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AgentOps vs vLLM

vLLM leads in package downloads at 9x; vLLM leads in npm dependents with 3; both compete in AI Infrastructure. Updated daily with live metrics.

Key Differences

vLLM leads in package downloads with 5.6M per month compared to 633.3K for AgentOps. vLLM has 72.3K GitHub stars versus 5.3K for AgentOps. vLLM is depended on by 3 npm packages versus 2 for AgentOps.

AgentOps has raised $3M in total funding. AgentOps's most recent round was Seed. both companies operate in the AI Infrastructure category.

vLLM received 86 Hacker News mentions in the last 30 days compared to 6 for AgentOps. vLLM accounts for 5.2% of Hacker News discussion in its category.

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Quick Comparison

AgentOps: 633.3K downloads/mo, 5.3K GitHub stars, 2 dependents, $3M funded vs

vLLM: 5.6M downloads/mo, 72.3K GitHub stars, 342 active contributors, 3 dependents

Source: AI-Buzz AI company database.

Key Differences
  • vLLM leads in package downloads with 5.6M/mo (9x AgentOps)
  • vLLM has 72.3K GitHub stars (14x more)
  • vLLM has 3 npm dependents (2x more than AgentOps)

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MetricAgentOpsvLLM
Websiteagentops.ai vllm.ai
DescriptionObservability and testing platform for AI agentsFast LLM inference engine. High-throughput serving for LLMs.
Total Funding
$3M
-
Last Funding
Seed
Feb 2024
Not available
Developer Adoption
npm Downloads (30d)
423
30.2K
PyPI Downloads (30d)
632.9K
5.5M
Total Downloads (30d)
633.3K+0%
5.6M+0%
Active Contributors (30d)
0
342
npm Dependents
2
3
HN Discussion Share0.4% of HN mentions5.2% of HN mentions
StatusPrivatePrivate
HN Mentions (30d)
6
86
HN Mentions Trend (30d)--
GitHub Stars
5.3K
72.3K
Founded20232023
Primary Category
Data Last Updated

Key Differences: AgentOps vs vLLM

In developer adoption, vLLM leads with 5.6M package downloads per month — roughly 9x the 633.3K downloads AgentOps receives. Both companies have packages on npm and PyPI.

AgentOps has raised $3M in funding, while vLLM does not have disclosed funding data. AgentOps's latest round was a Seed in 2024.

On GitHub, vLLM has 72.3K GitHub stars, 14x more than AgentOps's 5.3K.

In community signals, vLLM leads in Hacker News mindshare with 86 mentions in the past 30 days compared to 6 for AgentOps. Also, npm dependents are comparable at 2 for AgentOps and 3 for vLLM.

Both AgentOps and vLLM operate in the AI Infrastructure space, making them direct competitors for developer mindshare.

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