diff --git a/mteb/abstasks/TaskMetadata.py b/mteb/abstasks/TaskMetadata.py
index 872273e1d..fa2e8c9e0 100644
--- a/mteb/abstasks/TaskMetadata.py
+++ b/mteb/abstasks/TaskMetadata.py
@@ -113,6 +113,7 @@
     "s2s",  # Sentence-to-sentence
     "s2p",  # Sentence-to-paragraph
     "p2p",  # Paragraph-to-paragraph
+    "t2t",  # specifically for text-only tasks in mieb
     "i2i",
     "i2t",
     "t2i",
diff --git a/mteb/tasks/Image/Any2AnyRetrieval/eng/WebQAT2TRetrieval.py b/mteb/tasks/Image/Any2AnyRetrieval/eng/WebQAT2TRetrieval.py
index c431af439..eddc6e0fc 100644
--- a/mteb/tasks/Image/Any2AnyRetrieval/eng/WebQAT2TRetrieval.py
+++ b/mteb/tasks/Image/Any2AnyRetrieval/eng/WebQAT2TRetrieval.py
@@ -14,7 +14,7 @@ class WebQAT2TRetrieval(AbsTaskAny2AnyRetrieval):
             "revision": "468b42a2b2e767d80d2d93f5ae5d42f135a10478",
         },
         type="Any2AnyRetrieval",
-        category="s2p",
+        category="t2t",
         eval_splits=["test"],
         eval_langs=["eng-Latn"],
         main_score="ndcg_at_10",
diff --git a/scripts/run_mieb_missed_results.py b/scripts/run_mieb_missed_results.py
new file mode 100644
index 000000000..f3b523178
--- /dev/null
+++ b/scripts/run_mieb_missed_results.py
@@ -0,0 +1,141 @@
+from __future__ import annotations
+
+import mteb
+
+# missing
+model = mteb.get_model("royokong/e5-v")
+tasks = mteb.get_tasks(tasks=["EDIST2ITRetrieval", "Winoground"])
+evaluation = mteb.MTEB(tasks=tasks)
+results = evaluation.run(model, output_folder="results-mieb-final")
+
+model = mteb.get_model("nyu-visionx/moco-v3-vit-b")
+tasks = mteb.get_tasks(
+    tasks=[
+        "CIFAR10Clustering",
+        "ImageNetDog15Clustering",
+        "TinyImageNetClustering",
+        "UCF101",
+        "VOC2007",
+    ]
+)
+evaluation = mteb.MTEB(tasks=tasks)
+results = evaluation.run(model, output_folder="results-mieb-final")
+
+model = mteb.get_model("nyu-visionx/moco-v3-vit-l")
+tasks = mteb.get_tasks(
+    tasks=[
+        "SketchyI2IRetrieval",
+        "CIFAR10Clustering",
+        "ImageNetDog15Clustering",
+        "TinyImageNetClustering",
+        "UCF101",
+        "VOC2007",
+    ]
+)
+evaluation = mteb.MTEB(tasks=tasks)
+results = evaluation.run(model, output_folder="results-mieb-final")
+
+model = mteb.get_model("BAAI/bge-visualized-base")
+tasks = mteb.get_tasks(
+    tasks=[
+        "SciMMIRI2TRetrieval",
+        "SciMMIRT2IRetrieval",
+        "VisualNewsI2TRetrieval",
+        "WITT2IRetrieval",
+    ]
+)
+evaluation = mteb.MTEB(tasks=tasks)
+results = evaluation.run(model, output_folder="results-mieb-final")
+
+model = mteb.get_model("TIGER-Lab/VLM2Vec-Full")
+tasks = mteb.get_tasks(
+    tasks=["CVBenchCount", "CVBenchDepth", "CVBenchDistance", "CVBenchRelation"]
+)
+evaluation = mteb.MTEB(tasks=tasks)
+results = evaluation.run(model, output_folder="results-mieb-final")
+
+model = mteb.get_model("TIGER-Lab/VLM2Vec-LoRA")
+tasks = mteb.get_tasks(
+    task_types=[
+        "Any2AnyRetrieval",
+        "Any2AnyMultiChoice",
+        "Any2TextMutipleChoice",
+        "ImageClustering",
+        "ImageClassification",
+        "ImageMultilabelClassification",
+        "ImageTextPairClassification",
+        "VisualSTS",
+        "ZeroShotClassification",
+    ]
+)
+evaluation = mteb.MTEB(tasks=tasks)
+results = evaluation.run(model, output_folder="results-mieb-final")
+
+# rerun
+for model_name in [
+    "openai/clip-vit-base-patch32",
+    "openai/clip-vit-base-patch16",
+    "openai/clip-vit-large-patch14",
+    "royokong/e5-v",
+    "BAAI/bge-visualized-base",
+    "BAAI/bge-visualized-m3",
+    "kakaobrain/align-base",
+    "jinaai/jina-clip-v1",
+    "nomic-ai/nomic-embed-vision-v1.5",
+    "Salesforce/blip-image-captioning-large",
+    "Salesforce/blip-image-captioning-base",
+    "Salesforce/blip2-opt-2.7b",
+    "Salesforce/blip2-opt-6.7b-coco",
+    "facebook/dinov2-small",
+    "facebook/dinov2-base",
+    "facebook/dinov2-large",
+    "facebook/dinov2-giant",
+    "laion/CLIP-ViT-B-32-DataComp.XL-s13B-b90K",
+    "laion/CLIP-ViT-B-16-DataComp.XL-s13B-b90K",
+    "laion/CLIP-ViT-L-14-DataComp.XL-s13B-b90K",
+    "nyu-visionx/moco-v3-vit-b",
+    "nyu-visionx/moco-v3-vit-l",
+    "google/siglip-so400m-patch14-384",
+    "google/siglip-base-patch16-256-multilingual",
+    "google/siglip-base-patch16-256",
+    "google/siglip-base-patch16-512",
+    "google/siglip-base-patch16-384",
+    "google/siglip-base-patch16-224",
+    "google/siglip-large-patch16-256",
+    "google/siglip-large-patch16-384",
+    "laion/CLIP-ViT-L-14-DataComp.XL-s13B-b90K",
+    "laion/CLIP-ViT-B-32-DataComp.XL-s13B-b90K",
+    "laion/CLIP-ViT-B-16-DataComp.XL-s13B-b90K",
+    "laion/CLIP-ViT-bigG-14-laion2B-39B-b160k",
+    "laion/CLIP-ViT-g-14-laion2B-s34B-b88K",
+    "laion/CLIP-ViT-H-14-laion2B-s32B-b79K",
+    "laion/CLIP-ViT-L-14-laion2B-s32B-b82K",
+    "laion/CLIP-ViT-B-32-laion2B-s34B-b79K",
+    "TIGER-Lab/VLM2Vec-LoRA",
+    "TIGER-Lab/VLM2Vec-Full",
+    "Salesforce/blip-itm-base-coco",
+    "Salesforce/blip-itm-large-coco",
+    "Salesforce/blip-itm-base-flickr",
+    "Salesforce/blip-itm-large-flickr",
+    "EVA02-CLIP-B-16",
+    "EVA02-CLIP-L-14",
+    "EVA02-CLIP-bigE-14",
+    "EVA02-CLIP-bigE-14-plus",
+]:
+    model = mteb.get_model(model_name)
+    tasks = mteb.get_tasks(
+        tasks=[
+            "ROxfordEasyI2IRetrieval",
+            "ROxfordHardI2IRetrieval",
+            "ROxfordMediumI2IRetrieval",
+            "RParisEasyI2IRetrieval",
+            "RParisHardI2IRetrieval",
+            "RParisMediumI2IRetrieval",
+        ]
+    )
+    # get i-only tasks for i-only models.
+    if ("moco" in model_name) or ("dinov2" in model_name):
+        tasks = [task for task in tasks if "t" not in task.metadata.category]
+
+    evaluation = mteb.MTEB(tasks=tasks)
+    results = evaluation.run(model, output_folder="results-mieb-rerun")