diff --git a/litellm/__init__.py b/litellm/__init__.py
index 5078178e9b0..09fd6250c96 100644
--- a/litellm/__init__.py
+++ b/litellm/__init__.py
@@ -467,79 +467,80 @@ BEDROCK_CONVERSE_MODELS = [
 ]
 
 ####### COMPLETION MODELS ###################
-open_ai_chat_completion_models: List = []
-open_ai_text_completion_models: List = []
-cohere_models: List = []
-cohere_chat_models: List = []
-mistral_chat_models: List = []
-text_completion_codestral_models: List = []
-anthropic_models: List = []
-openrouter_models: List = []
-datarobot_models: List = []
-vertex_language_models: List = []
-vertex_vision_models: List = []
-vertex_chat_models: List = []
-vertex_code_chat_models: List = []
-vertex_ai_image_models: List = []
-vertex_text_models: List = []
-vertex_code_text_models: List = []
-vertex_embedding_models: List = []
-vertex_anthropic_models: List = []
-vertex_llama3_models: List = []
-vertex_deepseek_models: List = []
-vertex_ai_ai21_models: List = []
-vertex_mistral_models: List = []
-ai21_models: List = []
-ai21_chat_models: List = []
-nlp_cloud_models: List = []
-aleph_alpha_models: List = []
-bedrock_models: List = []
-bedrock_converse_models: List = BEDROCK_CONVERSE_MODELS
-fireworks_ai_models: List = []
-fireworks_ai_embedding_models: List = []
-deepinfra_models: List = []
-perplexity_models: List = []
-watsonx_models: List = []
-gemini_models: List = []
-xai_models: List = []
-deepseek_models: List = []
-azure_ai_models: List = []
-jina_ai_models: List = []
-voyage_models: List = []
-infinity_models: List = []
-databricks_models: List = []
-cloudflare_models: List = []
-codestral_models: List = []
-friendliai_models: List = []
-featherless_ai_models: List = []
-palm_models: List = []
-groq_models: List = []
-azure_models: List = []
-azure_text_models: List = []
-anyscale_models: List = []
-cerebras_models: List = []
-galadriel_models: List = []
-sambanova_models: List = []
-sambanova_embedding_models: List = []
-novita_models: List = []
-assemblyai_models: List = []
-snowflake_models: List = []
-gradient_ai_models: List = []
-llama_models: List = []
-nscale_models: List = []
-nebius_models: List = []
-nebius_embedding_models: List = []
-deepgram_models: List = []
-elevenlabs_models: List = []
-dashscope_models: List = []
-moonshot_models: List = []
-v0_models: List = []
-morph_models: List = []
-lambda_ai_models: List = []
-hyperbolic_models: List = []
-recraft_models: List = []
-cometapi_models: List = []
-oci_models: List = []
+from typing import Set  
+open_ai_chat_completion_models: Set = set()
+open_ai_text_completion_models: Set = set()
+cohere_models: Set = set()
+cohere_chat_models: Set = set()
+mistral_chat_models: Set = set()
+text_completion_codestral_models: Set = set()
+anthropic_models: Set = set()
+openrouter_models: Set = set()
+datarobot_models: Set = set()
+vertex_language_models: Set = set()
+vertex_vision_models: Set = set()
+vertex_chat_models: Set = set()
+vertex_code_chat_models: Set = set()
+vertex_ai_image_models: Set = set()
+vertex_text_models: Set = set()
+vertex_code_text_models: Set = set()
+vertex_embedding_models: Set = set()
+vertex_anthropic_models: Set = set()
+vertex_llama3_models: Set = set()
+vertex_deepseek_models: Set = set()
+vertex_ai_ai21_models: Set = set()
+vertex_mistral_models: Set = set()
+ai21_models: Set = set()
+ai21_chat_models: Set = set()
+nlp_cloud_models: Set = set()
+aleph_alpha_models: Set = set()
+bedrock_models: Set = set()
+bedrock_converse_models: Set = set(BEDROCK_CONVERSE_MODELS)
+fireworks_ai_models: Set = set()
+fireworks_ai_embedding_models: Set = set()
+deepinfra_models: Set = set()
+perplexity_models: Set = set()
+watsonx_models: Set = set()
+gemini_models: Set = set()
+xai_models: Set = set()
+deepseek_models: Set = set()
+azure_ai_models: Set = set()
+jina_ai_models: Set = set()
+voyage_models: Set = set()
+infinity_models: Set = set()
+databricks_models: Set = set()
+cloudflare_models: Set = set()
+codestral_models: Set = set()
+friendliai_models: Set = set()
+featherless_ai_models: Set = set()
+palm_models: Set = set()
+groq_models: Set = set()
+azure_models: Set = set()
+azure_text_models: Set = set()
+anyscale_models: Set = set()
+cerebras_models: Set = set()
+galadriel_models: Set = set()
+sambanova_models: Set = set()
+sambanova_embedding_models: Set = set()
+novita_models: Set = set()
+assemblyai_models: Set = set()
+snowflake_models: Set = set()
+gradient_ai_models: Set = set()
+llama_models: Set = set()
+nscale_models: Set = set()
+nebius_models: Set = set()
+nebius_embedding_models: Set = set()
+deepgram_models: Set = set()
+elevenlabs_models: Set = set()
+dashscope_models: Set = set()
+moonshot_models: Set = set()
+v0_models: Set = set()
+morph_models: Set = set()
+lambda_ai_models: Set = set()
+hyperbolic_models: Set = set()
+recraft_models: Set = set()
+cometapi_models: Set = set()
+oci_models: Set = set()
 
 
 def is_bedrock_pricing_only_model(key: str) -> bool:
@@ -580,166 +581,166 @@ def add_known_models():
         if value.get("litellm_provider") == "openai" and not is_openai_finetune_model(
             key
         ):
-            open_ai_chat_completion_models.append(key)
+            open_ai_chat_completion_models.add(key)
         elif value.get("litellm_provider") == "text-completion-openai":
-            open_ai_text_completion_models.append(key)
+            open_ai_text_completion_models.add(key)
         elif value.get("litellm_provider") == "azure_text":
-            azure_text_models.append(key)
+            azure_text_models.add(key)
         elif value.get("litellm_provider") == "cohere":
-            cohere_models.append(key)
+            cohere_models.add(key)
         elif value.get("litellm_provider") == "cohere_chat":
-            cohere_chat_models.append(key)
+            cohere_chat_models.add(key)
         elif value.get("litellm_provider") == "mistral":
-            mistral_chat_models.append(key)
+            mistral_chat_models.add(key)
         elif value.get("litellm_provider") == "anthropic":
-            anthropic_models.append(key)
+            anthropic_models.add(key)
         elif value.get("litellm_provider") == "empower":
-            empower_models.append(key)
+            empower_models.add(key)
         elif value.get("litellm_provider") == "openrouter":
-            openrouter_models.append(key)
+            openrouter_models.add(key)
         elif value.get("litellm_provider") == "datarobot":
-            datarobot_models.append(key)
+            datarobot_models.add(key)
         elif value.get("litellm_provider") == "vertex_ai-text-models":
-            vertex_text_models.append(key)
+            vertex_text_models.add(key)
         elif value.get("litellm_provider") == "vertex_ai-code-text-models":
-            vertex_code_text_models.append(key)
+            vertex_code_text_models.add(key)
         elif value.get("litellm_provider") == "vertex_ai-language-models":
-            vertex_language_models.append(key)
+            vertex_language_models.add(key)
         elif value.get("litellm_provider") == "vertex_ai-vision-models":
-            vertex_vision_models.append(key)
+            vertex_vision_models.add(key)
         elif value.get("litellm_provider") == "vertex_ai-chat-models":
-            vertex_chat_models.append(key)
+            vertex_chat_models.add(key)
         elif value.get("litellm_provider") == "vertex_ai-code-chat-models":
-            vertex_code_chat_models.append(key)
+            vertex_code_chat_models.add(key)
         elif value.get("litellm_provider") == "vertex_ai-embedding-models":
-            vertex_embedding_models.append(key)
+            vertex_embedding_models.add(key)
         elif value.get("litellm_provider") == "vertex_ai-anthropic_models":
             key = key.replace("vertex_ai/", "")
-            vertex_anthropic_models.append(key)
+            vertex_anthropic_models.add(key)
         elif value.get("litellm_provider") == "vertex_ai-llama_models":
             key = key.replace("vertex_ai/", "")
-            vertex_llama3_models.append(key)
+            vertex_llama3_models.add(key)
         elif value.get("litellm_provider") == "vertex_ai-deepseek_models":
             key = key.replace("vertex_ai/", "")
-            vertex_deepseek_models.append(key)
+            vertex_deepseek_models.add(key)
         elif value.get("litellm_provider") == "vertex_ai-mistral_models":
             key = key.replace("vertex_ai/", "")
-            vertex_mistral_models.append(key)
+            vertex_mistral_models.add(key)
         elif value.get("litellm_provider") == "vertex_ai-ai21_models":
             key = key.replace("vertex_ai/", "")
-            vertex_ai_ai21_models.append(key)
+            vertex_ai_ai21_models.add(key)
         elif value.get("litellm_provider") == "vertex_ai-image-models":
             key = key.replace("vertex_ai/", "")
-            vertex_ai_image_models.append(key)
+            vertex_ai_image_models.add(key)
         elif value.get("litellm_provider") == "ai21":
             if value.get("mode") == "chat":
-                ai21_chat_models.append(key)
+                ai21_chat_models.add(key)
             else:
-                ai21_models.append(key)
+                ai21_models.add(key)
         elif value.get("litellm_provider") == "nlp_cloud":
-            nlp_cloud_models.append(key)
+            nlp_cloud_models.add(key)
         elif value.get("litellm_provider") == "aleph_alpha":
-            aleph_alpha_models.append(key)
+            aleph_alpha_models.add(key)
         elif value.get(
             "litellm_provider"
         ) == "bedrock" and not is_bedrock_pricing_only_model(key):
-            bedrock_models.append(key)
+            bedrock_models.add(key)
         elif value.get("litellm_provider") == "bedrock_converse":
-            bedrock_converse_models.append(key)
+            bedrock_converse_models.add(key)
         elif value.get("litellm_provider") == "deepinfra":
-            deepinfra_models.append(key)
+            deepinfra_models.add(key)
         elif value.get("litellm_provider") == "perplexity":
-            perplexity_models.append(key)
+            perplexity_models.add(key)
         elif value.get("litellm_provider") == "watsonx":
-            watsonx_models.append(key)
+            watsonx_models.add(key)
         elif value.get("litellm_provider") == "gemini":
-            gemini_models.append(key)
+            gemini_models.add(key)
         elif value.get("litellm_provider") == "fireworks_ai":
             # ignore the 'up-to', '-to-' model names -> not real models. just for cost tracking based on model params.
             if "-to-" not in key and "fireworks-ai-default" not in key:
-                fireworks_ai_models.append(key)
+                fireworks_ai_models.add(key)
         elif value.get("litellm_provider") == "fireworks_ai-embedding-models":
             # ignore the 'up-to', '-to-' model names -> not real models. just for cost tracking based on model params.
             if "-to-" not in key:
-                fireworks_ai_embedding_models.append(key)
+                fireworks_ai_embedding_models.add(key)
         elif value.get("litellm_provider") == "text-completion-codestral":
-            text_completion_codestral_models.append(key)
+            text_completion_codestral_models.add(key)
         elif value.get("litellm_provider") == "xai":
-            xai_models.append(key)
+            xai_models.add(key)
         elif value.get("litellm_provider") == "deepseek":
-            deepseek_models.append(key)
+            deepseek_models.add(key)
         elif value.get("litellm_provider") == "meta_llama":
-            llama_models.append(key)
+            llama_models.add(key)
         elif value.get("litellm_provider") == "nscale":
-            nscale_models.append(key)
+            nscale_models.add(key)
         elif value.get("litellm_provider") == "azure_ai":
-            azure_ai_models.append(key)
+            azure_ai_models.add(key)
         elif value.get("litellm_provider") == "voyage":
-            voyage_models.append(key)
+            voyage_models.add(key)
         elif value.get("litellm_provider") == "infinity":
-            infinity_models.append(key)
+            infinity_models.add(key)
         elif value.get("litellm_provider") == "databricks":
-            databricks_models.append(key)
+            databricks_models.add(key)
         elif value.get("litellm_provider") == "cloudflare":
-            cloudflare_models.append(key)
+            cloudflare_models.add(key)
         elif value.get("litellm_provider") == "codestral":
-            codestral_models.append(key)
+            codestral_models.add(key)
         elif value.get("litellm_provider") == "friendliai":
-            friendliai_models.append(key)
+            friendliai_models.add(key)
         elif value.get("litellm_provider") == "palm":
-            palm_models.append(key)
+            palm_models.add(key)
         elif value.get("litellm_provider") == "groq":
-            groq_models.append(key)
+            groq_models.add(key)
         elif value.get("litellm_provider") == "azure":
-            azure_models.append(key)
+            azure_models.add(key)
         elif value.get("litellm_provider") == "anyscale":
-            anyscale_models.append(key)
+            anyscale_models.add(key)
         elif value.get("litellm_provider") == "cerebras":
-            cerebras_models.append(key)
+            cerebras_models.add(key)
         elif value.get("litellm_provider") == "galadriel":
-            galadriel_models.append(key)
+            galadriel_models.add(key)
         elif value.get("litellm_provider") == "sambanova":
-            sambanova_models.append(key)
+            sambanova_models.add(key)
         elif value.get("litellm_provider") == "sambanova-embedding-models":
-            sambanova_embedding_models.append(key)
+            sambanova_embedding_models.add(key)
         elif value.get("litellm_provider") == "novita":
-            novita_models.append(key)
+            novita_models.add(key)
         elif value.get("litellm_provider") == "nebius-chat-models":
-            nebius_models.append(key)
+            nebius_models.add(key)
         elif value.get("litellm_provider") == "nebius-embedding-models":
-            nebius_embedding_models.append(key)
+            nebius_embedding_models.add(key)
         elif value.get("litellm_provider") == "assemblyai":
-            assemblyai_models.append(key)
+            assemblyai_models.add(key)
         elif value.get("litellm_provider") == "jina_ai":
-            jina_ai_models.append(key)
+            jina_ai_models.add(key)
         elif value.get("litellm_provider") == "snowflake":
-            snowflake_models.append(key)
+            snowflake_models.add(key)
         elif value.get("litellm_provider") == "gradient_ai":
-            gradient_ai_models.append(key)
+            gradient_ai_models.add(key)
         elif value.get("litellm_provider") == "featherless_ai":
-            featherless_ai_models.append(key)
+            featherless_ai_models.add(key)
         elif value.get("litellm_provider") == "deepgram":
-            deepgram_models.append(key)
+            deepgram_models.add(key)
         elif value.get("litellm_provider") == "elevenlabs":
-            elevenlabs_models.append(key)
+            elevenlabs_models.add(key)
         elif value.get("litellm_provider") == "dashscope":
-            dashscope_models.append(key)
+            dashscope_models.add(key)
         elif value.get("litellm_provider") == "moonshot":
-            moonshot_models.append(key)
+            moonshot_models.add(key)
         elif value.get("litellm_provider") == "v0":
-            v0_models.append(key)
+            v0_models.add(key)
         elif value.get("litellm_provider") == "morph":
-            morph_models.append(key)
+            morph_models.add(key)
         elif value.get("litellm_provider") == "lambda_ai":
-            lambda_ai_models.append(key)
+            lambda_ai_models.add(key)
         elif value.get("litellm_provider") == "hyperbolic":
-            hyperbolic_models.append(key)
+            hyperbolic_models.add(key)
         elif value.get("litellm_provider") == "recraft":
-            recraft_models.append(key)
+            recraft_models.add(key)
         elif value.get("litellm_provider") == "cometapi":
-            cometapi_models.append(key)
+            cometapi_models.add(key)
         elif value.get("litellm_provider") == "oci":
-            oci_models.append(key)
+            oci_models.add(key)
 
 
 add_known_models()
@@ -769,68 +770,68 @@ ollama_models = ["llama2"]
 
 maritalk_models = ["maritalk"]
 
-model_list = (
+model_list = list(
     open_ai_chat_completion_models
-    + open_ai_text_completion_models
-    + cohere_models
-    + cohere_chat_models
-    + anthropic_models
-    + replicate_models
-    + openrouter_models
-    + datarobot_models
-    + huggingface_models
-    + vertex_chat_models
-    + vertex_text_models
-    + ai21_models
-    + ai21_chat_models
-    + together_ai_models
-    + baseten_models
-    + aleph_alpha_models
-    + nlp_cloud_models
-    + ollama_models
-    + bedrock_models
-    + deepinfra_models
-    + perplexity_models
-    + maritalk_models
-    + vertex_language_models
-    + watsonx_models
-    + gemini_models
-    + text_completion_codestral_models
-    + xai_models
-    + deepseek_models
-    + azure_ai_models
-    + voyage_models
-    + infinity_models
-    + databricks_models
-    + cloudflare_models
-    + codestral_models
-    + friendliai_models
-    + palm_models
-    + groq_models
-    + azure_models
-    + anyscale_models
-    + cerebras_models
-    + galadriel_models
-    + sambanova_models
-    + azure_text_models
-    + novita_models
-    + assemblyai_models
-    + jina_ai_models
-    + snowflake_models
-    + gradient_ai_models
-    + llama_models
-    + featherless_ai_models
-    + nscale_models
-    + deepgram_models
-    + elevenlabs_models
-    + dashscope_models
-    + moonshot_models
-    + v0_models
-    + morph_models
-    + lambda_ai_models
-    + recraft_models
-    + cometapi_models
-    + oci_models
+    | open_ai_text_completion_models
+    | cohere_models
+    | cohere_chat_models
+    | anthropic_models
+    | set(replicate_models)
+    | openrouter_models
+    | datarobot_models
+    | set(huggingface_models)
+    | vertex_chat_models
+    | vertex_text_models
+    | ai21_models
+    | ai21_chat_models
+    | set(together_ai_models)
+    | set(baseten_models)
+    | aleph_alpha_models
+    | nlp_cloud_models
+    | set(ollama_models)
+    | bedrock_models
+    | deepinfra_models
+    | perplexity_models
+    | set(maritalk_models)
+    | vertex_language_models
+    | watsonx_models
+    | gemini_models
+    | text_completion_codestral_models
+    | xai_models
+    | deepseek_models
+    | azure_ai_models
+    | voyage_models
+    | infinity_models
+    | databricks_models
+    | cloudflare_models
+    | codestral_models
+    | friendliai_models
+    | palm_models
+    | groq_models
+    | azure_models
+    | anyscale_models
+    | cerebras_models
+    | galadriel_models
+    | sambanova_models
+    | azure_text_models
+    | novita_models
+    | assemblyai_models
+    | jina_ai_models
+    | snowflake_models
+    | gradient_ai_models
+    | llama_models
+    | featherless_ai_models
+    | nscale_models
+    | deepgram_models
+    | elevenlabs_models
+    | dashscope_models
+    | moonshot_models
+    | v0_models
+    | morph_models
+    | lambda_ai_models
+    | recraft_models
+    | cometapi_models
+    | oci_models
 )
 
 model_list_set = set(model_list)
@@ -839,9 +840,9 @@ provider_list: List[Union[LlmProviders, str]] = list(LlmProviders)
 
 
 models_by_provider: dict = {
-    "openai": open_ai_chat_completion_models + open_ai_text_completion_models,
+    "openai": open_ai_chat_completion_models | open_ai_text_completion_models,
     "text-completion-openai": open_ai_text_completion_models,
-    "cohere": cohere_models + cohere_chat_models,
+    "cohere": cohere_models | cohere_chat_models,
     "cohere_chat": cohere_chat_models,
     "anthropic": anthropic_models,
     "replicate": replicate_models,
@@ -850,14 +851,9 @@ models_by_provider: dict = {
     "baseten": baseten_models,
     "openrouter": openrouter_models,
     "datarobot": datarobot_models,
-    "vertex_ai": vertex_chat_models
-    + vertex_text_models
-    + vertex_anthropic_models
-    + vertex_vision_models
-    + vertex_language_models
-    + vertex_deepseek_models,
+    "vertex_ai": vertex_chat_models | vertex_text_models | vertex_anthropic_models | vertex_vision_models | vertex_language_models | vertex_deepseek_models,
     "ai21": ai21_models,
-    "bedrock": bedrock_models + bedrock_converse_models,
+    "bedrock": bedrock_models | bedrock_converse_models,
     "petals": petals_models,
     "ollama": ollama_models,
     "ollama_chat": ollama_models,
@@ -866,7 +862,7 @@ models_by_provider: dict = {
     "maritalk": maritalk_models,
     "watsonx": watsonx_models,
     "gemini": gemini_models,
-    "fireworks_ai": fireworks_ai_models + fireworks_ai_embedding_models,
+    "fireworks_ai": fireworks_ai_models | fireworks_ai_embedding_models,
     "aleph_alpha": aleph_alpha_models,
     "text-completion-codestral": text_completion_codestral_models,
     "xai": xai_models,
@@ -882,14 +878,14 @@ models_by_provider: dict = {
     "friendliai": friendliai_models,
     "palm": palm_models,
     "groq": groq_models,
-    "azure": azure_models + azure_text_models,
+    "azure": azure_models | azure_text_models,
     "azure_text": azure_text_models,
     "anyscale": anyscale_models,
     "cerebras": cerebras_models,
     "galadriel": galadriel_models,
-    "sambanova": sambanova_models + sambanova_embedding_models,
+    "sambanova": sambanova_models | sambanova_embedding_models,
     "novita": novita_models,
-    "nebius": nebius_models + nebius_embedding_models,
+    "nebius": nebius_models | nebius_embedding_models,
     "assemblyai": assemblyai_models,
     "jina_ai": jina_ai_models,
     "snowflake": snowflake_models,
@@ -936,12 +932,12 @@ longer_context_model_fallback_dict: dict = {
 
 all_embedding_models = (
     open_ai_embedding_models
-    + cohere_embedding_models
-    + bedrock_embedding_models
-    + vertex_embedding_models
-    + fireworks_ai_embedding_models
-    + nebius_embedding_models
-    + sambanova_embedding_models
+    | set(cohere_embedding_models)
+    | set(bedrock_embedding_models)
+    | vertex_embedding_models
+    | fireworks_ai_embedding_models
+    | nebius_embedding_models
+    | sambanova_embedding_models
 )
 
 ####### IMAGE GENERATION MODELS ###################
diff --git a/litellm/constants.py b/litellm/constants.py
index 859a2eac178..365dfa84510 100644
--- a/litellm/constants.py
+++ b/litellm/constants.py
@@ -485,7 +485,7 @@ _openai_like_providers: List = [
     "watsonx",
 ]  # private helper. similar to openai but require some custom auth / endpoint handling, so can't use the openai sdk
 # well supported replicate llms
-replicate_models: List = [
+replicate_models: set = set([
     # llama replicate supported LLMs
     "replicate/llama-2-70b-chat:2796ee9483c3fd7aa2e171d38f4ca12251a30609463dcfd4cd76703f22e96cdf",
     "a16z-infra/llama-2-13b-chat:2a7f981751ec7fdf87b5b91ad4db53683a98082e9ff7bfd12c8cd5ea85980a52",
@@ -498,9 +498,9 @@ replicate_models: List = [
     # Others
     "replicate/dolly-v2-12b:ef0e1aefc61f8e096ebe4db6b2bacc297daf2ef6899f0f7e001ec445893500e5",
     "replit/replit-code-v1-3b:b84f4c074b807211cd75e3e8b1589b6399052125b4c27106e43d47189e8415ad",
-]
+])
 
-clarifai_models: List = [
+clarifai_models: set = set([
     "clarifai/meta.Llama-3.Llama-3-8B-Instruct",
     "clarifai/gcp.generate.gemma-1_1-7b-it",
     "clarifai/mistralai.completion.mixtral-8x22B",
@@ -564,10 +564,10 @@ clarifai_models: List = [
     "clarifai/gcp.generate.gemini-1_5-pro",
     "clarifai/gcp.generate.imagen-2",
     "clarifai/salesforce.blip.general-english-image-caption-blip-2",
-]
+])
 
 
-huggingface_models: List = [
+huggingface_models: set = set([
     "meta-llama/Llama-2-7b-hf",
     "meta-llama/Llama-2-7b-chat-hf",
     "meta-llama/Llama-2-13b-hf",
@@ -580,13 +580,13 @@ huggingface_models: List = [
     "meta-llama/Llama-2-13b-chat",
     "meta-llama/Llama-2-70b",
     "meta-llama/Llama-2-70b-chat",
-]  # these have been tested on extensively. But by default all text2text-generation and text-generation models are supported by liteLLM. - https://docs.litellm.ai/docs/providers
-empower_models = [
+])  # these have been tested on extensively. But by default all text2text-generation and text-generation models are supported by liteLLM. - https://docs.litellm.ai/docs/providers
+empower_models = set([
     "empower/empower-functions",
     "empower/empower-functions-small",
-]
+])
 
-together_ai_models: List = [
+together_ai_models: set = set([
     # llama llms - chat
     "togethercomputer/llama-2-70b-chat",
     # llama llms - language / instruct
@@ -614,16 +614,17 @@ together_ai_models: List = [
     "Austism/chronos-hermes-13b",
     "upstage/SOLAR-0-70b-16bit",
     "WizardLM/WizardLM-70B-V1.0",
-]  # supports all together ai models, just pass in the model id e.g. completion(model="together_computer/replit_code_3b",...)
+])
+  # supports all together ai models, just pass in the model id e.g. completion(model="together_computer/replit_code_3b",...)
 
 
-baseten_models: List = [
+baseten_models: set = set([
     "qvv0xeq",
     "q841o8w",
     "31dxrj3",
-]  # FALCON 7B  # WizardLM  # Mosaic ML
+])  # FALCON 7B  # WizardLM  # Mosaic ML
 
-featherless_ai_models: List = [
+featherless_ai_models: set = set([
     "featherless-ai/Qwerky-72B",
     "featherless-ai/Qwerky-QwQ-32B",
     "Qwen/Qwen2.5-72B-Instruct",
@@ -633,9 +634,9 @@ featherless_ai_models: List = [
     "mistralai/Mistral-Small-24B-Instruct-2501",
     "mistralai/Mistral-Nemo-Instruct-2407",
     "ProdeusUnity/Stellar-Odyssey-12b-v0.0",
-]
+])
 
-nebius_models: List = [
+nebius_models: set = set([
     "Qwen/Qwen3-235B-A22B",
     "Qwen/Qwen3-30B-A3B-fast",
     "Qwen/Qwen3-32B",
@@ -648,9 +649,9 @@ nebius_models: List = [
     "meta-llama/Llama-3.3-70B-Instruct-fast",
     "Qwen/Qwen2.5-32B-Instruct-fast",
     "Qwen/Qwen2.5-Coder-32B-Instruct-fast",
-]
+])
 
-dashscope_models: List = [
+dashscope_models: set = set([
     "qwen-turbo",
     "qwen-plus",
     "qwen-max",
@@ -661,13 +662,13 @@ dashscope_models: List = [
     "qwen3-235b-a22b",
     "qwen3-32b",
     "qwen3-30b-a3b",
-]
+])
 
-nebius_embedding_models: List = [
+nebius_embedding_models: set = set([
     "BAAI/bge-en-icl",
     "BAAI/bge-multilingual-gemma2",
     "intfloat/e5-mistral-7b-instruct",
-]
+])
 
 BEDROCK_INVOKE_PROVIDERS_LITERAL = Literal[
     "cohere",
@@ -681,8 +682,8 @@ BEDROCK_INVOKE_PROVIDERS_LITERAL = Literal[
     "deepseek_r1",
 ]
 
-open_ai_embedding_models: List = ["text-embedding-ada-002"]
-cohere_embedding_models: List = [
+open_ai_embedding_models: set = set(["text-embedding-ada-002"])
+cohere_embedding_models: set = set([
     "embed-v4.0",
     "embed-english-v3.0",
     "embed-english-light-v3.0",
@@ -690,12 +691,12 @@ cohere_embedding_models: List = [
     "embed-english-v2.0",
     "embed-english-light-v2.0",
     "embed-multilingual-v2.0",
-]
-bedrock_embedding_models: List = [
+])
+bedrock_embedding_models: set = set([
     "amazon.titan-embed-text-v1",
     "cohere.embed-english-v3",
     "cohere.embed-multilingual-v3",
-]
+])
 
 known_tokenizer_config = {
     "mistralai/Mistral-7B-Instruct-v0.1": {
diff --git a/litellm/utils.py b/litellm/utils.py
index a639678ca63..fdfe5e8fd7b 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -2316,47 +2316,47 @@ def register_model(model_cost: Union[str, dict]):  # noqa: PLR0915
         # add new model names to provider lists
         if value.get("litellm_provider") == "openai":
             if key not in litellm.open_ai_chat_completion_models:
-                litellm.open_ai_chat_completion_models.append(key)
+                litellm.open_ai_chat_completion_models.add(key)
         elif value.get("litellm_provider") == "text-completion-openai":
             if key not in litellm.open_ai_text_completion_models:
-                litellm.open_ai_text_completion_models.append(key)
+                litellm.open_ai_text_completion_models.add(key)
         elif value.get("litellm_provider") == "cohere":
             if key not in litellm.cohere_models:
-                litellm.cohere_models.append(key)
+                litellm.cohere_models.add(key)
         elif value.get("litellm_provider") == "anthropic":
             if key not in litellm.anthropic_models:
-                litellm.anthropic_models.append(key)
+                litellm.anthropic_models.add(key)
         elif value.get("litellm_provider") == "openrouter":
             split_string = key.split("/", 1)
             if key not in litellm.openrouter_models:
-                litellm.openrouter_models.append(split_string[1])
+                litellm.openrouter_models.add(split_string[1])
         elif value.get("litellm_provider") == "vertex_ai-text-models":
             if key not in litellm.vertex_text_models:
-                litellm.vertex_text_models.append(key)
+                litellm.vertex_text_models.add(key)
         elif value.get("litellm_provider") == "vertex_ai-code-text-models":
             if key not in litellm.vertex_code_text_models:
-                litellm.vertex_code_text_models.append(key)
+                litellm.vertex_code_text_models.add(key)
         elif value.get("litellm_provider") == "vertex_ai-chat-models":
             if key not in litellm.vertex_chat_models:
-                litellm.vertex_chat_models.append(key)
+                litellm.vertex_chat_models.add(key)
         elif value.get("litellm_provider") == "vertex_ai-code-chat-models":
             if key not in litellm.vertex_code_chat_models:
-                litellm.vertex_code_chat_models.append(key)
+                litellm.vertex_code_chat_models.add(key)
         elif value.get("litellm_provider") == "ai21":
             if key not in litellm.ai21_models:
-                litellm.ai21_models.append(key)
+                litellm.ai21_models.add(key)
         elif value.get("litellm_provider") == "nlp_cloud":
             if key not in litellm.nlp_cloud_models:
-                litellm.nlp_cloud_models.append(key)
+                litellm.nlp_cloud_models.add(key)
         elif value.get("litellm_provider") == "aleph_alpha":
             if key not in litellm.aleph_alpha_models:
-                litellm.aleph_alpha_models.append(key)
+                litellm.aleph_alpha_models.add(key)
         elif value.get("litellm_provider") == "bedrock":
             if key not in litellm.bedrock_models:
-                litellm.bedrock_models.append(key)
+                litellm.bedrock_models.add(key)
         elif value.get("litellm_provider") == "novita":
             if key not in litellm.novita_models:
-                litellm.novita_models.append(key)
+                litellm.novita_models.add(key)
     return model_cost
 
 
diff --git a/tests/litellm_utils_tests/test_utils.py b/tests/litellm_utils_tests/test_utils.py
index e9bfa643f3b..ce067df9de3 100644
--- a/tests/litellm_utils_tests/test_utils.py
+++ b/tests/litellm_utils_tests/test_utils.py
@@ -338,11 +338,9 @@ def test_aget_valid_models():
     print(valid_models)
 
     # list of openai supported llms on litellm
-    expected_models = (
-        litellm.open_ai_chat_completion_models + litellm.open_ai_text_completion_models
-    )
+    expected_models = litellm.open_ai_chat_completion_models | litellm.open_ai_text_completion_models
 
-    assert valid_models == expected_models
+    assert set(valid_models) == set(expected_models)
 
     # reset replicate env key
     os.environ = old_environ
@@ -355,7 +353,7 @@ def test_aget_valid_models():
     valid_models = get_valid_models()
 
     print(valid_models)
-    assert valid_models == expected_models
+    assert set(valid_models) == set(expected_models)
 
     # reset replicate env key
     os.environ = old_environ
@@ -376,7 +374,7 @@ def test_get_valid_models_with_custom_llm_provider(custom_llm_provider):
     )
     print(valid_models)
     assert len(valid_models) > 0
-    assert provider_config.get_models() == valid_models
+    assert set(provider_config.get_models()) == set(valid_models)
 
 
 # test_get_valid_models()
diff --git a/tests/llm_translation/test_lambda_ai.py b/tests/llm_translation/test_lambda_ai.py
index 3b73629b4a7..e50c6b09ef9 100644
--- a/tests/llm_translation/test_lambda_ai.py
+++ b/tests/llm_translation/test_lambda_ai.py
@@ -100,7 +100,7 @@ def test_lambda_ai_models_configuration():
     litellm.model_cost = litellm.get_model_cost_map(url="")
     
     # Clear and repopulate lambda_ai_models list after reloading model_cost
-    litellm.lambda_ai_models = []
+    litellm.lambda_ai_models = set()
     litellm.add_known_models()
     
     # Some Lambda AI models to test
@@ -132,7 +132,7 @@ def test_lambda_ai_model_list_populated():
     litellm.model_cost = litellm.get_model_cost_map(url="")
     
     # Clear and repopulate all model lists after reloading model_cost
-    litellm.lambda_ai_models = []
+    litellm.lambda_ai_models = set()
     litellm.add_known_models()
     
     # This should be populated by the add_known_models function
diff --git a/tests/local_testing/test_amazing_vertex_completion.py b/tests/local_testing/test_amazing_vertex_completion.py
index 20ffd44cca9..632e14a76eb 100644
--- a/tests/local_testing/test_amazing_vertex_completion.py
+++ b/tests/local_testing/test_amazing_vertex_completion.py
@@ -291,15 +291,15 @@ def test_avertex_ai():
     load_vertex_ai_credentials()
     test_models = (
         litellm.vertex_chat_models
-        + litellm.vertex_code_chat_models
-        + litellm.vertex_text_models
-        + litellm.vertex_code_text_models
+        | litellm.vertex_code_chat_models
+        | litellm.vertex_text_models
+        | litellm.vertex_code_text_models
     )
     litellm.set_verbose = False
     vertex_ai_project = "pathrise-convert-1606954137718"
 
-    test_models = random.sample(test_models, 1)
-    test_models += litellm.vertex_language_models  # always test gemini-pro
+    test_models = random.sample(list(test_models), 1)
+    test_models += list(litellm.vertex_language_models)  # always test gemini-pro
     for model in test_models:
         try:
             if model in VERTEX_MODELS_TO_NOT_TEST or (
@@ -345,12 +345,12 @@ def test_avertex_ai_stream():
 
     test_models = (
         litellm.vertex_chat_models
-        + litellm.vertex_code_chat_models
-        + litellm.vertex_text_models
-        + litellm.vertex_code_text_models
+        | litellm.vertex_code_chat_models
+        | litellm.vertex_text_models
+        | litellm.vertex_code_text_models
     )
-    test_models = random.sample(test_models, 1)
-    test_models += litellm.vertex_language_models  # always test gemini-pro
+    test_models = random.sample(list(test_models), 1)
+    test_models += list(litellm.vertex_language_models)  # always test gemini-pro
     for model in test_models:
         try:
             if model in VERTEX_MODELS_TO_NOT_TEST or (
@@ -393,12 +393,13 @@ async def test_async_vertexai_response():
     load_vertex_ai_credentials()
     test_models = (
         litellm.vertex_chat_models
-        + litellm.vertex_code_chat_models
-        + litellm.vertex_text_models
-        + litellm.vertex_code_text_models
+        | litellm.vertex_code_chat_models
+        | litellm.vertex_text_models
+        | litellm.vertex_code_text_models
     )
-    test_models = random.sample(test_models, 1)
-    test_models += litellm.vertex_language_models  # always test gemini-pro
+    
+    test_models = random.sample(list(test_models), 1)
+    test_models += list(litellm.vertex_language_models)  # always test gemini-pro
     for model in test_models:
         print(
             f"model being tested in async call: {model}, litellm.vertex_language_models: {litellm.vertex_language_models}"
@@ -450,12 +451,12 @@ async def test_async_vertexai_streaming_response():
     load_vertex_ai_credentials()
     test_models = (
         litellm.vertex_chat_models
-        + litellm.vertex_code_chat_models
-        + litellm.vertex_text_models
-        + litellm.vertex_code_text_models
+        | litellm.vertex_code_chat_models
+        | litellm.vertex_text_models
+        | litellm.vertex_code_text_models
     )
-    test_models = random.sample(test_models, 1)
-    test_models += litellm.vertex_language_models  # always test gemini-pro
+    test_models = random.sample(list(test_models), 1)
+    test_models += list(litellm.vertex_language_models)  # always test gemini-pro
     test_models = ["gemini-2.5-flash"]
     for model in test_models:
         if model in VERTEX_MODELS_TO_NOT_TEST or (