# LiteLLM vs OpenLIT

LiteLLM records 576,967 monthly visits with +7.9% month-over-month growth and Freemium, Contact for Pricing pricing. OpenLIT records 6,028 monthly visits with -18.3% growth and Free pricing.

| Metric | [LiteLLM](https://openaitools.app/tool/litellm) | [OpenLIT](https://openaitools.app/tool/openlit) |
| :--- | :--- | :--- |
| Website URL | https://litellm.ai | https://openlit.io |
| Categories | AI API, Large Language Models (LLMs), AI Developer Tools, Open Source AI Models | Large Language Models (LLMs), AI Developer Tools, AI Monitor, Open Source AI Models |
| Pricing Model | Freemium, Contact for Pricing | Free |
| Monthly Visits | 576,967 | 6,028 |
| MoM Growth Rate | +7.9% | -18.3% |
| Primary Market | United States | United States |
| Direct Visits | 228,967 | 2,375 |
| Review Score | 4.8 | 4.7 |
| 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)

## OpenLIT

OpenLIT positions itself as an agent harness engineering platform rather than a single-purpose monitoring tool. The idea is that the model is only one part of a reliable agent; the harness around it — prompts, context, tools, rules, and secrets — is what teams actually need to inspect and fix. OpenLIT brings those pieces together so you can trace what happened, evaluate whether it worked, guard the parts that should not break, and then change the harness without redeploying your application.

Instrumentation is deliberately flexible. Application teams can add an SDK and call openlit.init() to get tracing in-process, while teams that prefer zero-code coverage can use an eBPF-based controller in the Enterprise Edition. For infrastructure visibility there is a GPU collector for NVIDIA, AMD, and Intel cards, and if you already run OpenTelemetry tooling, you can simply point OTLP exporters at your OpenLIT deployment.

Because the project is OpenTelemetry-native and Apache 2.0 licensed, the data path stays portable. Traces and metrics can live in the OpenLIT UI and its ClickHouse-backed store, or be exported to Grafana, Datadog, or any OTLP backend. Storage is built on ClickHouse to keep queries fast across high-volume LLM and agent telemetry, and the whole stack can be self-hosted with Docker Compose or Kubernetes.

**Pricing & Plans:** The open-source edition is the free tier and is licensed under Apache 2.0, covering agent observability, evaluations, guardrails, Prompt Hub, Vault, OpenGround, coding-agent monitoring, and GPU metrics. There is no charge to self-host and no license key required. OpenLIT Cloud is not generally available yet. A separate Enterprise Edition adds capabilities such as the zero-code eBPF controller; check the official pricing page for current enterprise terms.

- **LLM and agent tracing:** Capture OpenTelemetry traces and metrics for every LLM call, tool invocation, retrieval, and agent step, and filter them by user, session, cost, latency, or custom metadata.
- **Evaluations on real traffic:** Score production traffic or experiments with LLM-as-a-judge, heuristic checks, or human review so you can measure accuracy, relevance, and safety over time.
- **Prompt Hub and versioning:** Manage and version prompts in Prompt Hub, then deploy, roll back, and update prompts without shipping new application code.
- **Vault for API keys:** Store and rotate OpenAI, Anthropic, and other LLM API keys outside your codebase with an encrypted, rotating secrets vault.
- **Cost, latency, and GPU monitoring:** Track spend, latency, and quality across AI workloads, and monitor GPU utilization, memory, temperature, and power for NVIDIA, AMD, and Intel hardware.

**Strengths:** OpenTelemetry-native design keeps traces and metrics portable and avoids vendor lock-in; Broad free open-source edition under Apache 2.0 with unlimited self-hosted use; Covers tracing, evals, guardrails, prompts, secrets, cost, and GPU monitoring in one platform; 56+ integrations across LLMs, agent frameworks, and vector databases, plus OTLP ingest from other tools

**Limitations:** Requires you to run and maintain your own ClickHouse and UI deployment to use the open-source edition; OpenLIT Cloud is not generally available, so there is no hosted option for teams that do not want to self-host; Some capabilities like the zero-code eBPF controller are tied to the Enterprise Edition; Feature surface is broad, so new users may need time to navigate the many modules

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

## Frequently Asked Questions

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

LiteLLM has 576,967 monthly visits, while OpenLIT has 6,028. 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%; OpenLIT has -18.3%.

### 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. OpenLIT: Free. The open-source edition is the free tier and is licensed under Apache 2.0, covering agent observability, evaluations, guardrails, Prompt Hub, Vault, OpenGround, coding-agent monitoring, and GPU metrics. There is no charge to self-host and no license key required. OpenLIT Cloud is not generally available yet. A separate Enterprise Edition adds capabilities such as the zero-code eBPF controller; check the official pricing page for current enterprise terms.

## 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 | [Ollama](https://openaitools.app/tool/ollama) | 9,421,973 | +4.3% | Free, Freemium, Paid | Run and build with open AI models locally or in the cloud | [.md](https://openaitools.app/tool/ollama.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 | [Arize AI](https://openaitools.app/tool/arize-com) | 249,028 | +3.2% | Paid, Contact for Pricing | Agent observability, evaluation, and continuous improvement for production AI | [.md](https://openaitools.app/tool/arize-com.md) |
| 7 | [Portkey](https://openaitools.app/tool/portkey-ai) | 195,650 | -9.4% | Freemium, Paid, Contact for Pricing | AI gateway, observability and guardrails for production LLM apps | [.md](https://openaitools.app/tool/portkey-ai.md) |
| 8 | [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) |
| 9 | [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) |
| 10 | [Future AGI](https://openaitools.app/tool/future-agi) | 121,741 | -7.8% | Freemium, Usage-based | Build, simulate, evaluate and monitor self-improving AI agents | [.md](https://openaitools.app/tool/future-agi.md) |

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

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