Comparison
AI-Infra-from-Zero-to-Hero vs Liger-Kernel
Verdict
Pick AI-Infra-from-Zero-to-Hero when license: AI-Infra-from-Zero-to-Hero is MIT, Liger-Kernel is BSD-2-Clause; pick Liger-Kernel when license: Liger-Kernel is BSD-2-Clause, AI-Infra-from-Zero-to-Hero is MIT.
Markdown twin · AI-Infra-from-Zero-to-Hero alternatives · Liger-Kernel alternatives
GraphCanon updated today
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Trust & integrity
| Signal | AI-Infra-from-Zero-to-Hero | Liger-Kernel |
|---|---|---|
| Maintenance | Slowing (351d since push) As of today · github_public_v1 | Very active (4d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Personal account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No lockfile As of today · none |
Tagline
- AI-Infra-from-Zero-to-Hero
- 🚀 Awesome System for Machine Learning ⚡️ AI System Papers and Industry Practice. ⚡️ System for Machine Learning, LLM (Large Language Model), GenAI (Generative AI). 🍻 OSDI, NSDI, SIGCOMM, SoCC, MLSys
- Liger-Kernel
- Efficient Triton Kernels for LLM Training
Stars
- AI-Infra-from-Zero-to-Hero
- 4.2k
- Liger-Kernel
- 6.5k
Forks
- AI-Infra-from-Zero-to-Hero
- 402
- Liger-Kernel
- 554
Open issues
- AI-Infra-from-Zero-to-Hero
- 14
- Liger-Kernel
- 161
Language
- AI-Infra-from-Zero-to-Hero
- -
- Liger-Kernel
- Python
Adopt for
- AI-Infra-from-Zero-to-Hero
- AI-Infra-from-Zero-to-Hero is an extensive repository that curates a wide range of resources related to AI infrastructure, including tutorials and research papers in the areas of machine learning and large language model
- Liger-Kernel
- -
Persona
- AI-Infra-from-Zero-to-Hero
- -
- Liger-Kernel
- -
Runtime
- AI-Infra-from-Zero-to-Hero
- -
- Liger-Kernel
- -
License
- AI-Infra-from-Zero-to-Hero
- MIT
- Liger-Kernel
- BSD-2-Clause
Last pushed
- AI-Infra-from-Zero-to-Hero
- Jul 25, 2025
- Liger-Kernel
- Jul 6, 2026
Categories
- AI-Infra-from-Zero-to-Hero
- Model Training, LLM Frameworks, Inference & Serving
- Liger-Kernel
- LLM Frameworks, Model Training
Trust and health
Maintenance
- AI-Infra-from-Zero-to-Hero
- Slowing (36%)
- Liger-Kernel
- Very active (96%)
Days since push
- AI-Infra-from-Zero-to-Hero
- 351d
- Liger-Kernel
- 4d
Open issues (now)
- AI-Infra-from-Zero-to-Hero
- 14
- Liger-Kernel
- 161
Owner type
- AI-Infra-from-Zero-to-Hero
- User
- Liger-Kernel
- Organization
Full report
- AI-Infra-from-Zero-to-Hero
- Trust report
- Liger-Kernel
- Trust report
Choose AI-Infra-from-Zero-to-Hero if…
- License: AI-Infra-from-Zero-to-Hero is MIT, Liger-Kernel is BSD-2-Clause.
- Tags unique to AI-Infra-from-Zero-to-Hero: llmsys, model-training, mlsys, genai.
- Also covers Inference & Serving.
- When you require detailed resource curation on ML systems and LLM infrastructures, as AI-Infra-from-Zero-to-Hero offers comprehensive information.
When NOT to use AI-Infra-from-Zero-to-Hero
- If you seek real-time support or interactive forums, as AI-Infra-from-Zero-to-Hero is primarily a resource repository without live assistance.
- For hands-on coding exercises or practical projects as the tool focuses mostly on curating resources like tutorials and academic papers but does not provide step-by-step coding guides.
Choose Liger-Kernel if…
- License: Liger-Kernel is BSD-2-Clause, AI-Infra-from-Zero-to-Hero is MIT.
- Tags unique to Liger-Kernel: llms, llama, mistral, gemma2.
- More GitHub stars (6.5k vs 4.2k) - visibility, not fit.
When NOT to use Liger-Kernel
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (HuaizhengZhang/AI-Infra-from-Zero-to-Hero) · observed Jul 11, 2026
- GitHub forks (HuaizhengZhang/AI-Infra-from-Zero-to-Hero) · observed Jul 11, 2026
- Last push (HuaizhengZhang/AI-Infra-from-Zero-to-Hero) · observed Jul 25, 2025
- License file (MIT) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 10, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (linkedin/Liger-Kernel) · observed Jul 11, 2026
- GitHub forks (linkedin/Liger-Kernel) · observed Jul 11, 2026
- Last push (linkedin/Liger-Kernel) · observed Jul 6, 2026
- License file (BSD-2-Clause) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: AI-Infra-from-Zero-to-Hero 4.2k · Liger-Kernel 6.5k (synced Jul 11, 2026).
Common questions
- What is the difference between AI-Infra-from-Zero-to-Hero and Liger-Kernel?
- AI-Infra-from-Zero-to-Hero: 🚀 Awesome System for Machine Learning ⚡️ AI System Papers and Industry Practice. ⚡️ System for Machine Learning, LLM (Large Language Model), GenAI (Generative AI). 🍻 OSDI, NSDI, SIGCOMM, SoCC, MLSys. Liger-Kernel: Efficient Triton Kernels for LLM Training. See the comparison table for live GitHub stats and shared categories.
- When should I choose AI-Infra-from-Zero-to-Hero over Liger-Kernel?
- Choose AI-Infra-from-Zero-to-Hero over Liger-Kernel when License: AI-Infra-from-Zero-to-Hero is MIT, Liger-Kernel is BSD-2-Clause; Tags unique to AI-Infra-from-Zero-to-Hero: llmsys, model-training, mlsys, genai; Also covers Inference & Serving; When you require detailed resource curation on ML systems and LLM infrastructures, as AI-Infra-from-Zero-to-Hero offers comprehensive information.
- When should I choose Liger-Kernel over AI-Infra-from-Zero-to-Hero?
- Choose Liger-Kernel over AI-Infra-from-Zero-to-Hero when License: Liger-Kernel is BSD-2-Clause, AI-Infra-from-Zero-to-Hero is MIT; Tags unique to Liger-Kernel: llms, llama, mistral, gemma2; More GitHub stars (6.5k vs 4.2k) - visibility, not fit.
- When should I avoid AI-Infra-from-Zero-to-Hero?
- If you seek real-time support or interactive forums, as AI-Infra-from-Zero-to-Hero is primarily a resource repository without live assistance. For hands-on coding exercises or practical projects as the tool focuses mostly on curating resources like tutorials and academic papers but does not provide step-by-step coding guides.
- When should I avoid Liger-Kernel?
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Is AI-Infra-from-Zero-to-Hero or Liger-Kernel more popular on GitHub?
- Liger-Kernel has more GitHub stars (6,494 vs 4,176). Stars measure visibility, not whether either tool fits your constraints.
- Are AI-Infra-from-Zero-to-Hero and Liger-Kernel open source?
- Yes - both are open-source projects on GitHub (AI-Infra-from-Zero-to-Hero: MIT, Liger-Kernel: BSD-2-Clause).
- Where can I find alternatives to AI-Infra-from-Zero-to-Hero or Liger-Kernel?
- GraphCanon lists graph-backed alternatives at AI-Infra-from-Zero-to-Hero alternatives and Liger-Kernel alternatives (AI-Infra-from-Zero-to-Hero markdown twin, Liger-Kernel 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, AI-Infra-from-Zero-to-Hero or Liger-Kernel?
- AI-Infra-from-Zero-to-Hero: Slowing. Liger-Kernel: 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 AI-Infra-from-Zero-to-Hero and Liger-Kernel?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: AI-Infra-from-Zero-to-Hero trust report; Liger-Kernel trust report.