Benchmark profile
RefCOCO average (RefCOCO (avg))
A referring-expression grounding benchmark averaged across RefCOCO variants to test whether a model can localize described objects correctly.
Data verifiedBenchmark score on RefCOCO (avg) — July 23, 2026
BenchLM mirrors the published score view for RefCOCO (avg). Qwen3.6-27B leads the public snapshot at 92.5% , followed by Qwen3.6-35B-A3B (92.0%) and Nemotron 3 Nano Omni 30B A3B (90.5%). BenchLM does not use these results to rank models overall.
Qwen3.6-27B
Alibaba
qwen3-6-27b
Qwen3.6-35B-A3B
Alibaba
qwen3-6-35b-a3b
Nemotron 3 Nano Omni 30B A3B
NVIDIA
nemotron-3-nano-omni-30b-a3b
Benchmark score table (4 models)
ScoreThe published RefCOCO (avg) snapshot places Qwen3.6-27B first at 92.5%. The third row is 2.0 points behind. The broader top-10 range is 10.4 points, so the table still separates the published systems.
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. BenchLM stores provider-reported aggregate RefCOCO values as a display-only grounding row.
BenchLM freshness & provenance
Version
RefCOCO (avg) 2026
Refresh cadence
Quarterly
Staleness state
Current
Question availability
Public benchmark set
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.
FAQ
What does RefCOCO (avg) measure?
A referring-expression grounding benchmark averaged across RefCOCO variants to test whether a model can localize described objects correctly.
Which model scores highest on RefCOCO (avg)?
Qwen3.6-27B by Alibaba currently leads with a score of 92.5% on RefCOCO (avg).
How many models are evaluated on RefCOCO (avg)?
4 AI models have been evaluated on RefCOCO (avg) on BenchLM.
Compare Top Models on RefCOCO (avg)
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