Comparison
distributed-llama vs deploy-llms-with-ansible
Verdict
Pick distributed-llama if distributed-llama is a C++ framework that leverages multiple home devices for faster large language model inference, under the MIT license; pick deploy-llms-with-ansible if deploy-llms-with-ansible.
Markdown twin · distributed-llama alternatives · deploy-llms-with-ansible alternatives
GraphCanon updated 1w
vs
Trust & integrity
| Signal | distributed-llama | deploy-llms-with-ansible |
|---|---|---|
| Maintenance | Active (19d since push) As of 3w · github_public_v1 | Dormant (462d since push) As of 1w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 3w · github_public_v1 | Not a fork · Personal account As of 1w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- distributed-llama
- Distributed LLM inference using home devices cluster
- deploy-llms-with-ansible
- Easily deploy LLMs using Ansible
Stars
- distributed-llama
- 3.0k
- deploy-llms-with-ansible
- 3
Forks
- distributed-llama
- 242
- deploy-llms-with-ansible
- 0
Open issues
- distributed-llama
- 48
- deploy-llms-with-ansible
- 0
Language
- distributed-llama
- C++
- deploy-llms-with-ansible
- -
Adopt for
- distributed-llama
- distributed-llama is a C++ framework that leverages multiple home devices for faster large language model inference, under the MIT license.
- deploy-llms-with-ansible
- deploy-llms-with-ansible
Persona
- distributed-llama
- -
- deploy-llms-with-ansible
- -
Runtime
- distributed-llama
- -
- deploy-llms-with-ansible
- -
License
- distributed-llama
- MIT
- deploy-llms-with-ansible
- -
Last pushed
- distributed-llama
- Jul 5, 2026
- deploy-llms-with-ansible
- May 1, 2025
Categories
- distributed-llama
- Inference & Serving
- deploy-llms-with-ansible
- Inference & Serving
Trust and health
Maintenance
- distributed-llama
- Active (82%)
- deploy-llms-with-ansible
- Dormant (18%)
Days since push
- distributed-llama
- 19d
- deploy-llms-with-ansible
- 462d
Open issues (now)
- distributed-llama
- 48
- deploy-llms-with-ansible
- 0
Full report
- distributed-llama
- Trust report
- deploy-llms-with-ansible
- Trust report
Choose distributed-llama if…
- Tags unique to distributed-llama: distributed-computing, llm-inference, neural-network.
- When you have multiple interconnected home devices and want to maximize their combined computing power for LLM inference tasks.
- More GitHub stars (3.0k vs 3) - visibility, not fit.
When NOT to use distributed-llama
- For scenarios with fewer than two available devices, as the framework's capability to distribute and boost performance would be limited.
- In professional environments that require strict data privacy controls, due to potential network vulnerabilities among home devices.
Choose deploy-llms-with-ansible if…
- Requirements: Requires Docker; Requires Ansible installed and configured on the local machine.; Debian-based VM with SSH access and Docker must be present..
- Tags unique to deploy-llms-with-ansible: ansible, deployment, docker, llama-cpp.
- When you prefer using Ansible to automate the deployment of LLMs on a Debian-based virtual machine equipped with Docker.
When NOT to use deploy-llms-with-ansible
- When working in an environment that uses alternative automation tools like Terraform or Chef, as this tool specifically requires Ansible knowledge.
- If the infrastructure does not support or permit the use of Docker for containerizing applications.
- In cases where extensive customization of models beyond what llama.cpp and Ollama offer is required.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (b4rtaz/distributed-llama) · observed Jul 25, 2026
- GitHub forks (b4rtaz/distributed-llama) · observed Jul 25, 2026
- Last push (b4rtaz/distributed-llama) · observed Jul 5, 2026
- License file (MIT) · observed Jul 25, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (xamey/deploy-llms-with-ansible) · observed Aug 7, 2026
- GitHub forks (xamey/deploy-llms-with-ansible) · observed Aug 7, 2026
- Last push (xamey/deploy-llms-with-ansible) · observed May 1, 2025
- License file (unknown) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: distributed-llama 3.0k · deploy-llms-with-ansible 3 (synced Jul 25, 2026).
Common questions
- What is the difference between distributed-llama and deploy-llms-with-ansible?
- distributed-llama: Distributed LLM inference using home devices cluster. deploy-llms-with-ansible: Easily deploy LLMs using Ansible. See the comparison table for live GitHub stats and shared categories.
- When should I choose distributed-llama over deploy-llms-with-ansible?
- Choose distributed-llama over deploy-llms-with-ansible when Tags unique to distributed-llama: distributed-computing, llm-inference, neural-network; When you have multiple interconnected home devices and want to maximize their combined computing power for LLM inference tasks; More GitHub stars (3.0k vs 3) - visibility, not fit.
- When should I choose deploy-llms-with-ansible over distributed-llama?
- Choose deploy-llms-with-ansible over distributed-llama when Requirements: Requires Docker; Requires Ansible installed and configured on the local machine.; Debian-based VM with SSH access and Docker must be present.; Tags unique to deploy-llms-with-ansible: ansible, deployment, docker, llama-cpp; When you prefer using Ansible to automate the deployment of LLMs on a Debian-based virtual machine equipped with Docker.
- When should I avoid distributed-llama?
- For scenarios with fewer than two available devices, as the framework's capability to distribute and boost performance would be limited. In professional environments that require strict data privacy controls, due to potential network vulnerabilities among home devices.
- When should I avoid deploy-llms-with-ansible?
- When working in an environment that uses alternative automation tools like Terraform or Chef, as this tool specifically requires Ansible knowledge. If the infrastructure does not support or permit the use of Docker for containerizing applications. In cases where extensive customization of models beyond what llama.cpp and Ollama offer is required.
- Is distributed-llama or deploy-llms-with-ansible more popular on GitHub?
- distributed-llama has more GitHub stars (3,012 vs 3). Stars measure visibility, not whether either tool fits your constraints.
- Are distributed-llama and deploy-llms-with-ansible open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to distributed-llama or deploy-llms-with-ansible?
- GraphCanon lists graph-backed alternatives at distributed-llama alternatives and deploy-llms-with-ansible alternatives (distributed-llama markdown twin, deploy-llms-with-ansible 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, distributed-llama or deploy-llms-with-ansible?
- distributed-llama: Active. deploy-llms-with-ansible: 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 distributed-llama and deploy-llms-with-ansible?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: distributed-llama trust report; deploy-llms-with-ansible trust report.