# Groq vs LiteLLM

Groq records 3,987,936 monthly visits with +10% month-over-month growth and Paid pricing. LiteLLM records 576,967 monthly visits with +7.9% growth and Freemium, Contact for Pricing pricing.

| Metric | [Groq](https://openaitools.app/tool/groq) | [LiteLLM](https://openaitools.app/tool/litellm) |
| :--- | :--- | :--- |
| Website URL | https://groq.com | https://litellm.ai |
| Categories | AI API, Large Language Models (LLMs), Open Source AI Models | AI API, Large Language Models (LLMs), AI Developer Tools, Open Source AI Models |
| Pricing Model | Paid | Freemium, Contact for Pricing |
| Monthly Visits | 3,987,936 | 576,967 |
| MoM Growth Rate | +10% | +7.9% |
| Primary Market | India | United States |
| Direct Visits | 1,702,515 | 228,967 |
| Review Score | 4.7 | 4.8 |
| Saved Count | 4 | 5 |
| 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)

## LiteLLM

LiteLLM is an open-source AI gateway and Python SDK designed to remove vendor lock-in from LLM applications. The SDK lets you call models from OpenAI, Anthropic, Google Vertex AI, Bedrock, Mistral, Azure and dozens of other providers using the same OpenAI-style request format, so switching models is a configuration change rather than a code rewrite. The same project ships an AI Gateway (often called the proxy) that turns that abstraction into a shared service for an entire organization.

That gateway is where most platform teams find the value. It issues virtual keys scoped by team, project or application, tracks spend per key against budgets, applies rate limits (TPM and RPM), and exposes dashboards for request volume, token usage and cost per model. Routing features include load balancing across deployments, automatic fallbacks when a provider fails, retries and budget-based rerouting, plus guardrails for PII masking, prompt-injection detection and secret detection.

The project is genuinely open source with the code on GitHub (BerriAI/litellm) and a very active community. Enterprise features add SSO, audit logs, and support for agents and MCP servers through the same gateway. Notably, LiteLLM supports day-zero access to new models so teams can adopt them as soon as they ship, and it can also serve self-hosted, fine-tuned and internal models behind the same key. Companies cited on the site include NVIDIA, Netflix, Okta, Lemonade and AT&T.

**Pricing & Plans:** Freemium and open source. The self-hosted LiteLLM gateway and SDK are free under an open-source licence, and a free tier lets you get started immediately. Enterprise plans with SSO, audit logs, SLAs and advanced support are quoted on request via the sales team.

- **OpenAI-compatible API for 100+ LLMs:** Call 100+ providers and 1,800+ models using one request format, so you can swap models without changing application code.
- **Virtual keys, teams and budgets:** Issue scoped keys per team, project or app, set monthly spend caps and see exactly who is driving usage and cost.
- **Routing, load balancing and fallbacks:** Distribute traffic across deployments, retry on failure and automatically fall back to another model or provider when one goes down.
- **Observability and spend tracking:** Dashboards for request volume, tokens and cost per model, with support for logging and analytics integrations.
- **Guardrails and policy controls:** Plug in PII masking, prompt-injection detection and secret-detection guardrails, and manage policies centrally instead of in every app.

**Strengths:** Truly open source with a large GitHub community and self-hosting option; Very broad provider coverage with an OpenAI-compatible interface; Enterprise-grade controls: virtual keys, budgets, rate limits and audit logs; Day-zero support for new models and easy fallback when providers fail

**Limitations:** Self-hosting means you own deployment, upgrades and uptime; Feature depth varies between the free open-source version and enterprise plan; The breadth of configuration options can be overwhelming for small projects

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

## Frequently Asked Questions

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

Groq has 3,987,936 monthly visits, while LiteLLM has 576,967. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Groq has a month-over-month growth rate of +10%; LiteLLM has +7.9%.

### 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. LiteLLM: Freemium, Contact for Pricing. Freemium and open source. The self-hosted LiteLLM gateway and SDK are free under an open-source licence, and a free tier lets you get started immediately. Enterprise plans with SSO, audit logs, SLAs and advanced support are quoted on request via the sales team.

## 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 | Provides a massive hosted model catalog with instant access, but requires trusting a third-party platform instead of self-hosting. | [.md](https://openaitools.app/tool/openrouter-ai.md) |
| 5 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Hosts high-performance open-weight models directly on dedicated serverless infrastructure, but does not route across external providers. | [.md](https://openaitools.app/tool/together-ai.md) |
| 6 | [OrcaRouter](https://openaitools.app/tool/orcarouter) | 975,300 | -5.2% | Freemium | Delivers automated model failover and budget governance through an API gateway, but with less open-source customization. | [.md](https://openaitools.app/tool/orcarouter.md) |
| 7 | [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) |
| 8 | [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) |
| 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 | [ZenMux](https://openaitools.app/tool/zenmux) | 444,394 | +16.7% | Freemium, Paid | Unified LLM gateway with failover and analytics, but offers less robust open-source developer SDK support. | [.md](https://openaitools.app/tool/zenmux.md) |

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

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