IBM & TOGETHER AI $240M INFERENCE ARCHITECTURE

AI Inference Cluster Economics & Capacity Planner

Real-time compute scaling, memory bandwidth bottlenecking & capital payback model
Cluster Architecture Specs H100 SXM5 / B200
GPU Count (Nvidia H100) 8,192 GPUs
Capital Outlay (CaPex) $240M
Amortization Horizon 36 Months
Avg Prompt Length 512 Tokens
Avg Completion Length 256 Tokens
Active Concurrent Streams 250,000
Interconnect Bandwidth 3,200 Gbps
Target Price Metric 1.5M Tokens/$
Unit Inference Cost
$0.18
Per 1,000,000 Generated Tokens
Peak Token Throughput
12.8M t/s
Cluster Aggregate Capacity
Monthly Operating Amortization
$7.85M
CaPex + Cloud Hosting Overhead
Economics Payback
18.4 Mo
Break-even at $0.50/M tokens
Cluster Architecture Topology 8,192 GPUs / 1,024 Nodes
Current Bottleneck State: Memory Bandwidth (KV-Cache Bound)
KV-CACHE LIMIT
Unit Cost Curve vs Concurrency Scale 1.5M Tokens/$ Target
Monthly Token Volume Output: 33.1 Billion Tokens
Deployment Configuration Spec Payload Live Json Schema Output
{ "status": "initializing..." }
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