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Multimodal model comparison

Research cut-off date: 2026-07-22. Status: Phase 4, not yet written. This file states the scope of the work, the arguments it owns, and the research required to complete it. It contains no findings, because none have been sourced. See the changelog for phase status.

Scope

Compares models on multimodal benchmarks by modality, with input resolution and frame sampling recorded, since these conditions change scores and are commonly omitted from published tables.

Comparison rules in force

  • Every row carries an evidence grade, a source, and a source date.
  • Results produced under different harnesses, sampling policies, or tool permissions are not placed in the same ranked column without a warning adjacent to the table.
  • Results whose conditions are unstated are never ranked against results whose conditions are known.
  • Provider-reported rows are labelled Grade C and are never used alone to rank one provider above another.

Research checklist

  • Group results by modality rather than presenting a single multimodal ranking.
  • Record resolution and sampling conditions in the notes field of every row.
  • Record which models accept a modality but have no independent evaluation on it.
  • Regenerate the table with python scripts/generate_benchmark_tables.py and commit the result.
  • Run python scripts/validate_tables.py --check-comparability.

Generated comparison

Generated from the data layer by scripts/generate_benchmark_tables.py. Do not edit the region by hand.

Benchmark Subset Model Score Metric Unit Harness Sampling policy n Tools Reported by Evidence grade Evaluation date Published
No results for this category. Populate data/benchmarks.csv and rerun scripts/generate_benchmark_tables.py