--- title: "codecompanion.nvim vs ollama" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/olimorris-codecompanion-nvim-vs-ollama-ollama" tools: ["olimorris-codecompanion-nvim", "ollama-ollama"] --- # codecompanion.nvim vs ollama *GraphCanon updated Jul 15, 2026* ## Verdict Pick codecompanion.nvim when codecompanion.nvim is primarily Lua; ollama is Go; pick ollama when ollama is primarily Go; codecompanion.nvim is Lua. [codecompanion.nvim](https://codecompanion.olimorris.dev) reports 6.7k GitHub stars, 436 forks, and 10 open issues, last pushed Jul 15, 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 [codecompanion.nvim's repository](https://github.com/olimorris/codecompanion.nvim) and [ollama's repository](https://github.com/ollama/ollama). | | [codecompanion.nvim](/tools/olimorris-codecompanion-nvim.md) | [ollama](/tools/ollama-ollama.md) | | --- | --- | --- | | Tagline | ✨ AI Coding, Vim Style | Get up and running with various large language models using Ollama. | | Stars | 6,743 | 175,936 | | Forks | 436 | 16,939 | | Open issues | 10 | 3,423 | | Language | Lua | Go | | 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 | Apache-2.0 | MIT license - permissive open-source licensing that allows for broad use of the tool. | | Categories | AI Agents, Inference & Serving, LLM Frameworks | Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [codecompanion.nvim](/tools/olimorris-codecompanion-nvim.md) | [ollama](/tools/ollama-ollama.md) | | --- | --- | --- | | Days since push | 0d | 1d | | Open issues (now) | 10 | 3.4k | | Owner type | User | Organization | | Full report | [trust report](/tools/olimorris-codecompanion-nvim/trust.md) | [trust report](/tools/ollama-ollama/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 codecompanion.nvim if… - codecompanion.nvim is primarily Lua; ollama is Go. - License: codecompanion.nvim is Apache-2.0, ollama is MIT. - Tags unique to codecompanion.nvim: acp, agent, agent-client-protocol, anthropic. - Also covers AI Agents. ### Choose ollama if… - ollama is primarily Go; codecompanion.nvim is Lua. - License: ollama is MIT, codecompanion.nvim is Apache-2.0. - Ollama supports self-hosted and cloud-deployable models using Docker, Helm charts, and various package managers. - Tags unique to ollama: gemma, glm, go, llama. - 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 codecompanion.nvim - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - 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. ## 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 codecompanion.nvim and ollama? codecompanion.nvim: ✨ AI Coding, Vim Style. 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 codecompanion.nvim over ollama? Choose codecompanion.nvim over ollama when codecompanion.nvim is primarily Lua; ollama is Go; License: codecompanion.nvim is Apache-2.0, ollama is MIT; Tags unique to codecompanion.nvim: acp, agent, agent-client-protocol, anthropic; Also covers AI Agents. ### When should I choose ollama over codecompanion.nvim? Choose ollama over codecompanion.nvim when ollama is primarily Go; codecompanion.nvim is Lua; License: ollama is MIT, codecompanion.nvim is Apache-2.0; Ollama supports self-hosted and cloud-deployable models using Docker, Helm charts, and various package managers; Tags unique to ollama: gemma, glm, go, llama; 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 codecompanion.nvim? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. 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. ### 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 codecompanion.nvim or ollama more popular on GitHub? ollama has more GitHub stars (175,936 vs 6,743). Stars measure visibility, not whether either tool fits your constraints. ### Are codecompanion.nvim and ollama open source? Yes - both are open-source projects on GitHub (codecompanion.nvim: Apache-2.0, ollama: MIT). ### Where can I find alternatives to codecompanion.nvim or ollama? GraphCanon lists graph-backed alternatives at [codecompanion.nvim alternatives](/tools/olimorris-codecompanion-nvim/alternatives) and [ollama alternatives](/tools/ollama-ollama/alternatives) ([codecompanion.nvim markdown twin](/tools/olimorris-codecompanion-nvim/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/olimorris-codecompanion-nvim-vs-ollama-ollama.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, codecompanion.nvim or ollama? codecompanion.nvim: Very active. 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 codecompanion.nvim and ollama? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [codecompanion.nvim trust report](/tools/olimorris-codecompanion-nvim/trust); [ollama trust report](/tools/ollama-ollama/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=olimorris-codecompanion-nvim`](/api/graphcanon/graph?tool=olimorris-codecompanion-nvim) - 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/_