Bedrock Overview
Bedrock (Latest) by AWS provides GPU-accelerated inference with features: Managed foundation models, Titan, Llama, Claude, Mistral, Stable Diffusion, multi-model endpoints... It achieves N/A (managed), pay per token or per hour throughput on H100 GPUs. License: Commercial, AWS integrated.
Performance Benchmarks
On H100 80GB with Llama 4 Scout (17B) at FP8: prefill throughput: 13,216 tokens/second; decode throughput: 3672 tokens/second per user with 733 max batch; TTFT (time to first token): 32ms; inter-token latency: 6ms. GPU utilization: N/A (managed).
Feature Comparison
Key features: Managed foundation models, Titan, Llama, Claude, Mistral, Stable Diffusion, multi-model endpoints... Unique strengths: Managed foundation models Titan Llama. Production features include: distributed tracing, request queuing, rate limiting.
Cost-Per-Token Analysis
Cost-per-token on H100 80GB at $2.50/hr: input tokens: $0.000026/1K tokens; output tokens: $0.000250/1K tokens with Bedrock. At 50% utilization, cost-per-million tokens: $137-$229 for output tokens, depending on batch size and model size. Reserved pricing reduces costs by 30-50%.
Production Deployment
Deploy Bedrock in production: containerized deployment with Docker + NVIDIA Container Toolkit; Kubernetes with GPU node pools; monitoring with Prometheus + GPU metrics; horizontal scaling with HAProxy + keepalived; and CI/CD integration for model updates. Recommended: 4x H100/B200 GPUs per node with NVLink.
When to Choose Bedrock
Choose Bedrock when: Managed foundation models Titan are critical for your workloads; Commercial, AWS integrated license model fits your budget; and your team has experience with AWS's ecosystem. Consider alternatives when: specific hardware optimization is needed, team familiarity with other frameworks, or license costs are prohibitive for your scale.