diff --git a/refact_known_models/passthrough.py b/refact_known_models/passthrough.py
index d94f8af2..3fdcffa6 100644
--- a/refact_known_models/passthrough.py
+++ b/refact_known_models/passthrough.py
@@ -1,6 +1,7 @@
 # refer to https://docs.litellm.ai/docs/providers/
 
 passthrough_mini_db = {
+    # OpenAI models
     "gpt-4o": {
         "backend": "litellm",
         "provider": "openai",
@@ -12,28 +13,41 @@
         "pp1000t_generated": 15_000,  # $15.00 / 1M tokens (2024 may)
         "filter_caps": ["chat", "tools", "completion"],
     },
-    "gpt-4-turbo": {
+    "gpt-4o-2024-05-13": {
         "backend": "litellm",
         "provider": "openai",
-        "tokenizer_path": "Xenova/gpt-4",
-        "resolve_as": "gpt-4-turbo",
+        "tokenizer_path": "Xenova/gpt-4o",
+        "resolve_as": "gpt-4o-2024-05-13",
         "T": 128_000,
         "T_out": 4096,
-        "pp1000t_prompt": 10_000,
-        "pp1000t_generated": 30_000,  # $30.00 / 1M tokens (2024 may)
+        "pp1000t_prompt": 5_000,
+        "pp1000t_generated": 15_000,  # $15.00 / 1M tokens
         "filter_caps": ["chat", "tools", "completion"],
     },
-    "gpt-3.5-turbo": {
+    "gpt-4o-2024-08-06": {
         "backend": "litellm",
         "provider": "openai",
-        "tokenizer_path": "Xenova/gpt-3.5-turbo-16k",
-        "resolve_as": "gpt-3.5-turbo-1106",
-        "T": 16_000,
+        "tokenizer_path": "Xenova/gpt-4o",
+        "resolve_as": "gpt-4o-2024-08-06",
+        "T": 128_000,
         "T_out": 4096,
-        "pp1000t_prompt": 1000,
-        "pp1000t_generated": 2000,
+        "pp1000t_prompt": 2_500,
+        "pp1000t_generated": 10_000,  # $15.00 / 1M tokens
+        "filter_caps": ["chat", "tools", "completion"]
+    },
+    "gpt-4o-mini": {
+        "backend": "litellm",
+        "provider": "openai",
+        "tokenizer_path": "Xenova/gpt-4o",
+        "resolve_as": "gpt-4o-mini-2024-07-18",
+        "T": 128_000,
+        "T_out": 4096,
+        "pp1000t_prompt": 150,
+        "pp1000t_generated": 600,  # $0.60 / 1M tokens
         "filter_caps": ["chat", "tools", "completion"],
     },
+
+    # Anthropic models
     "claude-3-5-sonnet": {
         "backend": "litellm",
         "provider": "anthropic",
@@ -78,39 +92,6 @@
         "pp1000t_generated": 15_000,
         "filter_caps": ["chat", "tools", "completion"],
     },
-    "gpt-4o-2024-05-13": {
-        "backend": "litellm",
-        "provider": "openai",
-        "tokenizer_path": "Xenova/gpt-4o",
-        "resolve_as": "gpt-4o-2024-05-13",
-        "T": 128_000,
-        "T_out": 4096,
-        "pp1000t_prompt": 5_000,
-        "pp1000t_generated": 15_000,  # $15.00 / 1M tokens
-        "filter_caps": ["chat", "tools", "completion"],
-    },
-    "gpt-4o-2024-08-06": {
-        "backend": "litellm",
-        "provider": "openai",
-        "tokenizer_path": "Xenova/gpt-4o",
-        "resolve_as": "gpt-4o-2024-08-06",
-        "T": 128_000,
-        "T_out": 4096,
-        "pp1000t_prompt": 2_500,
-        "pp1000t_generated": 10_000,  # $15.00 / 1M tokens
-        "filter_caps": ["chat", "tools", "completion"]
-    },
-    "gpt-4o-mini": {
-        "backend": "litellm",
-        "provider": "openai",
-        "tokenizer_path": "Xenova/gpt-4o",
-        "resolve_as": "gpt-4o-mini-2024-07-18",
-        "T": 128_000,
-        "T_out": 4096,
-        "pp1000t_prompt": 150,
-        "pp1000t_generated": 600,  # $0.60 / 1M tokens
-        "filter_caps": ["chat", "tools", "completion"],
-    },
     "claude-3-5-sonnet-20241022": {
         "backend": "litellm",
         "provider": "anthropic",
@@ -122,6 +103,8 @@
         "pp1000t_generated": 15_000,  # $15.00 / 1M tokens (2024 oct)
         "filter_caps": ["chat", "tools", "completion"],
     },
+
+    # Groq models
     "groq-llama-3.1-8b": {
         "backend": "litellm",
         "provider": "groq",
@@ -188,6 +171,8 @@
         "pp1000t_generated": 600,  # TODO: don't know the price
         "filter_caps": ["chat", "completion"],
     },
+
+    # Cerebras models
     "cerebras-llama3.1-8b": {
         "backend": "litellm",
         "provider": "cerebras",
diff --git a/refact_utils/finetune/utils.py b/refact_utils/finetune/utils.py
index 69558235..51874c03 100644
--- a/refact_utils/finetune/utils.py
+++ b/refact_utils/finetune/utils.py
@@ -103,6 +103,20 @@ def _add_results_for_passthrough_provider(provider: str) -> None:
                 if 'completion' in v.get('filter_caps', []):
                     result['completion'].append(k)
 
+    for k, v in data.get("model_assign", {}).items():
+        if model_dict := [d for d in data['models'] if d['name'] == k]:
+            model_dict = model_dict[0]
+
+            add_result(k, model_dict)
+
+            if not model_dict.get('has_finetune'):
+                continue
+
+            finetune_info = model_dict.get('finetune_info', []) or []
+            for run in finetune_info:
+                val = f"{k}:{run['run_id']}:{run['checkpoint']}"
+                add_result(val, model_dict)
+
     if data.get("openai_api_enable"):
         _add_results_for_passthrough_provider('openai')
 
@@ -121,20 +135,6 @@ def _add_results_for_passthrough_provider(provider: str) -> None:
     if data.get('xai_api_enable'):
         _add_results_for_passthrough_provider('xai')
 
-    for k, v in data.get("model_assign", {}).items():
-        if model_dict := [d for d in data['models'] if d['name'] == k]:
-            model_dict = model_dict[0]
-
-            add_result(k, model_dict)
-
-            if not model_dict.get('has_finetune'):
-                continue
-
-            finetune_info = model_dict.get('finetune_info', []) or []
-            for run in finetune_info:
-                val = f"{k}:{run['run_id']}:{run['checkpoint']}"
-                add_result(val, model_dict)
-
     return result
 
 
diff --git a/refact_webgui/webgui/selfhost_fastapi_completions.py b/refact_webgui/webgui/selfhost_fastapi_completions.py
index 6fbfa0ec..47e39125 100644
--- a/refact_webgui/webgui/selfhost_fastapi_completions.py
+++ b/refact_webgui/webgui/selfhost_fastapi_completions.py
@@ -270,7 +270,7 @@ def _caps_base_data(self) -> Dict[str, Any]:
             "telemetry_basic_dest": "/stats/telemetry-basic",
             "telemetry_corrected_snippets_dest": "/stats/telemetry-snippets",
             "telemetry_basic_retrieve_my_own": "/stats/rh-stats",
-            "running_models": [r for r in [*running['completion'], *running['chat']]],
+            "running_models": list(set(r for r in [*running['completion'], *running['chat']])),
             "code_completion_default_model": code_completion_default_model,
             "multiline_code_completion_default_model": multiline_code_completion_default_model,
             "code_chat_default_model": code_chat_default_model,