Comparison
dolly vs ollama
Verdict
Pick dolly if dolly is a large language model that can be used for response generation and training, available through Hugging Face and the Databricks Machine Learning Platform; 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, Gemma using docker images, package managers.
Markdown twin · dolly alternatives · ollama alternatives
GraphCanon updated 3w
Trust & integrity
| Signal | dolly | ollama |
|---|---|---|
| Maintenance | Dormant (1127d since push) As of 3w · github_public_v1 | Very active (1d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Organization account As of 3w · github_public_v1 |
| OSV dependency advisories | Published findings As of 1mo · osv@v1 | Published findings As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Published findings As of 2w · deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | No public record from this source As of 3w · openssf-scorecard@v1 |
Tagline
- dolly
- Large language model for response generation and training
- ollama
- Get up and running with various large language models using Ollama.
Stars
- dolly
- 11k
- ollama
- 178k
Forks
- dolly
- 1.1k
- ollama
- 17k
Open issues
- dolly
- 6
- ollama
- 3.6k
Language
- dolly
- Python
- ollama
- Go
Adopt for
- dolly
- Dolly is a large language model that can be used for response generation and training, available through Hugging Face and the Databricks Machine Learning Platform.
- ollama
- 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
- dolly
- -
- ollama
- -
Runtime
- dolly
- -
- ollama
- -
License
- dolly
- Apache-2.0
- ollama
- MIT license - permissive open-source licensing that allows for broad use of the tool.
Last pushed
- dolly
- Jun 30, 2023
- ollama
- Jul 31, 2026
Categories
- dolly
- Inference & Serving, LLM Frameworks
- ollama
- Inference & Serving, LLM Frameworks
Trust and health
Maintenance
- dolly
- Dormant (18%)
- ollama
- Very active (96%)
Days since push
- dolly
- 1127d
- ollama
- 1d
Open issues (now)
- dolly
- 6
- ollama
- 3.6k
deps.dev advisories
- dolly
- Not queried
- ollama
- Published findings
OpenSSF Scorecard
- dolly
- Not queried
- ollama
- No public record from this source
Full report
- dolly
- Trust report
- ollama
- Trust report
Choose dolly if…
- dolly is primarily Python; ollama is Go.
- License: dolly is Apache-2.0, ollama is MIT.
- Tags unique to dolly: chatbot, databricks, dolly.
- If your project requires a robust pre-trained model available via Hugging Face to quickly generate responses without extensive setup or training processes.
When NOT to use dolly
- If your project requires a local deployment model that does not involve cloud-based tools, as Dolly's optimal use case involves integration with the Databricks platform.
- In instances where immediate access to GPUs is constrained or expensive in your region, since Dolly training and inference are optimized for GPU processing environments.
Choose ollama if…
- ollama is primarily Go; dolly is Python.
- License: ollama is MIT, dolly 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, 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 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (databrickslabs/dolly) · observed Aug 1, 2026
- GitHub forks (databrickslabs/dolly) · observed Aug 1, 2026
- Last push (databrickslabs/dolly) · observed Jun 30, 2023
- License file (Apache-2.0) · observed Aug 1, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (ollama/ollama) · observed Aug 2, 2026
- GitHub forks (ollama/ollama) · observed Aug 2, 2026
- Last push (ollama/ollama) · observed Jul 31, 2026
- License file (MIT) · observed Aug 2, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: dolly 11k · ollama 178k (synced Aug 1, 2026).
Common questions
- What is the difference between dolly and ollama?
- dolly: Large language model for response generation and training. 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 dolly over ollama?
- Choose dolly over ollama when dolly is primarily Python; ollama is Go; License: dolly is Apache-2.0, ollama is MIT; Tags unique to dolly: chatbot, databricks, dolly; If your project requires a robust pre-trained model available via Hugging Face to quickly generate responses without extensive setup or training processes.
- When should I choose ollama over dolly?
- Choose ollama over dolly when ollama is primarily Go; dolly is Python; License: ollama is MIT, dolly 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, 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 dolly?
- If your project requires a local deployment model that does not involve cloud-based tools, as Dolly's optimal use case involves integration with the Databricks platform. In instances where immediate access to GPUs is constrained or expensive in your region, since Dolly training and inference are optimized for GPU processing environments.
- 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 dolly or ollama more popular on GitHub?
- ollama has more GitHub stars (177,524 vs 10,805). Stars measure visibility, not whether either tool fits your constraints.
- Are dolly and ollama open source?
- Yes - both are open-source projects on GitHub (dolly: Apache-2.0, ollama: MIT).
- Where can I find alternatives to dolly or ollama?
- GraphCanon lists graph-backed alternatives at dolly alternatives and ollama alternatives (dolly markdown twin, ollama markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, dolly or ollama?
- dolly: Dormant. 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 dolly and ollama?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: dolly trust report; ollama trust report.