Practical AI guides
Inference & deployment
Understand serving architectures, hardware requirements, and the conditions behind performance claims.
Where to start
Read throughput and latency claims alongside model size, hardware, concurrency, and workload. An optimization that helps a busy server may introduce unnecessary complexity for a small deployment.
- Does the documented hardware match your deployment?
- Is the bottleneck compute, memory, or scheduling?
- Which operating costs sit outside the headline benchmark?
Explore the reports
KServe: choosing the Kubernetes serving mode your models need
5.9Kstars
OpenVINO: choosing a deployment path for your model and hardware
10.8KstarsBifrost AI Gateway: what its latency numbers actually measure
7.7Kstars
Spice: choosing between federated queries and local acceleration
3.1Kstars