11× faster ttft
680ms vs 7+ seconds
Time to first token
A new model drops. Generic endpoints are still optimized for everyone. SwarmOptimizer simulates your real agentic workloads and tunes the stack to yours.
The missing layer.
11× faster ttft
680ms vs 7+ seconds
Time to first token
3.5× faster decode
106 vs 47-50 tok/s/user
Per-user decode speed
OPTIMIZED COST
80% lower cost
On existing GPU hardware
Existing GPU hardware
Published speed numbers are often 1k/1k or about 20k context. Real agentic traffic is 100-150k, multi-turn, with tool calls. On that load, public endpoints often drop to 20-30 tok/s per user. SwarmOne reached 140 tok/s per user on real agentic workloads.
Providers cannot subsidize inference anymore. Your workloads are consuming tokens faster than anyone predicted. SwarmOne finds the configuration that makes every token count.
100-150
Commodity hardware typically lands at 30-40 tokens per second per user on real agentic traffic. After optimization: 100-150. Specialized hardware: 300-600.
Deploy, simulate real agentic traffic at fleet scale, optimize across software and hardware, redeploy. The simulator is the ground truth, so the AI cannot cheat. Repeats every 24 hours.
01
Understand real behavior
A few real traces in. A stack that matches production out. SwarmSimulator is the ground truth. SwarmOptimizer tunes the serving stack against it.
Honest workload simulation
Stop guessing. Start simulating. Copying the same traces cheats. SwarmSimulator takes 1-3 real recordings, grows them into tens of thousands of conversations, and runs them at fleet scale so the numbers match production.
Record: 1-3 real agent traces and tool calls
Perturb: Same work, new conversations
Simulate: Tens of thousands of fleet-scale conversations
Match: Numbers the optimizer can trust
The full solution
Recursively optimizes your inference stack: serving knobs, env vars, KV cache policy, routing, kernels, and optionally source. Uses SwarmSimulator as unbiased ground truth. Plug in SwarmOne's optimizer or yours.
Knobs-only: typically 5-8× vs generic untuned stacks
KV cache analysis across hundreds of policies
24h continuous re-optimization
Works with your optimizer or ours
SwarmOptimizer works across any silicon, any cloud, any framework. Live cluster for highest fidelity. Vendor simulator (like NVIDIA DynoSim) for speed. No rewrites. No lock-in.
SILICON
The price war between OpenAI and Anthropic will not save you. Your workloads will just consume more. SwarmOptimizer continuously simulates, optimizes, and deploys. Automatically.
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