According to BenchLM.ai, Qwen3.6 Plus leads the RefCOCO (avg) benchmark with a score of 93.5%, followed by Qwen3.5 397B (92.3%) and Kimi K2.5 (87.8%). The scores show moderate spread, with meaningful differences between the top tier and mid-tier models.

4 models have been evaluated on RefCOCO (avg). The benchmark falls in the Multimodal & Grounded category. This category carries a 12% weight in BenchLM.ai's overall scoring system. RefCOCO (avg) is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.

About RefCOCO (avg)

Year

2026

Tasks

Referring-expression grounding

Format

Grounded visual localization

Difficulty

Fine-grained visual grounding

RefCOCO-style tasks matter for grounding-heavy assistants because they measure whether the model can map language to specific objects or regions instead of only answering abstract questions.

Qwen3.6 launch benchmarks

BenchLM freshness & provenance

Version

RefCOCO (avg) 2026

Refresh cadence

Quarterly

Staleness state

Current

Question availability

Public benchmark set

CurrentDisplay only

BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.