Comparison
rkllama vs awesome-local-llm
Verdict
Pick rkllama if ollama alternative for Rockchip NPU: optimized AI and deep learning inference on Rockchip devices; pick awesome-local-llm if awesome-local-llm is a curated list of resources for the local operation of large language models.
Markdown twin · rkllama alternatives · awesome-local-llm alternatives
GraphCanon updated Sep 20, 2026
17views this month
vs
Trust & integrity
| Signal | rkllama | awesome-local-llm |
|---|---|---|
| Maintenance | Active (25d since push) As of Sep 20, 2026 · github_public_v1 | Very active (6d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 20, 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
- rkllama
- Ollama alternative for Rockchip NPU with optimized AI and Deep learning model inference
- awesome-local-llm
- Resources for running LLMs locally
Stars
- rkllama
- 605
- awesome-local-llm
- 2.9k
Forks
- rkllama
- 99
- awesome-local-llm
- 388
Open issues
- rkllama
- 65
- awesome-local-llm
- 169
Language
- rkllama
- Python
- awesome-local-llm
- -
Adopt for
- rkllama
- Ollama alternative for Rockchip NPU: optimized AI and deep learning inference on Rockchip devices
- awesome-local-llm
- awesome-local-llm is a curated list of resources for the local operation of large language models.
Persona
- rkllama
- -
- awesome-local-llm
- -
Runtime
- rkllama
- -
- awesome-local-llm
- -
License
- rkllama
- GPL-3.0
- awesome-local-llm
- MIT License
Last pushed
- rkllama
- Aug 25, 2026
- awesome-local-llm
- Sep 13, 2026
Categories
- rkllama
- Inference & Serving
- awesome-local-llm
- Inference & Serving
Trust and health
Maintenance
- rkllama
- Active (82%)
- awesome-local-llm
- Very active (96%)
Days since push
- rkllama
- 25d
- awesome-local-llm
- 6d
Open issues (now)
- rkllama
- 65
- awesome-local-llm
- 169
Stars delta
- rkllama
- +28 (30d)
- awesome-local-llm
- +351 (30d)
Open issues delta
- rkllama
- +6 (30d)
- awesome-local-llm
- +40 (30d)
Full report
- rkllama
- Trust report
- awesome-local-llm
- Trust report
Choose rkllama if…
- License: rkllama is GPL-3.0, awesome-local-llm is MIT.
- Tags unique to rkllama: client-server, llm-inference, npu-llm, orange-pi.
- rkllama ships Docker support for self-hosted deployment.
- You need to run models specifically optimized for Rockchip Neural Processing Unit (NPU)
When NOT to use rkllama
- Your hardware does not include a Rockchip NPU
- You are looking for an AI solution that works across multiple non-Rockchip platforms
Choose awesome-local-llm if…
- License: awesome-local-llm is MIT, rkllama is GPL-3.0.
- Pricing: The list itself is free and open-source under the MIT license..
- Requirements: Technical skill in setting up a self-hosted large language model environment is necessary.
- Tags unique to awesome-local-llm: awesome-list, llm, local-ai, self-hosted.
- - If you require extensive documentation and resources for setting up and running LLMs on your own hardware, this tool provides a comprehensive list of options
When NOT to use awesome-local-llm
- - Avoid if you seek direct tools rather than a curated list; awesome-local-llm does not provide the actual software but guidance and links
- - Not suitable for users who prefer ready-to-use solutions without needing additional configuration, as it requires self-hosting expertise to utilize its resources
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (NotPunchnox/rkllama) · observed Sep 20, 2026
- GitHub forks (NotPunchnox/rkllama) · observed Sep 20, 2026
- Last push (NotPunchnox/rkllama) · observed Aug 25, 2026
- License file (GPL-3.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (rafska/awesome-local-llm) · observed Sep 20, 2026
- GitHub forks (rafska/awesome-local-llm) · observed Sep 20, 2026
- Last push (rafska/awesome-local-llm) · observed Sep 13, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: rkllama 605 · awesome-local-llm 2.9k (synced Sep 20, 2026).
Common questions
- What is the difference between rkllama and awesome-local-llm?
- rkllama: Ollama alternative for Rockchip NPU with optimized AI and Deep learning model inference. awesome-local-llm: Resources for running LLMs locally. See the comparison table for live GitHub stats and shared categories.
- When should I choose rkllama over awesome-local-llm?
- Choose rkllama over awesome-local-llm when License: rkllama is GPL-3.0, awesome-local-llm is MIT; Tags unique to rkllama: client-server, llm-inference, npu-llm, orange-pi; rkllama ships Docker support for self-hosted deployment; You need to run models specifically optimized for Rockchip Neural Processing Unit (NPU).
- When should I choose awesome-local-llm over rkllama?
- Choose awesome-local-llm over rkllama when License: awesome-local-llm is MIT, rkllama is GPL-3.0; Pricing: The list itself is free and open-source under the MIT license.; Requirements: Technical skill in setting up a self-hosted large language model environment is necessary; Tags unique to awesome-local-llm: awesome-list, llm, local-ai, self-hosted; - If you require extensive documentation and resources for setting up and running LLMs on your own hardware, this tool provides a comprehensive list of options.
- When should I avoid rkllama?
- Your hardware does not include a Rockchip NPU You are looking for an AI solution that works across multiple non-Rockchip platforms
- When should I avoid awesome-local-llm?
- - Avoid if you seek direct tools rather than a curated list; awesome-local-llm does not provide the actual software but guidance and links - Not suitable for users who prefer ready-to-use solutions without needing additional configuration, as it requires self-hosting expertise to utilize its resources
- Is rkllama or awesome-local-llm more popular on GitHub?
- awesome-local-llm has more GitHub stars (2,869 vs 605). Stars measure visibility, not whether either tool fits your constraints.
- Are rkllama and awesome-local-llm open source?
- Yes - both are open-source projects on GitHub (rkllama: GPL-3.0, awesome-local-llm: MIT).
- Where can I find alternatives to rkllama or awesome-local-llm?
- GraphCanon lists graph-backed alternatives at rkllama alternatives and awesome-local-llm alternatives (rkllama markdown twin, awesome-local-llm 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, rkllama or awesome-local-llm?
- rkllama: Active. awesome-local-llm: 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 rkllama and awesome-local-llm?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: rkllama trust report; awesome-local-llm trust report.