--- title: UNISOLVE — current-G validation | SpinForge url: https://spin-forge.com/unisolve/validation description: The current G suites, application-model results and historical scale records are distinct evidence sets. Figures here are reported by the owner’s release… --- UNISOLVE 0.16.1 / CURRENT SOURCE G SPINFORGE / A GARMO LABS COMPANY # Evidence tied to the source. The current G suites, application-model results and historical scale records are distinct evidence sets. Figures here are reported by the owner’s release account, not engine tests rerun for this publication. [Explore the application evidence](https://spin-forge.com/unisolve/applications) [Talk about your workload](https://spin-forge.com/contact) CURRENT G / ONE TEST INVENTORY ## 14,935 test IDs. Two tested environments. | Environment | Passed | Skipped | Additional | | Mac ARM64 / Python 3.14 | 14,894 | 41 | 34 passing subtests | | Existing Brev Linux ARM64 / Python 3.10 | 14,920 | 15 | 1 warning; 34 passing subtests | Do not add the host totals and call them unique tests. Clean offline installed-package checks exercised all 82 profiles, both tested MCP protocol eras and fresh answer checking, retaining declines and interruptions. CURRENT INVENTORY ## Different counts. Different meanings. | Measure | Reported count | | Problem-domain families | 13 | | Profiles | 82 | | Entry functions | 65 | | Python exports | 133 | | CLI operations | 38 | | Stdio MCP tools | 9 | | Runtime/data files | 260 | SEPARATE APPLICATION PROOF ## Airline planning: 1,201,500. For the original flugpl model, a separate proof established matching objective and global bound of 1,201,500 with gap zero. Its proof-work allowance was 50 million, above the default five million. Those are model units, not airline savings. [Read all eight application outcomes](https://spin-forge.com/unisolve/applications) CURRENT G / HISTORICAL-DATA MODEL ## 221 locations. 28 proved model batches. The LA experiment reports checked global optima for all 28 declared batches. Modeled red-exposure proxy: 17.067 9.101 seconds, a 46.67% reduction against an assumed equal split. Campaign wall time: 30.74 seconds. Not measured LA congestion reduction: 2013–2016 counts, assumed cycles and independent locations. Queues, capacities, turns, pedestrians, offsets and spillback are absent. External repartitioning enabled proof completion; it is not an automatic-router fix. HISTORICAL SOURCE C / SCALE ## Large input. Explicit result scope. An explicit one-billion-variable, three-billion-edge graph used 72 GB of original arrays and approximately 17.39 GB peak CUDA allocation. Initial solve including validation/recount: about 406 seconds. Separate replay: about 73 seconds. Continuation improved the checked objective by approximately 4.425%; global optimality remains unproved. The 200-billion records distinguish sparse namespaces, implicit structured proofs and a materialized 25 GB packed state. The temporary state was deleted after validation; evidence is retained. One physical GH200 was used, not physical multi-GPU scaling. RETAINED NEGATIVE FINDINGS ## Selection is implemented. A universal learned gain is not. The retained routing study measured 186 actual dispatch outcomes. In one comparison, probing-only completed 39/42, while the then-packaged learned default completed 37/42 and was slower. The general learned promotion was not made. A separate linear-capability selector also did not show held-out improvement. Garmo Solvers Router’s separate positive portfolio result must not overwrite these UNISOLVE records. HISTORY & DEPLOYMENT ## Keep the old records under their old identities. Earlier 78-profile, candidate-D and 0.13 descriptions remain historical. Current G figures are not retroactively assigned to those builds. Optional numerical/SMT/CUDA integrations retain their dependencies and trust boundaries. The source does not establish universal source-language conformance, physical multi-GPU speedup or a hosted multiuser security sandbox. [Review runtime scope](https://spin-forge.com/unisolve/runtime)