Comparison
distributed-llama vs omlx
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 omlx if omlx is an LLM inference server tailored for Apple Silicon that emphasizes continuous batching and SSD caching capabilities, accessible through macOS menu bar control or Homebrew installation.
Markdown twin · distributed-llama alternatives · omlx alternatives
GraphCanon updated Sep 20, 2026
7views this month
vs
Trust & integrity
| Signal | distributed-llama | omlx |
|---|---|---|
| Maintenance | Steady (76d since push) As of Sep 19, 2026 · github_public_v1 | Very active (0d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 19, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 15, 2026 · 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
- omlx
- LLM inference server with continuous batching and SSD caching for Apple Silicon
Stars
- distributed-llama
- 3.1k
- omlx
- 22k
Forks
- distributed-llama
- 250
- omlx
- 1.9k
Open issues
- distributed-llama
- 48
- omlx
- 1.4k
Language
- distributed-llama
- C++
- omlx
- Python
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.
- omlx
- omlx is an LLM inference server tailored for Apple Silicon that emphasizes continuous batching and SSD caching capabilities, accessible through macOS menu bar control or Homebrew installation.
Persona
- distributed-llama
- -
- omlx
- -
Runtime
- distributed-llama
- -
- omlx
- -
License
- distributed-llama
- MIT
- omlx
- omlx is available under the Apache License, Version 2.0 (Apache-2.0), a permissive free software license.
Last pushed
- distributed-llama
- Jul 5, 2026
- omlx
- Sep 20, 2026
Categories
- distributed-llama
- Inference & Serving
- omlx
- Inference & Serving
Trust and health
Maintenance
- distributed-llama
- Steady (60%)
- omlx
- Very active (96%)
Days since push
- distributed-llama
- 76d
- omlx
- 0d
Open issues (now)
- distributed-llama
- 48
- omlx
- 1.4k
Stars delta
- distributed-llama
- +48 (30d)
- omlx
- +3.3k (30d)
Open issues delta
- distributed-llama
- 0 (30d)
- omlx
- +552 (30d)
Full report
- distributed-llama
- Trust report
- omlx
- Trust report
Choose distributed-llama if…
- distributed-llama is primarily C++; omlx is Python.
- License: distributed-llama is MIT, omlx is Apache-2.0.
- 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.
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 omlx if…
- omlx is primarily Python; distributed-llama is C++.
- License: omlx is Apache-2.0, distributed-llama is MIT.
- Tags unique to omlx: apple-silicon, inference-server, llm, macos.
- If your primary computing environment is based on Apple Silicon devices, omlx offers optimized performance for running large language model inferences.
When NOT to use omlx
- If your development infrastructure relies on non-Apple Silicon hardware, omlx's specific optimizations will not be as beneficial.
- Teams that require cross-platform compatibility or run servers predominantly on non-macOS operating systems should consider alternatives with broader support.
- For environments where direct control through the menu bar is not practical or desired.
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 Sep 20, 2026
- GitHub forks (b4rtaz/distributed-llama) · observed Sep 20, 2026
- Last push (b4rtaz/distributed-llama) · observed Jul 5, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (jundot/omlx) · observed Sep 20, 2026
- GitHub forks (jundot/omlx) · observed Sep 20, 2026
- Last push (jundot/omlx) · observed Sep 20, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: distributed-llama 3.1k · omlx 22k (synced Sep 20, 2026).
Common questions
- What is the difference between distributed-llama and omlx?
- distributed-llama: Distributed LLM inference using home devices cluster. omlx: LLM inference server with continuous batching and SSD caching for Apple Silicon. See the comparison table for live GitHub stats and shared categories.
- When should I choose distributed-llama over omlx?
- Choose distributed-llama over omlx when distributed-llama is primarily C++; omlx is Python; License: distributed-llama is MIT, omlx is Apache-2.0; 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.
- When should I choose omlx over distributed-llama?
- Choose omlx over distributed-llama when omlx is primarily Python; distributed-llama is C++; License: omlx is Apache-2.0, distributed-llama is MIT; Tags unique to omlx: apple-silicon, inference-server, llm, macos; If your primary computing environment is based on Apple Silicon devices, omlx offers optimized performance for running large language model inferences.
- 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 omlx?
- If your development infrastructure relies on non-Apple Silicon hardware, omlx's specific optimizations will not be as beneficial. Teams that require cross-platform compatibility or run servers predominantly on non-macOS operating systems should consider alternatives with broader support. For environments where direct control through the menu bar is not practical or desired.
- Is distributed-llama or omlx more popular on GitHub?
- omlx has more GitHub stars (21,934 vs 3,060). Stars measure visibility, not whether either tool fits your constraints.
- Are distributed-llama and omlx open source?
- Yes - both are open-source projects on GitHub (distributed-llama: MIT, omlx: Apache-2.0).
- Where can I find alternatives to distributed-llama or omlx?
- GraphCanon lists graph-backed alternatives at distributed-llama alternatives and omlx alternatives (distributed-llama markdown twin, omlx 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 omlx?
- distributed-llama: Steady. omlx: 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 distributed-llama and omlx?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: distributed-llama trust report; omlx trust report.