monitoring tools

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

## 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)

## Frequently Asked Questions

### How do Citable and Groq compare in monthly traffic?

Citable has 0 monthly visits, while Groq has 3,987,936. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Citable has a month-over-month growth rate of 0%; Groq has +10%.

### How does pricing compare?

Citable: Free Trial, Paid. Citable lists both a free trial and paid plans, according to its directory classification. Our audit could not reach the pricing page during this pass, so specific prices and tier names are not quoted here — check the official site for current figures. 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.

## 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 | [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) |
| 10 | [Chutes](https://openaitools.app/tool/chutes) | 250,187 | -15.2% | Paid | Decentralized serverless inference platform hosting open-source models, offering lower costs but less enterprise reliability guarantees. | [.md](https://openaitools.app/tool/chutes.md) |

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

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