Comparison
LLMKube vs anubis-oss
Verdict
Pick LLMKube if lLMKube is a Kubernetes operator designed for deploying and scaling Language Model (LM) inference across different GPU types, supporting multiple runtimes; pick anubis-oss if anubis-oss, specifically tailored for Apple Silicon devices using Swift, is distinguished by its focus on local large language model evaluation and testing within the macOS environment.
Markdown twin · LLMKube alternatives · anubis-oss alternatives
GraphCanon updated 1w
vs
Trust & integrity
| Signal | LLMKube | anubis-oss |
|---|---|---|
| Maintenance | Very active (0d since push) As of 3w · github_public_v1 | Steady (56d since push) As of 1w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Personal account As of 1w · github_public_v1 |
| OSV dependency advisories | No published findings from this source as of 2026-07-11 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
- LLMKube
- Kubernetes operator for self-hosted LLM inference
- anubis-oss
- Local LLM Testing & Benchmarking for Apple Silicon
Stars
- LLMKube
- 183
- anubis-oss
- 198
Forks
- LLMKube
- 27
- anubis-oss
- 12
Open issues
- LLMKube
- 77
- anubis-oss
- 4
Language
- LLMKube
- Go
- anubis-oss
- Swift
Adopt for
- LLMKube
- LLMKube is a Kubernetes operator designed for deploying and scaling Language Model (LM) inference across different GPU types, supporting multiple runtimes.
- anubis-oss
- Anubis-oss, specifically tailored for Apple Silicon devices using Swift, is distinguished by its focus on local large language model evaluation and testing within the macOS environment.
Persona
- LLMKube
- -
- anubis-oss
- -
Runtime
- LLMKube
- -
- anubis-oss
- -
License
- LLMKube
- Apache-2.0
- anubis-oss
- GPL-3.0 license ensures that any derivative works related to anubis-oss must also be open source under the same licensing terms.
Last pushed
- LLMKube
- Aug 1, 2026
- anubis-oss
- Jun 18, 2026
Categories
- LLMKube
- Inference & Serving
- anubis-oss
- Evaluation & Observability, Inference & Serving
Trust and health
Maintenance
- LLMKube
- Very active (96%)
- anubis-oss
- Steady (60%)
Days since push
- LLMKube
- 0d
- anubis-oss
- 56d
Open issues (now)
- LLMKube
- 77
- anubis-oss
- 4
Owner type
- LLMKube
- Organization
- anubis-oss
- User
OSV dependency advisories
- LLMKube
- No published findings from this source as of 2026-07-11
- anubis-oss
- No lockfile (source not queried)
Full report
- LLMKube
- Trust report
- anubis-oss
- Trust report
Choose LLMKube if…
- LLMKube is primarily Go; anubis-oss is Swift.
- License: LLMKube is Apache-2.0, anubis-oss is GPL-3.0.
- Tags unique to LLMKube: ai, autoscaling, edge-computing, gguf.
- LLMKube ships Docker support for self-hosted deployment.
- Use LLMKube if you need to run self-hosted Language Model inference with support for various GPU types like NVIDIA CUDA, AMD Vulkan, or Apple Silicon Metal.
When NOT to use LLMKube
- Avoid LLMKube if your deployment environment strictly limits the use of Kubernetes or does not support the specified GPU types - NVIDIA CUDA, AMD Vulkan, Apple Silicon Metal.
- Not recommended for users who require a solution that only supports specific models or runtimes which are not covered by the runtime options provided (llama.cpp, vLLM, TGI, mlx-server).
Choose anubis-oss if…
- anubis-oss is primarily Swift; LLMKube is Go.
- License: anubis-oss is GPL-3.0, LLMKube is Apache-2.0.
- Pricing: The tool is free and open-source with no monetary costs for usage or distribution..
- Requirements: Min 8 GB RAM.
- Tags unique to anubis-oss: benchmarking, llm, local-llm, macos.
- Also covers Evaluation & Observability.
- When developing and evaluating large language models intended to run natively on Apple Silicon hardware.
When NOT to use anubis-oss
- If your development does not involve Apple Silicon or macOS environments as Anubis-oss is tightly integrated with these platforms.
- When preferring a language other than Swift, since Anubis-oss depends on this for its operations.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (defilantech/LLMKube) · observed Aug 2, 2026
- GitHub forks (defilantech/LLMKube) · observed Aug 2, 2026
- Last push (defilantech/LLMKube) · observed Aug 1, 2026
- License file (Apache-2.0) · observed Aug 2, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (uncSoft/anubis-oss) · observed Aug 13, 2026
- GitHub forks (uncSoft/anubis-oss) · observed Aug 13, 2026
- Last push (uncSoft/anubis-oss) · observed Jun 18, 2026
- License file (GPL-3.0) · observed Aug 13, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: LLMKube 183 · anubis-oss 198 (synced Aug 2, 2026).
Common questions
- What is the difference between LLMKube and anubis-oss?
- LLMKube: Kubernetes operator for self-hosted LLM inference. anubis-oss: Local LLM Testing & Benchmarking for Apple Silicon. See the comparison table for live GitHub stats and shared categories.
- When should I choose LLMKube over anubis-oss?
- Choose LLMKube over anubis-oss when LLMKube is primarily Go; anubis-oss is Swift; License: LLMKube is Apache-2.0, anubis-oss is GPL-3.0; Tags unique to LLMKube: ai, autoscaling, edge-computing, gguf; LLMKube ships Docker support for self-hosted deployment; Use LLMKube if you need to run self-hosted Language Model inference with support for various GPU types like NVIDIA CUDA, AMD Vulkan, or Apple Silicon Metal.
- When should I choose anubis-oss over LLMKube?
- Choose anubis-oss over LLMKube when anubis-oss is primarily Swift; LLMKube is Go; License: anubis-oss is GPL-3.0, LLMKube is Apache-2.0; Pricing: The tool is free and open-source with no monetary costs for usage or distribution.; Requirements: Min 8 GB RAM; Tags unique to anubis-oss: benchmarking, llm, local-llm, macos; Also covers Evaluation & Observability; When developing and evaluating large language models intended to run natively on Apple Silicon hardware.
- When should I avoid LLMKube?
- Avoid LLMKube if your deployment environment strictly limits the use of Kubernetes or does not support the specified GPU types - NVIDIA CUDA, AMD Vulkan, Apple Silicon Metal. Not recommended for users who require a solution that only supports specific models or runtimes which are not covered by the runtime options provided (llama.cpp, vLLM, TGI, mlx-server).
- When should I avoid anubis-oss?
- If your development does not involve Apple Silicon or macOS environments as Anubis-oss is tightly integrated with these platforms. When preferring a language other than Swift, since Anubis-oss depends on this for its operations.
- Is LLMKube or anubis-oss more popular on GitHub?
- anubis-oss has more GitHub stars (198 vs 183). Stars measure visibility, not whether either tool fits your constraints.
- Are LLMKube and anubis-oss open source?
- Yes - both are open-source projects on GitHub (LLMKube: Apache-2.0, anubis-oss: GPL-3.0).
- Where can I find alternatives to LLMKube or anubis-oss?
- GraphCanon lists graph-backed alternatives at LLMKube alternatives and anubis-oss alternatives (LLMKube markdown twin, anubis-oss 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, LLMKube or anubis-oss?
- LLMKube: Very active. anubis-oss: Steady. 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 LLMKube and anubis-oss?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LLMKube trust report; anubis-oss trust report.