---
title: "optillm vs vllm"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/algorithmicsuperintelligence-optillm-vs-vllm-project-vllm"
tools: ["algorithmicsuperintelligence-optillm", "vllm-project-vllm"]
---

# optillm vs vllm

Neutral, constraint-first comparison with live GitHub stats.

| | [optillm](/tools/algorithmicsuperintelligence-optillm.md) | [vllm](/tools/vllm-project-vllm.md) |
| --- | --- | --- |
| Tagline | OptiLLM is an OpenAI API-compatible optimizing inference proxy that enhances LLM accuracy and performance on reasoning tasks without needing to train or fine-tune models. | A high-throughput and memory-efficient inference and serving engine for LLMs |
| Stars | 4,170 | 85,621 |
| Forks | 368 | 19,078 |
| Open issues | 21 | 5,598 |
| Language | Python | Python |
| License | Apache-2.0 | Apache-2.0 |
| Categories | Model Training, Inference & Serving | Model Training, Inference & Serving |

**Typed relationship:** optillm _(related)_ vllm

---

**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/_