Cloud Region: US-East-1 | 450 gCO₂/kWh
Optimization Strategies
Temporally shift workloads to run at times with lower carbon intensity.
Optimization Suggestion:
Shift Job #9C2D0 to start in 3 hours
Potential Emissions Saved: ~450 gCO₂
Potential Cost Saved: $0.72
Assign workloads to hardware tiers based on lifecycle and performance needs.
New GPUs
Mid-life
End-of-life
Assign Job #8A4B1 (Low-priority) to Tier 3
Age: 4.2 yrs
Wear: 78%
Energy Amort.: 95%
Route queries to the most efficient model that meets confidence thresholds.
Input Query
Routing Logic
Confidence > 95%?
Tier 1
Tier 2
Tier 3
Current Route: Input -> Tier 3 Model
Confidence Score: 98.2%
Automatically put idle models to sleep to save energy.
Enable Sleep Mode
Reload Latency
350ms
Est. Energy Saved
12 kWh/day
Reduce redundant computation with batching, throttling, and caching.
| Endpoint | Avg. Latency | Reqs/min | Batching | Throttling | Caching |
|---|---|---|---|---|---|
| /v1/generate | 120ms | 85 | |||
| /v1/embed | 45ms | 250 | |||
| /v1/classify | 80ms | 150 |