Standardized benchmarks are often criticized for not being "real workloads," but this critique is rarely backed by data. This paper provides the first systematic, quantitative analysis of the "fidelity gap" between the SPEC CPU2026 suite and its original, upstream open-source counterparts. We compile both the SPEC benchmarks and their upstream applications and execute them with official input workloads under two scenarios: a single-copy latency run and a 192-copy throughput run. Our findings show that most benchmarks exhibit high fidelity in single-copy runs, while a few outliers reveal the impact of SPEC's adaptation process. The multi-copy results further highlight the necessity of this adaptation: several benchmarks become significantly more efficient than their upstream versions under heavy load, underscoring the importance of I/O reduction. This work offers data-driven validation of SPEC's methodology, showing that the fidelity gap is not a flaw but a quantifiable consequence of enforcing portability, determinism, and CPU-centric measurement.

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