SGLang vs CoreWeave — Comparison

SGLang

SGLang is a high-performance serving framework for large language models and multimodal models. - sgl-project/sglang

SGLang is a high-performance serving framework for large language models and multimodal models. It is designed to deliver low-latency and high-throughput inference across a wide range of setups, from a single GPU to large distributed clusters. Its core features include: SGLang has been deployed at large scale, generating trillions of tokens in production each day. It is trusted and adopted by a wide range of leading enterprises and institutions, including xAI, AMD, NVIDIA, Intel, LinkedIn, Cursor, Oracle Cloud, Google Cloud, Microsoft Azure, AWS, Atlas Cloud, Voltage Park, Nebius, DataCrunch, Novita, InnoMatrix, MIT, UCLA, the University of Washington, Stanford, UC Berkeley, Tsinghua University, Jam Tea Studios, Baseten, and other major technology organizations. As an open-source LLM inference engine, SGLang has become the de facto industry standard, with deployments running on over 400,000 GPUs worldwide. SGLang is currently hosted under the non-profit open-source organization LMSYS. For enterprises interested in adopting or deploying SGLang at scale, including technical consulting, sponsorship opportunities, or partnership inquiries, please contact us at sglang@lmsys.org. Long-term active SGLang contributors are eligible for coding agent sponsorship, such as Cursor, Claude Code, or OpenAI Codex. Email sglang@lmsys.org with your most important commits or pull requests. SGLang is a high-performance serving framework for large language models and multimodal models. There was an error while loading. Please reload this page. There was an error while loading. Please reload this page. There was an error while loading. Please reload this page. There was an error while loading. Please reload this page.

CoreWeave

CoreWeave is the force multiplier that empowers pioneers with momentum, magnitude, and mastery—enabling them to innovate with confidence. Explore the

Based on the limited social mentions provided, there's insufficient data to provide a comprehensive summary of user sentiment about CoreWeave. The mentions consist primarily of YouTube videos with minimal descriptive content and Reddit posts that focus on business deals (like the CoreWeave x Perplexity partnership) and technical discussions about AI infrastructure rather than user experiences. Without actual user reviews or detailed social commentary about CoreWeave's services, pricing, or performance, I cannot accurately summarize user opinions about their strengths, complaints, or overall reputation.

SGLang

CoreWeave

SGLang

CoreWeave

SGLang

CoreWeave