---
title: "ollama vs openmodelz"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/ollama-ollama-vs-tensorchord-openmodelz"
tools: ["ollama-ollama", "tensorchord-openmodelz"]
---

# ollama vs openmodelz

*GraphCanon updated Jul 11, 2026*

## Verdict

Pick ollama when license: ollama is MIT, openmodelz is Apache-2.0; pick openmodelz when license: openmodelz is Apache-2.0, ollama is MIT.

[ollama](https://ollama.com) reports 176k GitHub stars, 17k forks, and 3.4k open issues, last pushed Jul 10, 2026. [openmodelz](https://docs.open.modelz.ai) has 281 stars, 26 forks, and 23 open issues, last pushed Nov 3, 2023. Figures are from public GitHub metadata via [ollama's repository](https://github.com/ollama/ollama) and [openmodelz's repository](https://github.com/tensorchord/openmodelz).

| | [ollama](/tools/ollama-ollama.md) | [openmodelz](/tools/tensorchord-openmodelz.md) |
| --- | --- | --- |
| Tagline | Get up and running with various large language models using Ollama. | Autoscale LLM (vLLM, SGLang, LMDeploy) inferences on Kubernetes (and others) |
| Stars | 175,936 | 281 |
| Forks | 16,939 | 26 |
| Open issues | 3,423 | 23 |
| Language | Go | 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 | MIT license - permissive open-source licensing that allows for broad use of the tool. | Apache-2.0 |
| 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) | [openmodelz](/tools/tensorchord-openmodelz.md) |
| --- | --- | --- |
| Maintenance | Very active (96%) | Dormant (18%) |
| Days since push | 1d | 981d |
| Open issues (now) | 3.4k | 23 |
| Security scan | 52 low (52 low) | 106 low (106 low) |
| Full report | [trust report](/tools/ollama-ollama/trust.md) | [trust report](/tools/tensorchord-openmodelz/trust.md) |

## Shared compatibility

- **Python**: [ollama](/tools/ollama-ollama.md) - Python runtime; [openmodelz](/tools/tensorchord-openmodelz.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…

- License: ollama is MIT, openmodelz is Apache-2.0.
- Ollama supports self-hosted and cloud-deployable models using Docker, Helm charts, and various package managers.
- Tags unique to ollama: deepseek, gemma, glm, llama.
- 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 openmodelz if…

- License: openmodelz is Apache-2.0, ollama is MIT.
- Tags unique to openmodelz: cluster-manager, hacktoberfest, inference, llm.
- 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 openmodelz

- Last GitHub push was 982 days ago (dormant maintenance, Nov 3, 2023). Validate activity before betting a new project on openmodelz.
- 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 openmodelz?

ollama: Get up and running with various large language models using Ollama.. openmodelz: Autoscale LLM (vLLM, SGLang, LMDeploy) inferences on Kubernetes (and others). See the comparison table for live GitHub stats and shared categories.

### When should I choose ollama over openmodelz?

Choose ollama over openmodelz when License: ollama is MIT, openmodelz is Apache-2.0; Ollama supports self-hosted and cloud-deployable models using Docker, Helm charts, and various package managers; Tags unique to ollama: deepseek, gemma, glm, llama; 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 openmodelz over ollama?

Choose openmodelz over ollama when License: openmodelz is Apache-2.0, ollama is MIT; Tags unique to openmodelz: cluster-manager, hacktoberfest, inference, llm; 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 openmodelz?

Last GitHub push was 982 days ago (dormant maintenance, Nov 3, 2023). Validate activity before betting a new project on openmodelz. 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 openmodelz more popular on GitHub?

ollama has more GitHub stars (175,936 vs 281). Stars measure visibility, not whether either tool fits your constraints.

### Are ollama and openmodelz open source?

Yes - both are open-source projects on GitHub (ollama: MIT, openmodelz: Apache-2.0).

### Where can I find alternatives to ollama or openmodelz?

GraphCanon lists graph-backed alternatives at [ollama alternatives](/tools/ollama-ollama/alternatives) and [openmodelz alternatives](/tools/tensorchord-openmodelz/alternatives) ([ollama markdown twin](/tools/ollama-ollama/alternatives.md), [openmodelz markdown twin](/tools/tensorchord-openmodelz/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-tensorchord-openmodelz.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, ollama or openmodelz?

ollama: Very active. openmodelz: 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 openmodelz?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ollama trust report](/tools/ollama-ollama/trust); [openmodelz trust report](/tools/tensorchord-openmodelz/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/_
