ZibraLabs
Frontier-grade AI infrastructure for everyone
ZibraLabs builds distributed compute clusters that combine low-cost CPUs and GPUs across hyperscalers and neoclouds for AI workloads. The platform runs massively parallel workloads, including backtesting and large parameter sweeps, post-training and reinforcement learning, multi-modal data processing, batch inference, and long-horizon agentic workloads.
Its engine is designed to scale to clusters of 100 to 50,000 nodes, with millions of tasks in flight, dispatch and scheduling overhead under 50 ms, and spot instances across regions and providers. The company was founded by engineers who previously worked on systems at LinkedIn and on Ray, the open-source compute platform.
ZibraLabs targets teams that need to run large compute workloads and make effective use of CPUs and GPUs. Contact is arranged through a scheduled call.
12 alternatives to ZibraLabs
Ranked by how well each tool replaces ZibraLabs: shared features, audience, price and popularity.
- 61 out of 100 matchUsage-based
Zaphira Agentic Data Platform that decouples AI agents from existing Java applications and
59 out of 100 match—Deploy and scale AI workloads on serverless GPUs with Cerebrium's sub-second cold starts
Has a free plan.
Free plan58 out of 100 match$100/moVector database for AI, powered by Milvus
Has a free plan and is open source.
Free planOpen source57 out of 100 match$197/mo