OpenVLHarness Study - Base - MMSearch-Plus: leaderboard
OpenVLHarness (2026): full evaluation splits of 22 visual benchmarks, four models; Base protocol. Scores follow each source task metric (accuracy, F1 or grounding AP), all on 0–100; Average is the published equal-benchmark composite. No across-harness maximum; medium effort is explicit for both GPT models. Published Task Score (%); higher is better.
Metric: Published Task Score (%). Source: arxiv.org. Saturation forecast: Around 2028. 4 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GPT-6 Astra (Medium) | 27.97 | #6 (GPT-6 Astra) |
| 2 | GPT-6 Luna (Medium) | 10.93 | #59 (GPT-6 Luna) |
| 3 | Qwen 3 VL 32B Instruct | 2.57 | #282 |
| 4 | Qwen 3 VL 8B Instruct | 1.29 | #416 |
No result here: #4 Claude Opus 5.5, #7 Gemini 4 Argon, #8 GPT-6.1 Sol.
Interactive version: theaggregate.ai/benchmark?slug=openvlharness-study-base-mmsearch-plus · How It Works · Data refreshed daily, snapshot 2026-10-21.