Zibra Labs
Distributed runtime for AI workloads at scale
Based based in San Francisco, CA, USA, Zibra Labs works in b2b.
Profile
We build distributed compute clusters with the cheapest CPUs and GPUs across Hyperscalers and Neoclouds for AI. Our mission is to bring frontier-grade infrastructure to everyone.
We're starting by building large scale high performance computing (HPC) clusters for quantitative trading firms to run parallel simulation workloads such as backtesting.
Our technology generalizes to critical AI workloads such as post-training with reinforcement learning, fine-tuning, long-horizon agents with high tool use, and batch inference.
Its activity falls under b2b; the profile below is assembled from public directory data.
The company is recorded as being based in San Francisco, CA, USA.
Directory data places it at the Spring 2026 stage.
Its team size is recorded as 2 employees.
Directory analysis
Zibra Labs builds distributed compute clusters that leverage inexpensive CPUs and GPUs across hyperscalers and neoclouds to deliver high‑performance AI workloads. The company focuses initially on large‑scale HPC clusters for quantitative trading firms, enabling parallel simulation and back‑testing. Its technology is designed to generalize to other AI tasks such as reinforcement learning fine‑tuning, long‑horizon agent training, and batch inference.
Positioning: Zibra Labs positions itself as a low‑cost, high‑performance compute platform targeting enterprises that require large‑scale AI or HPC workloads, such as quantitative finance and advanced AI training. By targeting hyperscaler and neocloud resources, it seeks to compete with traditional cloud providers and specialized HPC vendors.
Note: Zibra Labs offers a distributed runtime for AI workloads that emphasizes cost efficiency and scalability.
Auto-generated directory analysis from public data · updated 7 Oct 2026. Informational only, not investment advice.
| Sector | B2B |
|---|---|
| Headquarters | San Francisco, CA, USA |
| Country | USA |
| Employees | 2 |
| Stage | Spring 2026 |
Website: zibralabs.ai
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