sglang vs vllm

Common questions

What is the difference between sglang and vllm?

sglang: High-performance serving framework for large language and multimodal models. vllm: A high-throughput and memory-efficient inference and serving engine for LLMs. See the comparison table for live GitHub stats and shared categories.

When should I choose sglang over vllm?

Choose sglang over vllm when SGLang and vllm both aim at providing easy and fast LLM serving solutions but use different approaches to achieve high performance in inference; Tags unique to sglang: attention, diffusion, llm, moe; - When you need to deploy large language or multimodal models efficiently across various types including transformers and diffusion models.

When should I choose vllm over sglang?

Choose vllm over sglang when Pricing: vLLM operates under the Apache-2.0 license, so it's entirely free to use without direct monetary costs, but users might incur costs related to hardware and cloud services required for deployment.; Requirements: Installation can be done via uv pip install vllm or by building from source, allowing flexibility in how the tool is set up.; SGLang and vllm both aim at providing easy and fast LLM serving solutions but use different approaches to achieve high performance in inference; Tags unique to vllm: amd, deepseek, gpt, llama; When you need to deploy large language models with requirements for both high throughput and low resource consumption.

When should I avoid sglang?

- Avoid using SGLang if your project or infrastructure already heavily relies on specific serving solutions that do not integrate easily with Python deployments. - If real-time performance is less critical than maintaining a lightweight and easy-to-deploy framework, another more specialized tool might be preferable. - For projects where the model types are limited to those beyond large language models (LLMs) or multimodal models, such as strictly CNNs or RNNs without a need for transformer support, SGLang may not

When should I avoid vllm?

Avoid using vLLM if your application strictly limits itself to a single type of hardware without needing cross-platform compatibility, as it may introduce unnecessary complexity. If memory efficiency is not a concern and you are optimizing for simplicity over resource management, alternatives with less configuration might be preferable.

Is sglang or vllm more popular on GitHub?

vllm has more GitHub stars (87,847 vs 31,454). Stars measure visibility, not whether either tool fits your constraints.

Are sglang and vllm open source?

Yes - both are open-source projects on GitHub (sglang: Apache-2.0, vllm: Apache-2.0).

Where can I find alternatives to sglang or vllm?

GraphCanon lists graph-backed alternatives at sglang alternatives and vllm alternatives (sglang markdown twin, vllm markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

Which is better maintained, sglang or vllm?

sglang: Very active. vllm: Very active. 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 sglang and vllm?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: sglang trust report; vllm trust report.