--- title: "lanarky vs litellm" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ajndkr-lanarky-vs-berriai-litellm" tools: ["ajndkr-lanarky", "berriai-litellm"] --- # lanarky vs litellm *GraphCanon updated Aug 21, 2026* ## Verdict Pick lanarky if lanarky, a deprecated Python-based framework for building LLM microservices with FastAPI, offers streamlined development but comes with caveats related to its deprecated status; pick litellm if litellm is a Python SDK and Proxy Server that facilitates the interaction with over 100 LLM APIs, offering features such as cost tracking, guardrails, load balancing, and logging. [lanarky](https://lanarky.ajndkr.com/) reports 990 GitHub stars, 76 forks, and 10 open issues, last pushed Jul 6, 2024. [litellm](https://docs.litellm.ai/docs/) has 55k stars, 10k forks, and 4.6k open issues, last pushed Aug 1, 2026. Figures are from public GitHub metadata via [lanarky's repository](https://github.com/ajndkr/lanarky) and [litellm's repository](https://github.com/BerriAI/litellm). | | [lanarky](/tools/ajndkr-lanarky.md) | [litellm](/tools/berriai-litellm.md) | | --- | --- | --- | | Tagline | A web framework for building LLM microservices (deprecated) | Python SDK and Proxy Server for calling multiple LLM APIs | | Stars | 990 | 55,221 | | Forks | 76 | 10,231 | | Open issues | 10 | 4,634 | | Language | Python | Python | | Adopt for | Lanarky, a deprecated Python-based framework for building LLM microservices with FastAPI, offers streamlined development but comes with caveats related to its deprecated status. | litellm is a Python SDK and Proxy Server that facilitates the interaction with over 100 LLM APIs, offering features such as cost tracking, guardrails, load balancing, and logging. | | Persona | - | - | | Runtime | - | - | | License | Lanarky is released under the MIT License, allowing free usage, modification, and distribution but with no warranty. | The licensing terms for LiteLLM are provided under a license type categorized as 'Other'; details of the exact license should be referenced directly from its source. | | Categories | Inference & Serving, LLM Frameworks | Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [lanarky](/tools/ajndkr-lanarky.md) | [litellm](/tools/berriai-litellm.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 775d | 0d | | Open issues (now) | 10 | 4.6k | | Stars delta | -2 (30d) | Unknown | | Open issues delta | +1 (30d) | Unknown | | Owner type | User | Organization | | Full report | [trust report](/tools/ajndkr-lanarky/trust.md) | [trust report](/tools/berriai-litellm/trust.md) | **Typed relationship:** lanarky _(integrates with)_ litellm Given that LiteLLM by berriai offers an easy way to interface with multiple LLMs, it can be integrated into lanarky to extend its functionality in terms of multi-LLM support. ## Decision facts: lanarky - **Pricing:** freemium - The library itself is free to use due to its open-source licensing. However, any associated services like OpenAI's `ChatCompletion` may incur costs depending on the service provider’s pricing. - **Requirements:** Min 1 GB RAM; Ensure you have Python and Pip installed to utilize Lanarky.; No Docker installation is required; it works with standard Python environments. - **Adopt for:** Lanarky, a deprecated Python-based framework for building LLM microservices with FastAPI, offers streamlined development but comes with caveats related to its deprecated status. - **License detail:** Lanarky is released under the MIT License, allowing free usage, modification, and distribution but with no warranty. ## Decision facts: litellm - **Pricing:** freemium - While the core functionality is provided free, specific extended features might require a paid plan. - **Requirements:** Requires Docker - **Adopt for:** litellm is a Python SDK and Proxy Server that facilitates the interaction with over 100 LLM APIs, offering features such as cost tracking, guardrails, load balancing, and logging. - **License detail:** The licensing terms for LiteLLM are provided under a license type categorized as 'Other'; details of the exact license should be referenced directly from its source. ## Choose when ### Choose lanarky if… - License: lanarky is MIT, litellm is Other. - Pricing: The library itself is free to use due to its open-source licensing. However, any associated services like OpenAI's `ChatCompletion` may incur costs depending on the service provider’s pricing.. - Requirements: Min 1 GB RAM; Ensure you have Python and Pip installed to utilize Lanarky.; No Docker installation is required; it works with standard Python environments.. - Given that LiteLLM by berriai offers an easy way to interface with multiple LLMs, it can be integrated into lanarky to extend its functionality in terms of multi-LLM support. - Tags unique to lanarky: fastapi, llmops, microservices, python3. - - Use if your project requires specific historical compatibility or knowledge of how Lanarky operated in the past. ### Choose litellm if… - License: litellm is Other, lanarky is MIT. - Pricing: While the core functionality is provided free, specific extended features might require a paid plan.. - Requirements: Requires Docker. - Given that LiteLLM by berriai offers an easy way to interface with multiple LLMs, it can be integrated into lanarky to extend its functionality in terms of multi-LLM support. - Tags unique to litellm: ai-gateway, azure-openai, bedrock, llm. - litellm ships Docker support for self-hosted deployment. - When you need to integrate multiple LLM (Language Learning Modelling) APIs into your application across different providers like Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, Hugging ## When NOT to use lanarky - - Avoid new deployments that rely on active maintenance and updates; opt for actively maintained alternatives like FastAPI directly without Lanarky's now-deprecated layer. - - Do not use if your application needs modern security patches or features, as the deprecated status signifies no further development or support. ## When NOT to use litellm - If your project only requires interaction with a single LLM API and basic functionalities, litellm may be overkill. ## Common questions ### What is the difference between lanarky and litellm? lanarky: A web framework for building LLM microservices (deprecated). litellm: Python SDK and Proxy Server for calling multiple LLM APIs. See the comparison table for live GitHub stats and shared categories. ### When should I choose lanarky over litellm? Choose lanarky over litellm when License: lanarky is MIT, litellm is Other; Pricing: The library itself is free to use due to its open-source licensing. However, any associated services like OpenAI's `ChatCompletion` may incur costs depending on the service provider’s pricing.; Requirements: Min 1 GB RAM; Ensure you have Python and Pip installed to utilize Lanarky.; No Docker installation is required; it works with standard Python environments.; Given that LiteLLM by berriai offers an easy way to interface with multiple LLMs, it can be integrated into lanarky to extend its functionality in terms of multi-LLM support; Tags unique to lanarky: fastapi, llmops, microservices, python3; - Use if your project requires specific historical compatibility or knowledge of how Lanarky operated in the past. ### When should I choose litellm over lanarky? Choose litellm over lanarky when License: litellm is Other, lanarky is MIT; Pricing: While the core functionality is provided free, specific extended features might require a paid plan.; Requirements: Requires Docker; Given that LiteLLM by berriai offers an easy way to interface with multiple LLMs, it can be integrated into lanarky to extend its functionality in terms of multi-LLM support; Tags unique to litellm: ai-gateway, azure-openai, bedrock, llm; litellm ships Docker support for self-hosted deployment; When you need to integrate multiple LLM (Language Learning Modelling) APIs into your application across different providers like Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, Hugging. ### When should I avoid lanarky? - Avoid new deployments that rely on active maintenance and updates; opt for actively maintained alternatives like FastAPI directly without Lanarky's now-deprecated layer. - Do not use if your application needs modern security patches or features, as the deprecated status signifies no further development or support. ### When should I avoid litellm? If your project only requires interaction with a single LLM API and basic functionalities, litellm may be overkill. ### Is lanarky or litellm more popular on GitHub? litellm has more GitHub stars (55,221 vs 990). Stars measure visibility, not whether either tool fits your constraints. ### Are lanarky and litellm open source? Yes - both are open-source projects on GitHub (lanarky: MIT, litellm: Other). ### Where can I find alternatives to lanarky or litellm? GraphCanon lists graph-backed alternatives at [lanarky alternatives](/tools/ajndkr-lanarky/alternatives) and [litellm alternatives](/tools/berriai-litellm/alternatives) ([lanarky markdown twin](/tools/ajndkr-lanarky/alternatives.md), [litellm markdown twin](/tools/berriai-litellm/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/ajndkr-lanarky-vs-berriai-litellm.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, lanarky or litellm? lanarky: Dormant. litellm: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for lanarky and litellm? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [lanarky trust report](/tools/ajndkr-lanarky/trust); [litellm trust report](/tools/berriai-litellm/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ajndkr-lanarky`](/api/graphcanon/graph?tool=ajndkr-lanarky) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_