CPUIntel i7-13700KF16 cores / 24 threads
GPURTX 407012 GB VRAM
Memory32 GBSystem RAM
Local modelQwen3-8BQ4_K_M
WHY PINF EXISTS
AI capability has a physical boundary.
PINF connects device capacity, model runtime, and workload behavior. It turns CPU, GPU, memory, storage, quantization, context, and concurrency into an explicit operating model for local AI.
COMPUTE BOUNDARY
Default local workload
Model class7B-9B Q4
Suitable for local tool use, structured extraction, document triage, RAG assistance, and low-risk Agent work.
Default context8K tokens
Context and concurrency are controlled because KV cache, desktop workloads, and runtime overhead share the same device.
AI INFRA CAREER LENS
Build evidence one infrastructure layer at a time.
01DeviceInventory, placement, capacity, policy
02ServingLatency, throughput, context, concurrency
03ReliabilityTelemetry, SLO, incidents, recovery
04ScaleContainers, scheduling, multi-node systems
CONTROL DOMAINS
One normalized device snapshot
01ObserveWindows CIM, NVIDIA, Ollama, Docker
02NormalizeTyped hardware and runtime snapshot
03EvaluateCapacity model and policy thresholds
04PresentDoctor output and local dashboard
LOCAL MODEL POLICY
System disk is not model storage.
- Runtime, model weights, and temporary model files use a dedicated data volume.
- Local models are unloaded from VRAM when a task finishes.
- Cloud escalation remains available for difficult reasoning.
- Deletion, migration, and runtime shutdown require human approval.