--- title: "ollama vs DistiLlama" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ollama-ollama-vs-shreyaskarnik-distillama" tools: ["ollama-ollama", "shreyaskarnik-distillama"] --- # ollama vs DistiLlama *GraphCanon updated Jul 15, 2026* ## Verdict Pick ollama when ollama is primarily Go; DistiLlama is TypeScript; pick DistiLlama when distiLlama is primarily TypeScript; ollama is Go. [ollama](https://ollama.com) reports 176k GitHub stars, 17k forks, and 3.4k open issues, last pushed Jul 10, 2026. [DistiLlama](https://github.com/shreyaskarnik/DistiLlama) has 305 stars, 32 forks, and 9 open issues, last pushed Sep 2, 2024. Figures are from public GitHub metadata via [ollama's repository](https://github.com/ollama/ollama) and [DistiLlama's repository](https://github.com/shreyaskarnik/DistiLlama). | | [ollama](/tools/ollama-ollama.md) | [DistiLlama](/tools/shreyaskarnik-distillama.md) | | --- | --- | --- | | Tagline | Get up and running with various large language models using Ollama. | Chrome Extension to Summarize or Chat with Web Pages/Local Documents Using locally running LLMs. Keep all of your data and conversations private. 🔐 | | Stars | 175,936 | 305 | | Forks | 16,939 | 32 | | Open issues | 3,423 | 9 | | Language | Go | TypeScript | | 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 | Data & Retrieval, Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ollama](/tools/ollama-ollama.md) | [DistiLlama](/tools/shreyaskarnik-distillama.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 1d | 680d | | Open issues (now) | 3.4k | 9 | | Owner type | Organization | User | | Full report | [trust report](/tools/ollama-ollama/trust.md) | [trust report](/tools/shreyaskarnik-distillama/trust.md) | ## 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; DistiLlama is TypeScript. - 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 DistiLlama if… - DistiLlama is primarily TypeScript; ollama is Go. - Tags unique to DistiLlama: chrome-extension, langchain, llama2, local-llm. - Also covers Data & Retrieval. ## 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 DistiLlama - Last GitHub push was 680 days ago (dormant maintenance, Sep 2, 2024). Validate activity before betting a new project on DistiLlama. - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - 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 DistiLlama? ollama: Get up and running with various large language models using Ollama.. DistiLlama: Chrome Extension to Summarize or Chat with Web Pages/Local Documents Using locally running LLMs. Keep all of your data and conversations private. 🔐. See the comparison table for live GitHub stats and shared categories. ### When should I choose ollama over DistiLlama? Choose ollama over DistiLlama when ollama is primarily Go; DistiLlama is TypeScript; 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 DistiLlama over ollama? Choose DistiLlama over ollama when DistiLlama is primarily TypeScript; ollama is Go; Tags unique to DistiLlama: chrome-extension, langchain, llama2, local-llm; Also covers Data & Retrieval. ### 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 DistiLlama? Last GitHub push was 680 days ago (dormant maintenance, Sep 2, 2024). Validate activity before betting a new project on DistiLlama. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. 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 DistiLlama more popular on GitHub? ollama has more GitHub stars (175,936 vs 305). Stars measure visibility, not whether either tool fits your constraints. ### Are ollama and DistiLlama open source? Yes - both are open-source projects on GitHub (ollama: MIT, DistiLlama: MIT). ### Where can I find alternatives to ollama or DistiLlama? GraphCanon lists graph-backed alternatives at [ollama alternatives](/tools/ollama-ollama/alternatives) and [DistiLlama alternatives](/tools/shreyaskarnik-distillama/alternatives) ([ollama markdown twin](/tools/ollama-ollama/alternatives.md), [DistiLlama markdown twin](/tools/shreyaskarnik-distillama/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-shreyaskarnik-distillama.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ollama or DistiLlama? ollama: Very active. DistiLlama: 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 DistiLlama? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ollama trust report](/tools/ollama-ollama/trust); [DistiLlama trust report](/tools/shreyaskarnik-distillama/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/_