--- title: "ollama vs MGDebugger" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ollama-ollama-vs-yerbapage-mgdebugger" tools: ["ollama-ollama", "yerbapage-mgdebugger"] --- # ollama vs MGDebugger *GraphCanon updated Jul 11, 2026* ## Verdict Pick ollama when ollama is primarily Go; MGDebugger is Python; pick MGDebugger when mGDebugger is primarily Python; ollama is Go. [ollama](https://ollama.com) reports 176k GitHub stars, 17k forks, and 3.4k open issues, last pushed Jul 10, 2026. [MGDebugger](https://github.com/YerbaPage/MGDebugger) has 100 stars, 10 forks, and 0 open issues, last pushed Jul 6, 2025. Figures are from public GitHub metadata via [ollama's repository](https://github.com/ollama/ollama) and [MGDebugger's repository](https://github.com/YerbaPage/MGDebugger). | | [ollama](/tools/ollama-ollama.md) | [MGDebugger](/tools/yerbapage-mgdebugger.md) | | --- | --- | --- | | Tagline | Get up and running with various large language models using Ollama. | Multi-Granularity LLM Debugger [ICSE2026] | | Stars | 175,936 | 100 | | Forks | 16,939 | 10 | | Open issues | 3,423 | 0 | | Language | Go | Python | | 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 | - | | Persona | - | - | | Runtime | - | - | | License | MIT license - permissive open-source licensing that allows for broad use of the tool. | MIT | | Categories | Inference & Serving, LLM Frameworks | Computer Vision, Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ollama](/tools/ollama-ollama.md) | [MGDebugger](/tools/yerbapage-mgdebugger.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 1d | 370d | | Open issues (now) | 3.4k | 0 | | Owner type | Organization | User | | Security scan | 52 low (52 low) | 111 low (111 low) | | Full report | [trust report](/tools/ollama-ollama/trust.md) | [trust report](/tools/yerbapage-mgdebugger/trust.md) | ## Shared compatibility - **Python**: [ollama](/tools/ollama-ollama.md) - Python runtime; [MGDebugger](/tools/yerbapage-mgdebugger.md) - Python runtime ## 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 ollama if… - ollama is primarily Go; MGDebugger 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 ### Choose MGDebugger if… - MGDebugger is primarily Python; ollama is Go. - Tags unique to MGDebugger: automatic-program-repair, code-generation, debugger, large-language-models. - Also covers Computer Vision. ## 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. ## When NOT to use MGDebugger - Last GitHub push was 371 days ago (dormant maintenance, Jul 6, 2025). Validate activity before betting a new project on MGDebugger. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between ollama and MGDebugger? ollama: Get up and running with various large language models using Ollama.. MGDebugger: Multi-Granularity LLM Debugger [ICSE2026]. See the comparison table for live GitHub stats and shared categories. ### When should I choose ollama over MGDebugger? Choose ollama over MGDebugger when ollama is primarily Go; MGDebugger 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 choose MGDebugger over ollama? Choose MGDebugger over ollama when MGDebugger is primarily Python; ollama is Go; Tags unique to MGDebugger: automatic-program-repair, code-generation, debugger, large-language-models; Also covers Computer Vision. ### 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. ### When should I avoid MGDebugger? Last GitHub push was 371 days ago (dormant maintenance, Jul 6, 2025). Validate activity before betting a new project on MGDebugger. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is ollama or MGDebugger more popular on GitHub? ollama has more GitHub stars (175,936 vs 100). Stars measure visibility, not whether either tool fits your constraints. ### Are ollama and MGDebugger open source? Yes - both are open-source projects on GitHub (ollama: MIT, MGDebugger: MIT). ### Where can I find alternatives to ollama or MGDebugger? GraphCanon lists graph-backed alternatives at [ollama alternatives](/tools/ollama-ollama/alternatives) and [MGDebugger alternatives](/tools/yerbapage-mgdebugger/alternatives) ([ollama markdown twin](/tools/ollama-ollama/alternatives.md), [MGDebugger markdown twin](/tools/yerbapage-mgdebugger/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/ollama-ollama-vs-yerbapage-mgdebugger.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ollama or MGDebugger? ollama: Very active. MGDebugger: Dormant. 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 ollama and MGDebugger? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ollama trust report](/tools/ollama-ollama/trust); [MGDebugger trust report](/tools/yerbapage-mgdebugger/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ollama-ollama`](/api/graphcanon/graph?tool=ollama-ollama) - 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/_