--- title: "optillm vs optimate" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/algorithmicsuperintelligence-optillm-vs-nebuly-ai-optimate" tools: ["algorithmicsuperintelligence-optillm", "nebuly-ai-optimate"] --- # optillm vs optimate *GraphCanon updated Sep 20, 2026* ## Verdict Pick optillm if optillm is an optimizing inference proxy for LLMs that provides enhanced deployment options through Docker, supporting both full and lightweight configurations; pick optimate if optiMate is a legacy collection of Python libraries for optimizing AI models, including Speedster for inference cost reduction, Nos for infrastructure cost reduction, and ChatLLaMA for hardware and data cost reduction. [optillm](https://github.com/algorithmicsuperintelligence/optillm) reports 4.2k GitHub stars, 385 forks, and 25 open issues, last pushed Jul 18, 2026. [optimate](https://www.nebuly.com/) has 8.3k stars, 613 forks, and 109 open issues, last pushed Jul 22, 2024. Figures are from public GitHub metadata via [optillm's repository](https://github.com/algorithmicsuperintelligence/optillm) and [optimate's repository](https://github.com/nebuly-ai/optimate). | | [optillm](/tools/algorithmicsuperintelligence-optillm.md) | [optimate](/tools/nebuly-ai-optimate.md) | | --- | --- | --- | | Tagline | Optimizing inference proxy for LLMs | A collection of libraries to optimise AI model performances | | Stars | 4,244 | 8,328 | | Forks | 385 | 613 | | Open issues | 25 | 109 | | Language | Python | Python | | Adopt for | optillm is an optimizing inference proxy for LLMs that provides enhanced deployment options through Docker, supporting both full and lightweight configurations. | OptiMate is a legacy collection of Python libraries for optimizing AI models, including Speedster for inference cost reduction, Nos for infrastructure cost reduction, and ChatLLaMA for hardware and data cost reduction. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | OptiMate is licensed under Apache-2.0, allowing for free use, modification, and distribution. | | Categories | Inference & Serving | Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [optillm](/tools/algorithmicsuperintelligence-optillm.md) | [optimate](/tools/nebuly-ai-optimate.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Dormant (18%) | | Days since push | 30d | 788d | | Open issues (now) | 25 | 109 | | Stars delta | +67 (30d) | -1 (30d) | | Open issues delta | +5 (30d) | -1 (30d) | | Full report | [trust report](/tools/algorithmicsuperintelligence-optillm/trust.md) | [trust report](/tools/nebuly-ai-optimate/trust.md) | ## Decision facts: optillm - **Hosting:** self hosted - This open-source proxy supports diverse hosting environments and can be run via Docker for flexibility in deployment. - **Pricing:** freemium - optillm is available under the Apache-2.0 license, which makes it free to use and distribute without cost. - **Adopt for:** optillm is an optimizing inference proxy for LLMs that provides enhanced deployment options through Docker, supporting both full and lightweight configurations. ## Decision facts: optimate - **Requirements:** OptiMate is a legacy project and no longer actively maintained, so users should be prepared to handle any issues without official support. - **Adopt for:** OptiMate is a legacy collection of Python libraries for optimizing AI models, including Speedster for inference cost reduction, Nos for infrastructure cost reduction, and ChatLLaMA for hardware and data cost reduction. - **License detail:** OptiMate is licensed under Apache-2.0, allowing for free use, modification, and distribution. ## Choose when ### Choose optillm if… - This open-source proxy supports diverse hosting environments and can be run via Docker for flexibility in deployment. - Pricing: optillm is available under the Apache-2.0 license, which makes it free to use and distribute without cost.. - Tags unique to optillm: agent, agentic-ai, genai, llm-inference. - optillm ships Docker support for self-hosted deployment. - Use optillm when you require automatic optimization of the server approach to enhance reasoning capabilities with large language models. ### Choose optimate if… - Requirements: OptiMate is a legacy project and no longer actively maintained, so users should be prepared to handle any issues without official support.. - Tags unique to optimate: ai, analytics, artificial-intelligence, deeplearning. - Also covers Model Training. - When you need to leverage legacy optimization techniques for reducing inference costs with Speedster, infrastructure costs with Nos, and hardware and data costs with ChatLLaMA. ## When NOT to use optillm - Avoid optillm when your application does not require proxy server optimization for large language models; simpler serving setups may suffice. - Do not use optillm if your deployment environment strictly prohibits the use of Docker images or containers, given that this tool heavily relies on Docker for its various configurations. ## When NOT to use optimate - If you require the latest optimization techniques and ongoing support, as OptiMate is in a legacy phase and no longer actively maintained. - When you need to integrate with modern AI frameworks that require the latest updates and patches, as OptiMate does not receive these updates. ## Common questions ### What is the difference between optillm and optimate? optillm: Optimizing inference proxy for LLMs. optimate: A collection of libraries to optimise AI model performances. See the comparison table for live GitHub stats and shared categories. ### When should I choose optillm over optimate? Choose optillm over optimate when This open-source proxy supports diverse hosting environments and can be run via Docker for flexibility in deployment; Pricing: optillm is available under the Apache-2.0 license, which makes it free to use and distribute without cost.; Tags unique to optillm: agent, agentic-ai, genai, llm-inference; optillm ships Docker support for self-hosted deployment; Use optillm when you require automatic optimization of the server approach to enhance reasoning capabilities with large language models. ### When should I choose optimate over optillm? Choose optimate over optillm when Requirements: OptiMate is a legacy project and no longer actively maintained, so users should be prepared to handle any issues without official support.; Tags unique to optimate: ai, analytics, artificial-intelligence, deeplearning; Also covers Model Training; When you need to leverage legacy optimization techniques for reducing inference costs with Speedster, infrastructure costs with Nos, and hardware and data costs with ChatLLaMA. ### When should I avoid optillm? Avoid optillm when your application does not require proxy server optimization for large language models; simpler serving setups may suffice. Do not use optillm if your deployment environment strictly prohibits the use of Docker images or containers, given that this tool heavily relies on Docker for its various configurations. ### When should I avoid optimate? If you require the latest optimization techniques and ongoing support, as OptiMate is in a legacy phase and no longer actively maintained. When you need to integrate with modern AI frameworks that require the latest updates and patches, as OptiMate does not receive these updates. ### Is optillm or optimate more popular on GitHub? optimate has more GitHub stars (8,328 vs 4,244). Stars measure visibility, not whether either tool fits your constraints. ### Are optillm and optimate open source? Yes - both are open-source projects on GitHub (optillm: Apache-2.0, optimate: Apache-2.0). ### Where can I find alternatives to optillm or optimate? GraphCanon lists graph-backed alternatives at [optillm alternatives](/tools/algorithmicsuperintelligence-optillm/alternatives) and [optimate alternatives](/tools/nebuly-ai-optimate/alternatives) ([optillm markdown twin](/tools/algorithmicsuperintelligence-optillm/alternatives.md), [optimate markdown twin](/tools/nebuly-ai-optimate/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/algorithmicsuperintelligence-optillm-vs-nebuly-ai-optimate.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, optillm or optimate? optillm: Steady. optimate: 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 optillm and optimate? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [optillm trust report](/tools/algorithmicsuperintelligence-optillm/trust); [optimate trust report](/tools/nebuly-ai-optimate/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=algorithmicsuperintelligence-optillm`](/api/graphcanon/graph?tool=algorithmicsuperintelligence-optillm) - 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/_