Cerebrium - 2026 Pricing, Features, Reviews & Alternatives

Cerebrium is a cloud-based serverless GPU infrastructure platform built for engineering teams and AI-focused companies deploying real-time and high-performance AI workloads at scale. The platform supports large language model inference, voice agent pipelines, image and video generation, computer vision, batch processing, and LLM fine-tuning across 12+ chip types including B200, H100, H200, L40s, and AMD MI300X. Workloads run across multiple cloud providers and regions with no Kubernetes, capacity planning, or infrastructure management required. Existing Dockerfiles and entry points deploy without rewrites, decorators, or custom SDKs.

Core infrastructure capabilities include sub-second to 2-second cold starts, memory and GPU snapshotting for fast container restores, and instant autoscaling across thousands of GPUs. Per-second billing covers GPU, CPU, and memory with no idle charges and no billing during cold starts. Multi-region deployment supports data residency requirements, and multi-region failover routing maintains availability for bursty or latency-sensitive workloads. Inference engine support spans vLLM, SGLang, and TensorRT-LLM, with static, dynamic, and continuous batching options. Co-located STT, LLM, and TTS pipelines deliver sub-500ms latency for real-time voice workloads. Endpoints are available via REST, streaming, WebSocket, and OpenAI-compatible interfaces, with support for async requests, webhook forwarding, custom domains, and inter-cluster routing.

Cerebrium targets industries including voice AI, generative AI, computer vision, healthcare AI, and enterprise AI. The platform holds SOC 2 Type II certification and supports GDPR and HIPAA compliance requirements. Container isolation is enforced via gVisor. Full request-level observability is included, along with CI/CD pipeline support, gradual rollouts, and integrations with Deepgram, AssemblyAI, Rime, Resemble AI, LiveKit, and Pipecat. Volume discounts and longer-term commitment pricing are available for larger deployments.