Same tasks. Different intelligence. Real benchmark on MSI desktop (GTX 1650, 4GB VRAM, 8 threads): 5 tasks, 506 tokens, $0.00 cloud spend. Every task ran locally on qwen2.5-coder:7b.
Real benchmark · MSI desktop · GTX 1650 · 5 tasks · 100% local
Task
Model
Latency
Cost
Review Python function for bugs
qwen2.5-coder:7b
→
30,123ms
$0.00
Write Google-style docstring
qwen2.5-coder:7b
→
50,475ms
$0.00
Rename variable 'data' → 'records'
qwen2.5-coder:7b
→
10,181ms
$0.00
Explain TCP vs UDP in 2 sentences
qwen2.5-coder:7b
→
15,321ms
$0.00
Classify bug ticket category
qwen2.5-coder:7b
→
8,649ms
$0.00
Fleet total · 5 tasks · 506 tokens · avg 23s/task
$0.00
Every task ran locally on GTX 1650 (4GB VRAM). No cloud. No API keys. No telemetry. This is what "AI Infrastructure OS" means in practice.
Or pick a real example:
🧠 Routing Trace — how OmniAgent split this task
—
money saved on this one task
All-Claude-Sonnet (typical)
—
OmniAgent (smart mix)
—
🎯
Smart routing
Picks the cheapest model that can handle the task. Tries local first, falls back to cloud only when needed.
💰
Cost transparency
See exactly what every agent, every model, every project costs. Per token. Per call. Per day.
🛡️
Guardian++
Detects secrets, blocks destructive commands, verifies commits. Rolls back on critical failures.
🏠
100% local
Runs on your hardware. No telemetry. No vendor lock-in. Bring your own keys or use free local models.
Stop guessing. Start saving.
OmniAgent is open source, runs on a Raspberry Pi or a beast, and pays for itself the first time you route a task to a local model.