Provider Overview
Strengths & Best For
Cerebrium is a serverless ML infrastructure platform that deploys H100, A100, and T4 GPU workloads in seconds using custom containers, enabling real-time LLM inference and fine-tuned model serving without managing any infrastructure. Per-second billing and fast cold starts make it highly cost-efficient for bursty AI inference APIs and model deployment pipelines. A top choice for ML teams that want to ship production inference endpoints quickly with minimal DevOps overhead.
- Serverless deployment
- Fast cold starts
- Custom containers
- Simple pricing
Lyceum is an academic GPU cloud offering H100 and A100 instances with research-friendly policies, flexible on-demand pricing, and configurations tailored for AI experimentation and academic research teams. Accessible pricing and a focus on the research community make it a practical option for universities and independent researchers who need GPU compute for LLM experimentation and model training without enterprise overhead. A strong choice for academic AI teams that want affordable, flexible GPU access.
- Research-friendly
- Flexible pricing
- Academic focus
Live GPU Pricing
Region Coverage
Popular Comparisons
Cerebrium — specialist provider
Cerebrium is a serverless ML infrastructure platform that deploys H100, A100, and T4 GPU workloads in seconds using custom containers, enabling real-time LLM inference and fine-tuned model serving without managing any infrastructure. Per-second billing and fast cold starts make it highly cost-efficient for bursty AI inference APIs and model deployment pipelines. A top choice for ML teams that want to ship production inference endpoints quickly with minimal DevOps overhead.
Lyceum — specialist provider
Lyceum is an academic GPU cloud offering H100 and A100 instances with research-friendly policies, flexible on-demand pricing, and configurations tailored for AI experimentation and academic research teams. Accessible pricing and a focus on the research community make it a practical option for universities and independent researchers who need GPU compute for LLM experimentation and model training without enterprise overhead. A strong choice for academic AI teams that want affordable, flexible GPU access.
Billing model comparison
Cerebrium uses a Per-second usage billing model with a minimum commitment of None. Lyceum uses On-demand billing with a None minimum. Both providers offer flexible billing options — compare the live pricing table above to find the best rate for your specific GPU model and workload duration.
Which workloads each provider suits best
Cerebrium is best suited for: Real-time inference APIs, Model deployment, Serverless AI. Its key strengths are serverless deployment, fast cold starts, custom containers. Lyceum is best suited for: Academic research, AI experimentation, Small teams. Its key strengths are research-friendly, flexible pricing, academic focus. Both providers target similar workload profiles — the live pricing table above is the most reliable way to determine which offers better value for your specific GPU model and region requirements.
Support tiers and region coverage
Cerebrium offers Standard support across 2 regions (US, EU). Lyceum offers Standard support across 1 region (US). Cerebrium's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: Cerebrium vs Lyceum
Cerebrium was founded in 2022 and is headquartered in Cape Town, South Africa. Lyceum was founded in 2023 and is headquartered in United States. Cerebrium has 1 years more operational history than Lyceum, which may matter for teams evaluating provider stability and long-term contract risk. Use the live pricing table above to compare current on-demand and spot rates for specific GPU models, and the region map to verify coverage in your target geography.