diff --git a/mteb/models/kalm_models.py b/mteb/models/kalm_models.py
new file mode 100644
index 0000000000..55cfa41d0f
--- /dev/null
+++ b/mteb/models/kalm_models.py
@@ -0,0 +1,109 @@
+from __future__ import annotations
+
+from functools import partial
+
+from mteb.model_meta import ModelMeta
+from mteb.models.instruct_wrapper import InstructSentenceTransformerWrapper
+
+
+MODEL_PROMPTS = {
+    "Classification": "Instruct: classify the query into different classes. \n Query: ",
+    "MultilabelClassification": "Instruct: classify the query into different classes. \n Query: ",
+    "Clustering": "Instruct: classify the query into different classes. \n Query: ",
+    "Reranking-query": "Instruct: Given a query, retrieve documents that answer the query. \n Query: ",
+    "Retrieval-query": "Instruct: Given a query, retrieve documents that answer the query. \n Query: ",
+}
+
+kalm_training_data = {
+    # from technical report
+    # not in MTEB:
+    # ExpertQA
+    # MEDI2BGE
+    # OpenOrca
+    # PAQ
+    # PubMedQA
+    # SearchQA
+    # arxiv_qa
+    # rag-dataset-12000
+    # CC-News
+    # SQuAD 2.0
+    # TriviaQA
+    # WebGPT Comparisons
+    # MultiNLI
+    # NLLB
+    # WikiAnswers
+    # SimCSE NLI
+    # SNLI
+    # Aya Dataset
+    # eli5
+    # ----
+    # in MTEB:
+    "CodeFeedbackMT": ["train"],
+    "CodeFeedbackST": ["train"],
+    "ArxivClusteringP2P": ["train"],
+    "ArxivClusteringS2S": ["train"],
+    "ArxivClusteringP2P.v2": ["train"],
+    "TRECCOVID": ["train"],
+    "DBPedia": ["train"],
+    "ESCIReranking": ["train"],
+    "FEVER": ["train"],
+    "FiQA2018": ["train"],
+    "FEVERHardNegatives": ["train"],
+    "NanoFEVERRetrieval": ["train"],
+    "HotpotQAHardNegatives": ["train"],
+    "MultiLongDocRetrieval": ["train"],
+    "MSMARCO": ["train"],
+    "MSMARCOHardNegatives": ["train"],
+    "NanoMSMARCORetrieval": ["train"],
+    "MSMARCOv2": ["train"],
+    "NFCorpus": ["train"],
+    "SciFact": ["train"],
+    "NQ": ["train"],
+    "NQHardNegatives": ["train"],
+    "NanoNQRetrieval": ["train"],
+    "QuoraRetrieval": ["train"],
+    "NanoQuoraRetrieval": ["train"],
+    "BiorxivClusteringP2P.v2": ["train"],
+    "BiorxivClusteringS2S.v2": ["train"],
+    "MedrxivClusteringP2P.v2": ["train"],
+    "MedrxivClusteringS2S.v2": ["train"],
+    "Banking77Classification": ["train"],
+    "AmazonPolarityClassification": ["train"],
+    "ImdbClassification": ["train"],
+    "EmotionClassification": ["train"],
+    "TweetSentimentExtractionClassification": ["train"],
+    "ToxicConversationsClassification": ["train"],
+    "MIRACLRetrieval": ["train"],
+    "MIRACLRetrievalHardNegatives": ["train"],
+    "MIRACLReranking": ["train"],
+    "MrTidyRetrieval": ["train"],
+    "PawsXPairClassification": ["train"],
+    "AmazonReviewsClassification": ["train"],
+    "AmazonCounterfactualClassification": ["train"],
+    "MultilingualSentiment": ["train"],
+    "MassiveIntentClassification": ["train"],
+    "MassiveScenarioClassification": ["train"],
+    "MTOPDomainClassification": ["train"],
+    "MTOPIntentClassification": ["train"],
+}
+
+KaLM_Embedding_X_0605 = ModelMeta(
+    name="KaLM-Team/KaLM-Embedding-X-0605",
+    loader=None,
+    languages=None,
+    open_weights=False,
+    revision="1",
+    release_date="2025-06-05",
+    n_parameters=9.24 * 1e9,
+    memory_usage_mb=35254,
+    max_tokens=8192,
+    embed_dim=3584,
+    license=None,
+    reference="https://github.com/KaLM-Team/KaLM-Embedding-X",
+    similarity_fn_name="cosine",
+    framework=["Sentence Transformers","PyTorch"],
+    use_instructions=True,
+    public_training_code="https://github.com/HITsz-TMG/KaLM-Embedding",
+    public_training_data=None,
+    training_datasets=kalm_training_data,
+)
\ No newline at end of file
diff --git a/mteb/models/misc_models.py b/mteb/models/misc_models.py
index b895122266..94308fd48d 100644
--- a/mteb/models/misc_models.py
+++ b/mteb/models/misc_models.py
@@ -243,7 +243,7 @@
     similarity_fn_name="cosine",
     use_instructions=None,
     training_datasets=kalm_training_data,
-    adapted_from="/mnt/shgeminicephfs/wx-dc-plt-hpc/xinshuohu/Output/Embedding/Qwen2-0.5B-eos_mean_pretrain_0806_1e-4_uen_sft_1022_filtered_v2_inst_3node_g8_1e-5_sin-0.1_mrl",
+    adapted_from="Qwen/Qwen2-0.5B",
     superseded_by=None,
 )
 HIT_TMG__KaLM_embedding_multilingual_mini_v1 = ModelMeta(
@@ -265,7 +265,7 @@
     similarity_fn_name="cosine",
     use_instructions=None,
     training_datasets=kalm_training_data,
-    adapted_from="/mnt/shgeminicephfs/wx-dc-plt-hpc/xinshuohu/Output/Embedding/Qwen2-0.5B-eos_mean_pretrain_0806_1e-4_uen_sft_0902_filtered_v2_3node_g8_1e-5_sin-0.1",
+    adapted_from="Qwen/Qwen2-0.5B",
     superseded_by=None,
 )
 Hum_Works__lodestone_base_4096_v1 = ModelMeta(
diff --git a/mteb/models/overview.py b/mteb/models/overview.py
index e5300c7323..661bf51782 100644
--- a/mteb/models/overview.py
+++ b/mteb/models/overview.py
@@ -47,6 +47,7 @@
     jasper_models,
     jina_clip,
     jina_models,
+    kalm_models,
     lens_models,
     linq_models,
     llm2clip_models,
@@ -122,6 +123,7 @@
     jasper_models,
     jina_models,
     jina_clip,
+    kalm_models,
     lens_models,
     linq_models,
     llm2clip_models,