--- title: "llm-axe vs aqueduct" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/emirsahin1-llm-axe-vs-runllm-aqueduct" tools: ["emirsahin1-llm-axe", "runllm-aqueduct"] --- # llm-axe vs aqueduct *GraphCanon updated Aug 13, 2026* ## Verdict Pick llm-axe if llm-axe is a Python-based toolkit aiming to facilitate quick applications development with local large language models, focusing on function-calling and compatibility with models like llama3; pick aqueduct if aqueduct is a deprecated Go-based tool for orchestrating LLM and ML workloads across various cloud infrastructures with Kubernetes support. [llm-axe](https://github.com/emirsahin1/llm-axe) reports 275 GitHub stars, 38 forks, and 0 open issues, last pushed Jan 5, 2025. [aqueduct](https://aqueducthq.com) has 517 stars, 20 forks, and 11 open issues, last pushed Jun 7, 2023. Figures are from public GitHub metadata via [llm-axe's repository](https://github.com/emirsahin1/llm-axe) and [aqueduct's repository](https://github.com/RunLLM/aqueduct). | | [llm-axe](/tools/emirsahin1-llm-axe.md) | [aqueduct](/tools/runllm-aqueduct.md) | | --- | --- | --- | | Tagline | Toolkit for quick implementation of LLM powered applications | Orchestrate LLM and ML workloads on any cloud infrastructure using Go. | | Stars | 275 | 517 | | Forks | 38 | 20 | | Open issues | 0 | 11 | | Language | Python | Go | | Adopt for | llm-axe is a Python-based toolkit aiming to facilitate quick applications development with local large language models, focusing on function-calling and compatibility with models like llama3. | Aqueduct is a deprecated Go-based tool for orchestrating LLM and ML workloads across various cloud infrastructures with Kubernetes support. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | LLM Frameworks, Model Training | Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [llm-axe](/tools/emirsahin1-llm-axe.md) | [aqueduct](/tools/runllm-aqueduct.md) | | --- | --- | --- | | Days since push | 584d | 1152d | | Open issues (now) | 0 | 11 | | Owner type | User | Organization | | Full report | [trust report](/tools/emirsahin1-llm-axe/trust.md) | [trust report](/tools/runllm-aqueduct/trust.md) | ## Decision facts: llm-axe - **Adopt for:** llm-axe is a Python-based toolkit aiming to facilitate quick applications development with local large language models, focusing on function-calling and compatibility with models like llama3. ## Decision facts: aqueduct - **Adopt for:** Aqueduct is a deprecated Go-based tool for orchestrating LLM and ML workloads across various cloud infrastructures with Kubernetes support. ## Choose when ### Choose llm-axe if… - llm-axe is primarily Python; aqueduct is Go. - License: llm-axe is MIT, aqueduct is Apache-2.0. - Tags unique to llm-axe: function-calling, llama3, local-llm, ollama. - When you need to develop LLM-powered applications quickly using local models, emphasizing simplicity and ease of integration. ### Choose aqueduct if… - aqueduct is primarily Go; llm-axe is Python. - License: aqueduct is Apache-2.0, llm-axe is MIT. - Tags unique to aqueduct: ai, data, data-science, kubernetes. - Also covers Inference & Serving. - When you need to deploy legacy workflows that depend on Aqueduct's specific implementation of custom ops for resource allocation and training. ## When NOT to use llm-axe - Avoid if your project strictly requires cloud-based LLM resources or seamless model switching across different providers. - Not recommended for scenarios where extensive customization of the training pipeline is a requirement, as it focuses on implementation rather than deep training flexibility. ## When NOT to use aqueduct - Avoid if active project maintenance or community support is required as Aqueduct is no longer maintained. - Skip this tool for new projects focusing on state-of-the-art ML orchestration, opting instead for actively supported alternatives. ## Common questions ### What is the difference between llm-axe and aqueduct? llm-axe: Toolkit for quick implementation of LLM powered applications. aqueduct: Orchestrate LLM and ML workloads on any cloud infrastructure using Go.. See the comparison table for live GitHub stats and shared categories. ### When should I choose llm-axe over aqueduct? Choose llm-axe over aqueduct when llm-axe is primarily Python; aqueduct is Go; License: llm-axe is MIT, aqueduct is Apache-2.0; Tags unique to llm-axe: function-calling, llama3, local-llm, ollama; When you need to develop LLM-powered applications quickly using local models, emphasizing simplicity and ease of integration. ### When should I choose aqueduct over llm-axe? Choose aqueduct over llm-axe when aqueduct is primarily Go; llm-axe is Python; License: aqueduct is Apache-2.0, llm-axe is MIT; Tags unique to aqueduct: ai, data, data-science, kubernetes; Also covers Inference & Serving; When you need to deploy legacy workflows that depend on Aqueduct's specific implementation of custom ops for resource allocation and training. ### When should I avoid llm-axe? Avoid if your project strictly requires cloud-based LLM resources or seamless model switching across different providers. Not recommended for scenarios where extensive customization of the training pipeline is a requirement, as it focuses on implementation rather than deep training flexibility. ### When should I avoid aqueduct? Avoid if active project maintenance or community support is required as Aqueduct is no longer maintained. Skip this tool for new projects focusing on state-of-the-art ML orchestration, opting instead for actively supported alternatives. ### Is llm-axe or aqueduct more popular on GitHub? aqueduct has more GitHub stars (517 vs 275). Stars measure visibility, not whether either tool fits your constraints. ### Are llm-axe and aqueduct open source? Yes - both are open-source projects on GitHub (llm-axe: MIT, aqueduct: Apache-2.0). ### Where can I find alternatives to llm-axe or aqueduct? GraphCanon lists graph-backed alternatives at [llm-axe alternatives](/tools/emirsahin1-llm-axe/alternatives) and [aqueduct alternatives](/tools/runllm-aqueduct/alternatives) ([llm-axe markdown twin](/tools/emirsahin1-llm-axe/alternatives.md), [aqueduct markdown twin](/tools/runllm-aqueduct/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/emirsahin1-llm-axe-vs-runllm-aqueduct.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, llm-axe or aqueduct? llm-axe: Dormant. aqueduct: 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 llm-axe and aqueduct? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [llm-axe trust report](/tools/emirsahin1-llm-axe/trust); [aqueduct trust report](/tools/runllm-aqueduct/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=emirsahin1-llm-axe`](/api/graphcanon/graph?tool=emirsahin1-llm-axe) - 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/_