Exabits
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About
Exabits provides foundational AI compute infrastructure by transforming raw GPU hardware into optimized, scalable compute services. Unlike simple resellers, the platform acts as a compute refinery, managing the entire stack from hardware and firmware to high-speed networking. This allows businesses to bypass the complexities of building and maintaining their own data centers while accessing elite performance for intensive AI workloads. The infrastructure is built on a global network of 27 data centers located across North America, Europe, and Asia, ensuring regional flexibility and low-latency access. The platform offers a wide range of GPUs, including the latest Nvidia H200 and H100 models, as well as cost-effective RTX 4090s for lighter workloads. It differentiates itself through proprietary AIOps agents that monitor and adjust workloads in real-time to ensure peak efficiency. Networking is a core focus of the service, utilizing 1.6TB/3.2TB InfiniBand for high-tier clusters to eliminate data transfer bottlenecks. Every machine undergoes rigorous burn-in testing with real-world workloads to ensure stability and reliability before being deployed to the user. Exabits is primarily designed for AI enterprises, research labs, and GPU marketplaces that require massive compute power for model training and serving. It also serves the gaming and metaverse industries for 3D rendering and blockchain companies needing validation power. The service bridges the gap between hardware manufacturers like Nvidia and end users who need reliable, managed clusters rather than just raw metal. It is particularly suitable for organizations that have outgrown basic cloud providers and require specialized, high-bandwidth interconnects. What makes the tool unique is its industry-leading deployment speed; large-scale clusters of 1,000 or more H100s can be delivered in just 1-2 months, compared to the typical 4-8 month industry average. Additionally, the platform avoids the volatility of token-subsidized decentralized networks, focusing instead on demand-driven economics and enterprise-grade 24/7 technical support. Their proprietary optimizations claim to enhance performance by 2-7x compared to standard server configurations, providing a superior performance-to-cost ratio for mission-critical AI applications.
Pros & Cons
Delivers large-scale H100 clusters in 1-2 months, beating the 4-8 month industry average.
Provides ultra-high-speed networking with up to 3.2TB InfiniBand interconnections for AI training.
Proprietary optimizations can boost GPU performance by 2-7x over standard hardware setups.
Global infrastructure spanning 27 data centers across North America, Europe, and Asia.
Offers enterprise-grade reliability with rigorous burn-in testing and 99%+ uptime SLAs.
Standard internet bandwidth is limited to 1-10GB unless users pay for dedicated upgrades.
Specific pricing for GPU instances is not publicly disclosed without account registration.
Next-generation chips like the B200 and 5090 are currently listed as upcoming and not yet available.
Minimum deployment for large customized clusters still requires at least one month of lead time.
Use Cases
AI Research Teams can utilize high-performance H100 clusters to train large language models with 99%+ uptime and optimized throughput.
Game Developers can leverage RTX 4090 clusters for high-speed 3D rendering and metaverse application hosting with low latency.
Blockchain Operators can deploy scalable GPU resources for network validation and decentralized application support across global regions.
Enterprise Data Scientists can use the on-demand API to instantly spin up GPU instances for testing and small-scale model serving.
Industrial Enterprises can utilize dedicated data center interconnectivity for long-distance, high-bandwidth data processing tasks.
Platform
Task
Features
• 24/7 technical support
• on-demand api access
• custom supercluster deployment
• firmware-level performance tuning
• global data center network
• infiniband interconnectivity
• aiops workload optimization
• high-performance gpu clusters
FAQs
What types of GPUs are available on the Exabits platform?
Exabits offers a comprehensive range of GPUs including the high-end H200, H100, and A100 models. For more cost-effective needs, users can access RTX 4090, L40, Ada6000, and several other professional-grade cards.
How quickly can a large-scale GPU cluster be deployed?
Large clusters consisting of 1,000 to 2,000+ H100 GPUs can be deployed within 1 to 2 months. This is significantly faster than the standard industry lead time of 4 to 8 months.
What kind of networking infrastructure supports the GPU clusters?
High-performance clusters utilize 1.6TB or 3.2TB InfiniBand interconnections for maximum data throughput. For other configurations, 400GB/800GB RoCE or 25GB-100GB Ethernet options are available depending on the GPU model.
How does Exabits ensure the reliability of its compute resources?
All GPU machines undergo rigorous burn-in testing with real-world workloads to ensure stability before deployment. The platform also offers uptime guarantees ranging from 95% to over 99% depending on specific customer requirements.
What makes Exabits different from decentralized GPU providers?
Unlike decentralized providers that rely on token subsidies, Exabits operates on demand-driven economics with real-world AI enterprise revenue. This approach ensures long-term stability, enterprise-grade security, and consistent service quality.
Pricing Plans
On-Demand GPU Cloud
Unknown Price• Instant API access
• Public GPU cloud
• AIOps monitoring
• Standard ethernet (25-100GB)
• 1-10GB shared bandwidth
• Self-service registration
Enterprise Supercluster
Unknown Price• H100/H200 dedicated clusters
• 1.6TB/3.2TB InfiniBand
• 99%+ uptime SLA
• 1-2 month deployment speed
• Burn-in tested hardware
• 24/7 technical support
Job Opportunities
There are currently no job postings for this AI tool.
Ratings & Reviews
No ratings available yet. Be the first to rate this tool!
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