sofron-v7 / README.md
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Add de-identified model-index card: HumanEval self-reported results (combination 90.2%, solo 89.0%)
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metadata
license: other
license_name: sofron-project-license
pipeline_tag: text-generation
tags:
  - code-generation
  - agent-architecture
model-index:
  - name: sofron-v7 (combination)
    results:
      - task:
          type: text-generation
        dataset:
          name: openai_humaneval
          type: openai_humaneval
        metrics:
          - name: pass@1
            type: pass@1
            value: 90.2
        source:
          name: Sofron HumanEval benchmark writeup (own harness, self-reported)
          url: https://github.com/s4h8a/sofron-benchmark-results
  - name: sofron-v7 (solo)
    results:
      - task:
          type: text-generation
        dataset:
          name: openai_humaneval
          type: openai_humaneval
        metrics:
          - name: pass@1
            type: pass@1
            value: 89
        source:
          name: Sofron HumanEval benchmark writeup (own harness, self-reported)
          url: https://github.com/s4h8a/sofron-benchmark-results

Sofron v7

Sofron is a combination-architecture coding agent: its own model weights (v7) paired with advisory teacher models (GLM-5.2 and DeepSeek) gathered in parallel as candidates on each problem. Sofron synthesizes its own final answer from their input, using its own judgment as the foundation rather than deferring to any single advisor.

This is a metadata-only repository. No model weights are hosted here; it exists to record a real, execution-graded, self-reported benchmark result with a citable, verifiable source.

Contact / homepage: https://sofron.one

HumanEval result (self-reported, not third-party verified)

Condition Pass@1 (164/164 problems)
combination (v7 + GLM-5.2 + DeepSeek synthesis) 90.2% (148/164)
solo (v7 alone) 89.0% (146/164)

Full methodology, raw results log, and harness scripts: https://github.com/s4h8a/sofron-benchmark-results

Sofron combines advisory input from external teacher models with its own model weights — it is not a frontier proprietary model. This result should be read as an honest, real placement rather than a state-of-the-art claim.