RefCOCO / RefCOCO+ / RefCOCOg
Model grounds a referring expression to a bounding box in a COCO image. Scored by accuracy at IoU 0.5.
Reka's 'RefCOCO-A/B' are the testA/testB splits.
- Released
- July 2016
- Kind
- Detection and captioning
- Level
- Everyday
- Scored
- Checked automatically
- Answers
- Short answer
- Tasks
- All public
- Strongest model tested
-
Qwen3.5 397B-A17B #77 on the capability index
- Last in a launch post
- August 2026
- Last model added
- September 2026
In the authors’ words
Humans refer to objects in their environments all the time, especially in dialogue with other people. We explore generating and comprehending natural language referring expressions for objects in images. In particular, we focus on incorporating better measures of visual context into referring expression models and find that visual comparison to other objects within an image helps improve performance significantly. We also develop methods to tie the language generation process together, so that we generate expressions for all objects of a particular category jointly. Evaluation on three recent datasets - RefCOCO, RefCOCO+, and RefCOCOg, shows the advantages of our methods for both referring expression generation and comprehension.
Qwen3.5-Omni-Plus leads with 95% among models released by September 2026
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
The newest model with a score here came out in September 2026, and nobody has reported a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:
- Claude Fable 5.2
-
Gemini 4 Carbon
- Claude Opus 5.5
- GPT-6.1 Sol
- and 16 more
- 95.0
Qwen3.5-Omni-Plus
- 93.9
LongCat-Flash-Omni
- 92.5
Qwen3.6 27B
- 92.4
InternVL3.5-241B-A28B
- 92.4
Qwen3-VL-235B-A22B
- 92.3
Qwen3.5 397B-A17B
- 92.0
Qwen 3.6 35B-A3B
- 91.9
Intern-S1-Pro
- 91.3
Seed1.5-VL
- 91.3 GLM-4.5V
- 91.3
Qwen3.5-122B-A10B
- 90.9
Qwen3.5-27B
- 90.5
Nemotron 3 Nano Omni 30B-A3B
- 89.9 Reka Edge
- 89.7
Qwen3.5-9B
- 89.2
Qwen3.5-35B-A3B
- 88.6 GLM-4.6V
- 88.1
Qwen3.5-4B
- 88.1
Keye-VL-2.0-30B-A3B
- 87.9 LFM2.5-VL-3B
- 87.7
Qwen2.5-Omni-7B
- 87.4 GLM-4.1V-9B-Thinking
- 86.3
Nova 2 Omni Preview
- 86.0
DeepSeek-V4.1-Flash Base
- 84.8
Qwen3.5-2B
- 84.3
Cosmos3-Nano
- 80.1
Cosmos3-Edge
- 79.3
Qwen3.5-0.8B
- 73.2
North Micro Vision Instruct
- 1
Qwen3.5-Omni-Plus 95%
- 2
LongCat-Flash-Omni 93.9%
- 3
Qwen3.6 27B 92.5%
- 4
InternVL3.5-241B-A28B 92.4%
- 5
Qwen3-VL-235B-A22B 92.4%
- 6
Qwen3.5 397B-A17B 92.3%
- 7
Qwen 3.6 35B-A3B 92%
- 8
Intern-S1-Pro 91.9%
- 9
Seed1.5-VL 91.3%
- 10 GLM-4.5V 91.3%
- 11
Qwen3.5-122B-A10B 91.3%
- 12
Qwen3.5-27B 90.9%
- 13
Nemotron 3 Nano Omni 30B-A3B 90.5%
- 14 Reka Edge 89.9%
- 15
Qwen3.5-9B 89.7%
- 16
Qwen3.5-35B-A3B 89.2%
- 17 GLM-4.6V 88.6%
- 18
Qwen3.5-4B 88.1%
- 19
Keye-VL-2.0-30B-A3B 88.1%
- 20 LFM2.5-VL-3B 87.9%
- 21
Qwen2.5-Omni-7B 87.7%
- 22 GLM-4.1V-9B-Thinking 87.4%
- 23
Nova 2 Omni Preview 86.3%
- 24
DeepSeek-V4.1-Flash Base 86%
- 25
Qwen3.5-2B 84.8%
- 26
Cosmos3-Nano 84.3%
- 27
Cosmos3-Edge 80.1%
- 28
Qwen3.5-0.8B 79.3%
- 29
North Micro Vision Instruct 73.2%
Source: Labs’ model cards
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 95% | Mar 2026 | Lab model card | |
| 2 | | 93.9% | Oct 2025 | Lab model card | |
| 3 | | 92.5% | Apr 2026 | Lab model card | |
| 4 | | 92.4% | Aug 2025 | Lab model card | |
| 5 | | 92.4% | Sep 2025 | Lab model card | |
| 6 | | 92.3% | Feb 2026 | Lab model card | |
| 7 | | 92% | Apr 2026 | Lab model card | |
| 8 | | 91.9% | Feb 2026 | Lab model card | |
| 9 | | 91.3% | May 2025 | Lab model card | |
| 10 | GLM-4.5V | 91.3% | Aug 2025 | Lab model card | |
| 11 | | 91.3% | Feb 2026 | Lab model card | |
| 12 | | 90.9% | Feb 2026 | Lab model card | |
| 13 | | 90.5% | Apr 2026 | Lab model card | |
| 14 | Reka Edge | 89.9% | Mar 2026 | Lab model card | |
| 15 | | 89.7% | Mar 2026 | Lab model card | |
| 16 | | 89.2% | Feb 2026 | Lab model card | |
| 17 | GLM-4.6V | 88.6% | Dec 2025 | Lab model card | |
| 18 | | 88.1% | Mar 2026 | Lab model card | |
| 19 | | 88.1% | May 2026 | Lab model card | |
| 20 | LFM2.5-VL-3B | 87.9% | Aug 2026 | Lab model card | |
| 21 | | 87.7% | Mar 2025 | Lab model card | |
| 22 | GLM-4.1V-9B-Thinking | 87.4% | Jul 2025 | Lab model card | |
| 23 | | 86.3% | Dec 2025 | Lab model card | |
| 24 | | 86% | Sep 2026 | Lab model card | |
| 25 | | 84.8% | Mar 2026 | Lab model card | |
| 26 | | 84.3% | May 2026 | Lab model card | |
| 27 | | 80.1% | May 2026 | Lab model card | |
| 28 | | 79.3% | Mar 2026 | Lab model card | |
| 29 | | 73.2% | Aug 2026 | Lab model card |
5 models have held number one in labs’ own numbers since 2023
Lab claims count from the day the card came out, independent runs from the model’s release.
Source: Labs’ model cards
Qwen’s own number for Qwen2.5-Omni-7B passed 85% in March 2025
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Labs’ model cards
2 labs put it in a launch post in the last six months
Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| Aug 12, 2026 | LFM2.5-VL-3B | 87.9 | RefCOCO-avg |
| Aug 12, 2026 | 73.2 | RefCOCO avg (average of 8 RefCOCO, RefCOCO+ and RefCOCOg splits) | |
| May 25, 2026 | 88.1 | RefCOCO (avg) | |
| Apr 22, 2026 | 92.5 | RefCOCO avg | |
| Apr 15, 2026 | 92 | RefCOCO(avg) | |
| Mar 30, 2026 | 95 | RefCOCO(avg) | |
| Mar 11, 2026 | Reka Edge | 89.9 | Mean of RefCOCO-A 93.13 / RefCOCO-B 86.70 |
| Mar 2, 2026 | 79.3 | RefCOCO(avg) 79.3/77.8 (with CI / without CI) | |
| Mar 2, 2026 | 84.8 | RefCOCO(avg) 84.8/84.3 (with CI / without CI) | |
| Mar 2, 2026 | 88.1 | RefCOCO(avg) | |
| Mar 2, 2026 | 89.7 | RefCOCO(avg) | |
| Feb 24, 2026 | 89.2 | RefCOCO(avg) | |
| Feb 24, 2026 | 90.9 | RefCOCO(avg) | |
| Feb 24, 2026 | 91.3 | RefCOCO(avg) | |
| Feb 16, 2026 | 92.3 | RefCOCO(avg) | |
| Feb 2, 2026 | 91.9 | RefCOCO-avg | |
| Dec 8, 2025 | GLM-4.6V | 88.6 | RefCOCO-avg (val) |
| Dec 2, 2025 | 86.3 | RefCOCOg acc@0.5 | |
| Oct 31, 2025 | 93.9 | RefCOCO-avg | |
| Sep 23, 2025 | 92.4 | RefCOCO-avg | |
| Aug 11, 2025 | GLM-4.5V | 91.3 | RefCOCO-avg (val) |
| Jul 1, 2025 | GLM-4.1V-9B-Thinking | 87.4 | RefCOCO-avg (val) |
| May 12, 2025 | 91.3 | RefCOCO-avg | |
| Mar 27, 2025 | 87.7 | Mean of Refcoco val/testA/testB, Refcoco+ val/testA/testB, Refcocog val/test (90.5/93.5/86.6/85.4/91.0/79.3/87.4/87.9) |
17 system cards report it, from 9 labs
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| Sep 10, 2026 | | 86 | RefCOCO-avg, Acc@0.5, 0-shot | Capabilities |
| Jun 9, 2026 | | 88.1 | RefCOCO (avg) (Figure 5, printed value) | Capabilities |
| May 31, 2026 | | 84.3 | RefCOCO, Cosmos3-Nano 8B column, Table 10 | Capabilities |
| May 31, 2026 | | 80.1 | RefCOCO, Cosmos3-Edge 2B column, Table 10 | Capabilities |
| Apr 27, 2026 | | 90.5 | RefCOCO, reasoning on, 80.6 reasoning off (Table 7) | Capabilities |
| Apr 17, 2026 | | 95 | RefCOCO(avg) (Table 6) | Capabilities |
| Mar 26, 2026 | | 91.9 | RefCOCO-avg, non-thinking (Table 2) | Capabilities |
| Jan 1, 2026 | GLM-4.6V technical report | 88.6 | RefCOCO-avg (val), GLM-4.6V thinking (Table 2) | Capabilities |
| Dec 2, 2025 | | 86.3 | RefCOCOg acc@0.5 (Table 6) | Capabilities |
| Nov 26, 2025 | | 92.1 | RefCOCO-avg (Table 2) | Capabilities |
| Oct 31, 2025 | | 93.9 | RefCOCO-avg, average of RefCOCO and RefCOCO+ (Table 5) | Capabilities |
| Aug 25, 2025 | | 92.4 | RefCOCO, RefCOCO+ and RefCOCOg Overall (Table 7). RefCOCO val 94.1, testA 96.3, testB 91.5. RefCOCO+ val 91.6, testA 94.6, testB 86.9. RefCOCOg val 92.0, test 92.1 | Capabilities |
| Aug 13, 2025 | GLM-4.5V technical report | 91.3 | RefCOCO-avg (val), GLM-4.5V thinking (Table 2) | Capabilities |
| Jul 1, 2025 | GLM-4.1V-9B-Thinking technical report | 85.3 | RefCOCO-avg (val), GLM-4.1V-9B-Thinking thinking (Table 2). Table 3 prints 87.4 | Capabilities |
| May 11, 2025 | | 91.3 | RefCOCO-avg, thinking (Table 6). Non-thinking 91.6 | Capabilities |
| Mar 26, 2025 | | Refcoco val 90.5, testA 93.5, testB 86.6. Refcoco+ val 85.4, testA 91.0, testB 79.3. Refcocog val 87.4, test 87.9. No overall score (Table 6) | Capabilities | |
| Feb 19, 2025 | | RefCOCO val 92.7, testA 94.6, testB 89.7, RefCOCO+ val 88.9, testA 92.2, testB 83.7, RefCOCOg val 89.9, test 90.3, no overall (Table 6) | Capabilities |
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