--- title: "pratical-llms vs Awesome-LLMs-ICLR-24" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/antoniogr7-pratical-llms-vs-azminewasi-awesome-llms-iclr-24" tools: ["antoniogr7-pratical-llms", "azminewasi-awesome-llms-iclr-24"] --- # pratical-llms vs Awesome-LLMs-ICLR-24 *GraphCanon updated Sep 20, 2026* ## Verdict Pick pratical-llms if practical-llms is a collection of Jupyter Notebooks aimed at LLM practitioners with practical guidance on quantization, sharding, inference and evaluation techniques; pick Awesome-LLMs-ICLR-24 if awesome-LLMs-ICLR-24 is an essential resource hub for researchers and developers working with large language models, focusing on LLM research papers accepted at ICLR in 2024. [pratical-llms](https://github.com/AntonioGr7/pratical-llms) reports 53 GitHub stars, 15 forks, and 0 open issues, last pushed Jan 13, 2025. [Awesome-LLMs-ICLR-24](https://github.com/azminewasi/Awesome-LLMs-ICLR-24) has 72 stars, 5 forks, and 0 open issues, last pushed Apr 4, 2024. Figures are from public GitHub metadata via [pratical-llms's repository](https://github.com/AntonioGr7/pratical-llms) and [Awesome-LLMs-ICLR-24's repository](https://github.com/azminewasi/Awesome-LLMs-ICLR-24). | | [pratical-llms](/tools/antoniogr7-pratical-llms.md) | [Awesome-LLMs-ICLR-24](/tools/azminewasi-awesome-llms-iclr-24.md) | | --- | --- | --- | | Tagline | A collection of hands-on notebooks for LLM practitioners | Compilation of LLM papers from ICLR 2024 | | Stars | 53 | 72 | | Forks | 15 | 5 | | Open issues | 0 | 0 | | Language | Jupyter Notebook | - | | Adopt for | practical-llms is a collection of Jupyter Notebooks aimed at LLM practitioners with practical guidance on quantization, sharding, inference and evaluation techniques. | Awesome-LLMs-ICLR-24 is an essential resource hub for researchers and developers working with large language models, focusing on LLM research papers accepted at ICLR in 2024. | | Persona | - | - | | Runtime | - | - | | License | - | MIT | | Categories | Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [pratical-llms](/tools/antoniogr7-pratical-llms.md) | [Awesome-LLMs-ICLR-24](/tools/azminewasi-awesome-llms-iclr-24.md) | | --- | --- | --- | | Days since push | 604d | 887d | | Full report | [trust report](/tools/antoniogr7-pratical-llms/trust.md) | [trust report](/tools/azminewasi-awesome-llms-iclr-24/trust.md) | ## Decision facts: pratical-llms - **Adopt for:** practical-llms is a collection of Jupyter Notebooks aimed at LLM practitioners with practical guidance on quantization, sharding, inference and evaluation techniques. ## Decision facts: Awesome-LLMs-ICLR-24 - **Adopt for:** Awesome-LLMs-ICLR-24 is an essential resource hub for researchers and developers working with large language models, focusing on LLM research papers accepted at ICLR in 2024. ## Choose when ### Choose pratical-llms if… - Tags unique to pratical-llms: genai, llm-serving, quantization. - If you want to explore specific quantization methods like BitandBytes, GPTQ, exllamav2, or Half-Quadratic Quantization (HQQ). - More recently updated (last pushed Jan 13, 2025). ### Choose Awesome-LLMs-ICLR-24 if… - Tags unique to Awesome-LLMs-ICLR-24: large-language-model, llm-agent, llm-framework, pretrained-language-model. - Also covers Developer Tools. - If you are focusing specifically on recent advancements in Large Language Models discussed in the context of ICLR 2024, this repository will provide cutting-edge research papers and insights. ## When NOT to use pratical-llms - If you seek deep theoretical insights rather than practical implementation details. - For users looking for commercial support as this repository does not provide it, unlike some competitors. ## When NOT to use Awesome-LLMs-ICLR-24 - If you are looking for more general resources that cover a wider time span or different conferences than ICLR 2024. - For projects where immediate practical application of models without understanding the underlying research is prioritized over detailed exploration and analysis. ## Common questions ### What is the difference between pratical-llms and Awesome-LLMs-ICLR-24? pratical-llms: A collection of hands-on notebooks for LLM practitioners. Awesome-LLMs-ICLR-24: Compilation of LLM papers from ICLR 2024. See the comparison table for live GitHub stats and shared categories. ### When should I choose pratical-llms over Awesome-LLMs-ICLR-24? Choose pratical-llms over Awesome-LLMs-ICLR-24 when Tags unique to pratical-llms: genai, llm-serving, quantization; If you want to explore specific quantization methods like BitandBytes, GPTQ, exllamav2, or Half-Quadratic Quantization (HQQ); More recently updated (last pushed Jan 13, 2025). ### When should I choose Awesome-LLMs-ICLR-24 over pratical-llms? Choose Awesome-LLMs-ICLR-24 over pratical-llms when Tags unique to Awesome-LLMs-ICLR-24: large-language-model, llm-agent, llm-framework, pretrained-language-model; Also covers Developer Tools; If you are focusing specifically on recent advancements in Large Language Models discussed in the context of ICLR 2024, this repository will provide cutting-edge research papers and insights. ### When should I avoid pratical-llms? If you seek deep theoretical insights rather than practical implementation details. For users looking for commercial support as this repository does not provide it, unlike some competitors. ### When should I avoid Awesome-LLMs-ICLR-24? If you are looking for more general resources that cover a wider time span or different conferences than ICLR 2024. For projects where immediate practical application of models without understanding the underlying research is prioritized over detailed exploration and analysis. ### Is pratical-llms or Awesome-LLMs-ICLR-24 more popular on GitHub? Awesome-LLMs-ICLR-24 has more GitHub stars (72 vs 53). Stars measure visibility, not whether either tool fits your constraints. ### Are pratical-llms and Awesome-LLMs-ICLR-24 open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to pratical-llms or Awesome-LLMs-ICLR-24? GraphCanon lists graph-backed alternatives at [pratical-llms alternatives](/tools/antoniogr7-pratical-llms/alternatives) and [Awesome-LLMs-ICLR-24 alternatives](/tools/azminewasi-awesome-llms-iclr-24/alternatives) ([pratical-llms markdown twin](/tools/antoniogr7-pratical-llms/alternatives.md), [Awesome-LLMs-ICLR-24 markdown twin](/tools/azminewasi-awesome-llms-iclr-24/alternatives.md)), 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](/compare/antoniogr7-pratical-llms-vs-azminewasi-awesome-llms-iclr-24.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, pratical-llms or Awesome-LLMs-ICLR-24? pratical-llms: Dormant. Awesome-LLMs-ICLR-24: 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 pratical-llms and Awesome-LLMs-ICLR-24? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [pratical-llms trust report](/tools/antoniogr7-pratical-llms/trust); [Awesome-LLMs-ICLR-24 trust report](/tools/azminewasi-awesome-llms-iclr-24/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=antoniogr7-pratical-llms`](/api/graphcanon/graph?tool=antoniogr7-pratical-llms) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_