Live Compute Proof · IEEE-754 Enforced

Deterministic Engineering Compute
Reproducible simulations for certification-grade systems

QOMN is not a language model. It is a physics-class deterministic compute engine —
designed for engineering simulations, reproducible results, and certification workflows.

LIVE · Numbers pulled from server · Auto-refresh 15s

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Scenarios / second

Full IEEE-754 plan evaluation

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Pareto latency

170 optimal solutions per call

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Parameter sweep / 12 s

Bounded engineering input space

0.0

Variance across runs

Bit-identical · IEEE-754 exact

Values measured in real-time. Throughput fluctuates with CPU load — this is expected behavior for a live compute server.

QOMN is designed for

Engineering compute

Deterministic simulation
Pareto optimization
Certification-grade results
NFPA 20 · IEC · ASCE
Reproducible benchmarks

Not designed for

Language understanding
Text generation
Conversational AI
Heuristic reasoning
Open-ended questions

Compute paradigms

Deterministic compute (QOMN)

Given identical inputs → always identical outputs, bit-for-bit. Required for engineering certification (NFPA, IEC, ISO). No variance, no hallucination, no probabilistic drift.

Probabilistic generation (LLMs)

Optimized for language understanding and text generation. Non-deterministic by design. Not suitable for certification-grade engineering calculations.

Numeric solvers (MATLAB / ANSYS)

Accurate for their domain. No JIT physics plans, no Pareto optimization at SIMD speed, no multi-domain single-call coverage.

Compute Paradigms — Characteristics

System type	Determinism	Throughput	Pareto search	Certification	Primary use case
QOMN v3.2 Deterministic JIT · AVX2	IEEE-754 exact	—	✓ 170 points/call	✓ NFPA · IEC · ASCE	Engineering simulation
MATLAB / ANSYS numeric solvers	deterministic	~1–50 M/s	✗ separate toolbox	✓ domain-specific	Scientific modeling
C++ GCC -O3 manual implementation	✗ UB risk	~5 M/s	✗ manual only	~ depends on impl	Performance code
Language Models GPT-4, Claude, etc.	probabilistic	~1–5 ans/s	✗ not applicable	✗ not applicable	Language understanding

Note on LLM row: Language models are not engineering compute engines. Including them here is for reference only — they solve fundamentally different problem classes. Comparing throughput directly would be meaningless.

Pareto Latency — Engineering Compute Systems

QOMN v3.2

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C++ SIMD solver

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~850 µs

Parameter sweep: QOMN evaluates — parameter combinations in bounded engineering input space (flow, pressure, efficiency) in 12 seconds. This is a structured parameter sweep with Pareto optimization — not sampling, not stochastic search.

What QOMN is — honest framing

QOMN replaces non-reproducible workflows:

→ Spreadsheet engineering (Excel — no Pareto, no audit trail)

→ Manual sequential solvers (one result at a time, no SIMD)

→ Non-reproducible calculations (float drift, UB risk)

Bit-identical results across runs, servers, and time.
IEEE-754 exact · auditable · certification-ready
Orders of magnitude faster for parameter sweep optimization workloads.

Live API Log

JSON API ↗ ← All Proofs

Deterministic Engineering ComputeReproducible simulations for certification-grade systems

QOMN is designed for

Compute paradigms

Deterministic Engineering Compute
Reproducible simulations for certification-grade systems