vLLM vs Scale AI

Scale AI has a disclosed valuation of $29B, while vLLM's valuation is not publicly available, making a direct size comparison difficult. Scale AI employs 1,000 people.

Scale AI has raised $15.9B in disclosed funding across 5 known rounds. vLLM's funding history is not publicly available.

Scale AI leads with an Awaira Score of 84/100, while vLLM sits at 45/100. That 39-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

vLLM was founded by Woosuk Kwon in 2023. Scale AI was founded by Alexandr Wang in 2016. Visit each company's profile on Awaira for a full founder biography.

vLLM: vLLM is an open-source high-throughput and memory-efficient inference and serving engine for large language models, developed initially at UC Berkeley and widely adopted in production AI deployments. The project introduced PagedAttention, a novel memory management technique that significantly increases GPU utilization during LLM inference by managing key-value cache memory analogously to how operating systems manage virtual memory pages.\n\nThe engine is used in production by AI infrastructure teams at major technology companies, AI labs, and cloud providers who need to maximize the number of concurrent LLM requests served per GPU. vLLM benchmarks consistently demonstrate throughput improvements of 10 to 20 times over naive inference implementations, translating directly into lower cost per inference query at scale. The project is maintained by a community of contributors from both academia and industry.\n\nHigh-throughput LLM serving infrastructure is foundational to the economics of AI deployment. As inference costs represent an increasing share of AI operating budgets, the performance characteristics of the serving engine directly determine the financial viability of AI-powered products. vLLM dominant position in open-source LLM serving gives it deep adoption among infrastructure engineers and makes it a reference implementation against which commercial serving solutions are measured. Scale AI: Scale AI is a data infrastructure company founded in 2016 that specializes in data labeling and annotation services for artificial intelligence model development. The company provides managed workforce solutions and software platforms that enable organizations to prepare high-quality training data at scale. Scale AI's core offerings include data labeling, model evaluation, data generation, and managed workforce services across computer vision, natural language processing, and other AI domains. The company serves enterprise customers across automotive, defense, technology, and other sectors requiring large-scale data annotation for machine learning applications. Notable use cases include autonomous vehicle development, where precise labeled data is critical for training perception systems. Scale AI operates a hybrid model combining software automation with human-in-the-loop annotation capabilities. With a Series F valuation of $13.8 billion and total funding of $1.6 billion, Scale AI represents one of the highest-valued data infrastructure companies in the AI stack. The company competes in the data labeling market alongside firms like Labelbox, Snorkel AI, and various in-house solutions deployed by large technology companies. Its growth trajectory reflects increasing enterprise demand for quality training data as AI model development accelerates. Scale AI's positioning emphasizes enterprise-grade reliability, security, and quality assurance in data preparation workflows. Scale AI has achieved unicorn valuation by solving the critical bottleneck of high-quality labeled data production at enterprise scale.

Scale AI got there first, launching in 2016 — that's 7 years of extra runway. vLLM didn't arrive until 2023. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

vLLM has about 1-50 employees; Scale AI has about 1,000. A bigger team usually means more revenue or heavier VC backing, but in AI, small teams can build at massive scale.

Yes — they're direct rivals. Both vLLM and Scale AI compete in AI Infrastructure, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.