--- title: "guidance vs ollama" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/guidance-ai-guidance-vs-ollama-ollama" tools: ["guidance-ai-guidance", "ollama-ollama"] --- # guidance vs ollama *GraphCanon updated Jul 11, 2026* ## Verdict Pick guidance if guidance is a specialized tool written in Jupyter Notebooks that provides a unique language to control large language models (LLMs) across multiple backends such as Transformers, llama.cpp, and OpenAI. It's open-source,轻; 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. [guidance](https://github.com/guidance-ai/guidance) reports 22k GitHub stars, 1.2k forks, and 303 open issues, last pushed May 21, 2026. [ollama](https://ollama.com) has 176k stars, 17k forks, and 3.4k open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [guidance's repository](https://github.com/guidance-ai/guidance) and [ollama's repository](https://github.com/ollama/ollama). | | [guidance](/tools/guidance-ai-guidance.md) | [ollama](/tools/ollama-ollama.md) | | --- | --- | --- | | Tagline | A guidance language for controlling large language models. | Get up and running with various large language models using Ollama. | | Stars | 21,656 | 175,936 | | Forks | 1,190 | 16,939 | | Open issues | 303 | 3,423 | | Language | Jupyter Notebook | Go | | Adopt for | Guidance is a specialized tool written in Jupyter Notebooks that provides a unique language to control large language models (LLMs) across multiple backends such as Transformers, llama.cpp, and OpenAI. It's open-source,轻 | 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 | 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._ | | [guidance](/tools/guidance-ai-guidance.md) | [ollama](/tools/ollama-ollama.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 50d | 1d | | Open issues (now) | 303 | 3.4k | | Security scan | No lockfile | 52 low (52 low) | | Full report | [trust report](/tools/guidance-ai-guidance/trust.md) | [trust report](/tools/ollama-ollama/trust.md) | ## Shared compatibility - **Python**: [guidance](/tools/guidance-ai-guidance.md) - Python runtime; [ollama](/tools/ollama-ollama.md) - Python runtime ## Decision facts: guidance - **Adopt for:** Guidance is a specialized tool written in Jupyter Notebooks that provides a unique language to control large language models (LLMs) across multiple backends such as Transformers, llama.cpp, and OpenAI. It's open-source,轻 ## 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 guidance if… - guidance is primarily Jupyter Notebook; ollama is Go. - Tags unique to guidance: backend support, control language, language-models, pip-installable. - When you need a specific language to finely control various LLM backends including Transformers, llama.cpp, and OpenAI ### Choose ollama if… - ollama is primarily Go; guidance is Jupyter Notebook. - 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 guidance - When your project is strictly confined to using only one type of backend which you can manage without a specialized control language - If your development environment does not support or prefer Jupyter Notebooks, Guidance may not be the best choice ## 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 guidance and ollama? guidance: A guidance language for controlling large language models.. 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 guidance over ollama? Choose guidance over ollama when guidance is primarily Jupyter Notebook; ollama is Go; Tags unique to guidance: backend support, control language, language-models, pip-installable; When you need a specific language to finely control various LLM backends including Transformers, llama.cpp, and OpenAI. ### When should I choose ollama over guidance? Choose ollama over guidance when ollama is primarily Go; guidance is Jupyter Notebook; 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 guidance? When your project is strictly confined to using only one type of backend which you can manage without a specialized control language If your development environment does not support or prefer Jupyter Notebooks, Guidance may not be the best choice ### 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 guidance or ollama more popular on GitHub? ollama has more GitHub stars (175,936 vs 21,656). Stars measure visibility, not whether either tool fits your constraints. ### Are guidance and ollama open source? Yes - both are open-source projects on GitHub (guidance: MIT, ollama: MIT). ### Where can I find alternatives to guidance or ollama? GraphCanon lists graph-backed alternatives at [guidance alternatives](/tools/guidance-ai-guidance/alternatives) and [ollama alternatives](/tools/ollama-ollama/alternatives) ([guidance markdown twin](/tools/guidance-ai-guidance/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/guidance-ai-guidance-vs-ollama-ollama.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, guidance or ollama? guidance: Steady. 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 guidance and ollama? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [guidance trust report](/tools/guidance-ai-guidance/trust); [ollama trust report](/tools/ollama-ollama/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=guidance-ai-guidance`](/api/graphcanon/graph?tool=guidance-ai-guidance) - 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/_