--- title: "lanarky vs ollama" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ajndkr-lanarky-vs-ollama-ollama" tools: ["ajndkr-lanarky", "ollama-ollama"] --- # lanarky vs ollama *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 ollama if ollama is a Go-based platform that provides tools for deploying and managing large language models (LLMs) like Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma using docker images, package managers, cloud and. [lanarky](https://lanarky.ajndkr.com/) reports 990 GitHub stars, 76 forks, and 10 open issues, last pushed Jul 6, 2024. [ollama](https://ollama.com) has 178k stars, 17k forks, and 3.6k open issues, last pushed Jul 31, 2026. Figures are from public GitHub metadata via [lanarky's repository](https://github.com/ajndkr/lanarky) and [ollama's repository](https://github.com/ollama/ollama). | | [lanarky](/tools/ajndkr-lanarky.md) | [ollama](/tools/ollama-ollama.md) | | --- | --- | --- | | Tagline | A web framework for building LLM microservices (deprecated) | Get up and running with various large language models using Ollama. | | Stars | 990 | 177,524 | | Forks | 76 | 17,229 | | Open issues | 10 | 3,583 | | Language | Python | Go | | 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. | Ollama is a Go-based platform that provides tools for deploying and managing large language models (LLMs) like Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma using docker images, package managers, cloud and | | Persona | - | - | | Runtime | - | - | | License | Lanarky is released under the MIT License, allowing free usage, modification, and distribution but with no warranty. | MIT license - permissive open-source licensing that allows for broad use of the tool. | | 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) | [ollama](/tools/ollama-ollama.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 775d | 1d | | Open issues (now) | 10 | 3.6k | | 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/ollama-ollama/trust.md) | ## Shared compatibility - **Python**: [lanarky](/tools/ajndkr-lanarky.md) - Python runtime; [ollama](/tools/ollama-ollama.md) - Python runtime ## 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: ollama - **Hosting:** self hosted - Ollama supports self-hosted and cloud-deployable models using Docker, Helm charts, and various package managers. - **Adopt for:** Ollama is a Go-based platform that provides tools for deploying and managing large language models (LLMs) like Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma using docker images, package managers, cloud and - **License detail:** MIT license - permissive open-source licensing that allows for broad use of the tool. ## Choose when ### Choose lanarky if… - lanarky is primarily Python; ollama is Go. - 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.. - 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 ollama if… - ollama is primarily Go; lanarky is Python. - Ollama supports self-hosted and cloud-deployable models using Docker, Helm charts, and various package managers. - Tags unique to ollama: deepseek, gemma, glm, go. - ollama ships Docker support for self-hosted deployment. - Use Ollama when you require a multi-model platform supporting several large language models such as Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and intend to deploy in various cloud or ## 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 ollama - Avoid using Ollama if you are only interested in a single LLM deployment and seek simplified, model-specific solutions with tailored support rather than a comprehensive multi-model platform. ## Common questions ### What is the difference between lanarky and ollama? lanarky: A web framework for building LLM microservices (deprecated). ollama: Get up and running with various large language models using Ollama.. See the comparison table for live GitHub stats and shared categories. ### When should I choose lanarky over ollama? Choose lanarky over ollama when lanarky is primarily Python; ollama is Go; 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.; 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 ollama over lanarky? Choose ollama over lanarky when ollama is primarily Go; lanarky is Python; Ollama supports self-hosted and cloud-deployable models using Docker, Helm charts, and various package managers; Tags unique to ollama: deepseek, gemma, glm, go; ollama ships Docker support for self-hosted deployment; Use Ollama when you require a multi-model platform supporting several large language models such as Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and intend to deploy in various cloud or. ### 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 ollama? Avoid using Ollama if you are only interested in a single LLM deployment and seek simplified, model-specific solutions with tailored support rather than a comprehensive multi-model platform. ### Is lanarky or ollama more popular on GitHub? ollama has more GitHub stars (177,524 vs 990). Stars measure visibility, not whether either tool fits your constraints. ### Are lanarky and ollama open source? Yes - both are open-source projects on GitHub (lanarky: MIT, ollama: MIT). ### Where can I find alternatives to lanarky or ollama? GraphCanon lists graph-backed alternatives at [lanarky alternatives](/tools/ajndkr-lanarky/alternatives) and [ollama alternatives](/tools/ollama-ollama/alternatives) ([lanarky markdown twin](/tools/ajndkr-lanarky/alternatives.md), [ollama markdown twin](/tools/ollama-ollama/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-ollama-ollama.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, lanarky or ollama? lanarky: Dormant. ollama: 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 ollama? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [lanarky trust report](/tools/ajndkr-lanarky/trust); [ollama trust report](/tools/ollama-ollama/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/_