# LiteLLM vs Monkt

LiteLLM records 576,967 monthly visits with +7.9% month-over-month growth and Freemium, Contact for Pricing pricing. Monkt records 51,826 monthly visits with +47.4% growth and Paid pricing.

| Metric | [LiteLLM](https://openaitools.app/tool/litellm) | [Monkt](https://openaitools.app/tool/monkt) |
| :--- | :--- | :--- |
| Website URL | https://litellm.ai | https://monkt.com |
| Categories | AI API, Large Language Models (LLMs), AI Developer Tools, Open Source AI Models | AI Document Extraction, AI API, AI PDF, Large Language Models (LLMs) |
| Pricing Model | Freemium, Contact for Pricing | Paid |
| Monthly Visits | 576,967 | 51,826 |
| MoM Growth Rate | +7.9% | +47.4% |
| Primary Market | United States | United States |
| Direct Visits | 228,967 | 20,730 |
| Review Score | 4.8 | 4.3 |
| Saved Count | 5 | 0 |
| Supported Platforms | Website | Website |

## 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)

## Monkt

Monkt solves a very specific problem in the AI stack: getting messy documents into a format a language model can actually use. Instead of scanning and copying, you upload files or hand it URLs and receive standardized Markdown with formatting and structure preserved, or JSON shaped by a schema you define. It handles PDF, Word, PowerPoint, Excel, CSV and HTML, reads images and scanned pages through OCR, and can describe visual content as text so figures inside documents survive the conversion.

Beyond plain conversion, the platform markets itself as a way to build intelligent applications on top of your own content. Structured output plugs into custom chatbots, semantic knowledge bases, document intelligence workflows and model fine-tuning datasets. A REST API means the same pipeline can be run programmatically and at scale, and batch processing lets you clear an entire backlog of documents in one pass — the company reports over a million documents processed across thousands of users.

Pricing is deliberately simple: a low-cost individual plan, a professional plan that adds DeepExtract processing, OCR for scanned documents and longer data persistence, and an enterprise tier with GPU inference, layout and reading-order understanding, custom integration support and an extended context window. A separate premium service covers managed bulk processing, intelligent chunking, vectorization and RAG-optimized data preparation for teams that would rather buy the pipeline than build it.

**Pricing & Plans:** Paid, subscription-based with a per-request premium service. The Start plan is $4.99/month for 50 transformations, files up to 15 MB and 7 days of data persistence. Pro is $14.99/month for 1,000 transformations, files up to 25 MB, 30 days of persistence, DeepExtract processing, OCR and page screenshots for multi-page PDFs. Enterprise is custom pricing for unlimited persistence, GPU inference and layout/table understanding. A Premium managed tier is quoted per request for bulk processing, chunking and vectorization. A transformation counts as one conversion to Markdown, JSON, DeepExtract or OCR, and cached results do not consume quota.

- **Markdown and JSON output:** Convert documents to clean, LLM-friendly Markdown or to JSON shaped by automated detection or a custom schema you define.
- **Wide format support:** Handles PDF, Word, PowerPoint, Excel, CSV, images and web pages or raw HTML, preserving document structure and formatting.
- **OCR and image understanding:** Extract text from scanned documents and turn images and figures inside documents into descriptive text and structured data.
- **REST API and batch processing:** Run conversions programmatically and process multiple documents at once to scale dataset preparation and pipeline automation.
- **DeepExtract and enterprise processing:** Higher tiers add advanced extraction, page layout, reading order and table structure understanding plus GPU-accelerated inference.

**Strengths:** Purpose-built for LLM and RAG workflows rather than general document editing; Markdown plus custom JSON schema covers both reading and extraction needs; OCR and image understanding rescue scanned files and embedded figures; REST API and batch processing make large-volume conversion practical

**Limitations:** Pricing is metered by transformations, so very large corpora need planning; File size caps on lower tiers (15–25 MB per file) can block big documents; Advanced features such as layout and table understanding sit behind the enterprise tier

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

## Frequently Asked Questions

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

LiteLLM has 576,967 monthly visits, while Monkt has 51,826. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

LiteLLM has a month-over-month growth rate of +7.9%; Monkt has +47.4%.

### How does pricing compare?

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. Monkt: Paid. Paid, subscription-based with a per-request premium service. The Start plan is $4.99/month for 50 transformations, files up to 15 MB and 7 days of data persistence. Pro is $14.99/month for 1,000 transformations, files up to 25 MB, 30 days of persistence, DeepExtract processing, OCR and page screenshots for multi-page PDFs. Enterprise is custom pricing for unlimited persistence, GPU inference and layout/table understanding. A Premium managed tier is quoted per request for bulk processing, chunking and vectorization. A transformation counts as one conversion to Markdown, JSON, DeepExtract or OCR, and cached results do not consume quota.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [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) |
| 2 | [Firecrawl](https://openaitools.app/tool/firecrawl-dev) | 1,828,239 | -1.9% | Freemium, Contact for Pricing | Web data API that turns any site into clean, AI-ready content | [.md](https://openaitools.app/tool/firecrawl-dev.md) |
| 3 | [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) |
| 4 | [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) |
| 5 | [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) |
| 6 | [LlamaIndex](https://openaitools.app/tool/llamaindex) | 387,910 | +19.9% | Freemium, Contact for Pricing | Turn any document into AI-ready context with agentic parsing and extraction | [.md](https://openaitools.app/tool/llamaindex.md) |
| 7 | [Jina AI](https://openaitools.app/tool/jina-ai) | 280,782 | -16.5% | Freemium, Paid | Search foundation built from embeddings, rerankers, and reader APIs | [.md](https://openaitools.app/tool/jina-ai.md) |
| 8 | [Portkey](https://openaitools.app/tool/portkey-ai) | 195,650 | -9.4% | Freemium, Paid, Contact for Pricing | Offers advanced enterprise observability and guardrail tools, but lacks LiteLLM's lightweight self-hosted proxy simplicity. | [.md](https://openaitools.app/tool/portkey-ai.md) |
| 9 | [Eden AI](https://openaitools.app/tool/eden-ai) | 173,828 | +6.5% | Paid, Contact for Pricing | Provides managed multi-provider AI routing and cost tracking, but lacks the native open-source flexibility of LiteLLM. | [.md](https://openaitools.app/tool/eden-ai.md) |
| 10 | [LLM Gateway](https://openaitools.app/tool/llm-gateway) | 168,426 | -14.5% | Freemium, Contact for Pricing | An open-source alternative for unifying LLM providers, but features a less extensive ecosystem of middleware integrations. | [.md](https://openaitools.app/tool/llm-gateway.md) |

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

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