--- title: "litellm vs aqueduct" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/berriai-litellm-vs-runllm-aqueduct" tools: ["berriai-litellm", "runllm-aqueduct"] --- # litellm vs aqueduct *GraphCanon updated Aug 3, 2026* ## Verdict Pick litellm if litellm is a Python SDK and Proxy Server that facilitates the interaction with over 100 LLM APIs, offering features such as cost tracking, guardrails, load balancing, and logging; pick aqueduct if aqueduct is a deprecated Go-based tool for orchestrating LLM and ML workloads across various cloud infrastructures with Kubernetes support. [litellm](https://docs.litellm.ai/docs/) reports 55k GitHub stars, 10k forks, and 4.6k open issues, last pushed Aug 1, 2026. [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 [litellm's repository](https://github.com/BerriAI/litellm) and [aqueduct's repository](https://github.com/RunLLM/aqueduct). | | [litellm](/tools/berriai-litellm.md) | [aqueduct](/tools/runllm-aqueduct.md) | | --- | --- | --- | | Tagline | Python SDK and Proxy Server for calling multiple LLM APIs | Orchestrate LLM and ML workloads on any cloud infrastructure using Go. | | Stars | 55,221 | 517 | | Forks | 10,231 | 20 | | Open issues | 4,634 | 11 | | Language | Python | Go | | Adopt for | litellm is a Python SDK and Proxy Server that facilitates the interaction with over 100 LLM APIs, offering features such as cost tracking, guardrails, load balancing, and logging. | Aqueduct is a deprecated Go-based tool for orchestrating LLM and ML workloads across various cloud infrastructures with Kubernetes support. | | Persona | - | - | | Runtime | - | - | | License | The licensing terms for LiteLLM are provided under a license type categorized as 'Other'; details of the exact license should be referenced directly from its source. | Apache-2.0 | | Categories | Inference & Serving, LLM Frameworks | Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [litellm](/tools/berriai-litellm.md) | [aqueduct](/tools/runllm-aqueduct.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 1152d | | Open issues (now) | 4.6k | 11 | | Full report | [trust report](/tools/berriai-litellm/trust.md) | [trust report](/tools/runllm-aqueduct/trust.md) | ## Decision facts: litellm - **Pricing:** freemium - While the core functionality is provided free, specific extended features might require a paid plan. - **Requirements:** Requires Docker - **Adopt for:** litellm is a Python SDK and Proxy Server that facilitates the interaction with over 100 LLM APIs, offering features such as cost tracking, guardrails, load balancing, and logging. - **License detail:** The licensing terms for LiteLLM are provided under a license type categorized as 'Other'; details of the exact license should be referenced directly from its source. ## 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 litellm if… - litellm is primarily Python; aqueduct is Go. - License: litellm is Other, aqueduct is Apache-2.0. - Pricing: While the core functionality is provided free, specific extended features might require a paid plan.. - Requirements: Requires Docker. - Tags unique to litellm: ai-gateway, azure-openai, bedrock, openai. - litellm ships Docker support for self-hosted deployment. - When you need to integrate multiple LLM (Language Learning Modelling) APIs into your application across different providers like Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, Hugging ### Choose aqueduct if… - aqueduct is primarily Go; litellm is Python. - License: aqueduct is Apache-2.0, litellm is Other. - Tags unique to aqueduct: ai, data, data-science, kubernetes. - Also covers Model Training. - 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 litellm - If your project only requires interaction with a single LLM API and basic functionalities, litellm may be overkill. ## 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 litellm and aqueduct? litellm: Python SDK and Proxy Server for calling multiple LLM APIs. 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 litellm over aqueduct? Choose litellm over aqueduct when litellm is primarily Python; aqueduct is Go; License: litellm is Other, aqueduct is Apache-2.0; Pricing: While the core functionality is provided free, specific extended features might require a paid plan.; Requirements: Requires Docker; Tags unique to litellm: ai-gateway, azure-openai, bedrock, openai; litellm ships Docker support for self-hosted deployment; When you need to integrate multiple LLM (Language Learning Modelling) APIs into your application across different providers like Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, Hugging. ### When should I choose aqueduct over litellm? Choose aqueduct over litellm when aqueduct is primarily Go; litellm is Python; License: aqueduct is Apache-2.0, litellm is Other; Tags unique to aqueduct: ai, data, data-science, kubernetes; Also covers Model Training; 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 litellm? If your project only requires interaction with a single LLM API and basic functionalities, litellm may be overkill. ### 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 litellm or aqueduct more popular on GitHub? litellm has more GitHub stars (55,221 vs 517). Stars measure visibility, not whether either tool fits your constraints. ### Are litellm and aqueduct open source? Yes - both are open-source projects on GitHub (litellm: Other, aqueduct: Apache-2.0). ### Where can I find alternatives to litellm or aqueduct? GraphCanon lists graph-backed alternatives at [litellm alternatives](/tools/berriai-litellm/alternatives) and [aqueduct alternatives](/tools/runllm-aqueduct/alternatives) ([litellm markdown twin](/tools/berriai-litellm/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/berriai-litellm-vs-runllm-aqueduct.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, litellm or aqueduct? litellm: Very active. 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 litellm and aqueduct? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [litellm trust report](/tools/berriai-litellm/trust); [aqueduct trust report](/tools/runllm-aqueduct/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=berriai-litellm`](/api/graphcanon/graph?tool=berriai-litellm) - 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/_