diff --git a/app/config/models.json b/app/config/models.json
index bb3793cc..7215f69c 100644
--- a/app/config/models.json
+++ b/app/config/models.json
@@ -1336,6 +1336,890 @@
       "cache_read_per_1m": 0.25
     }
   },
+  "MiniMaxAI/MiniMax-M2.7": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "MiniMaxAI MiniMax M2.7 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.3,
+      "output_per_1m": 1.2,
+      "cache_read_per_1m": 0.06
+    }
+  },
+  "MiniMaxAI/MiniMax-M3": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "MiniMaxAI MiniMax M3 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.3,
+      "output_per_1m": 1.2,
+      "cache_read_per_1m": 0.06
+    }
+  },
+  "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "NousResearch Nous Hermes 2 Mixtral 8x7B DPO via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.6,
+      "output_per_1m": 0.6
+    }
+  },
+  "Qwen/QwQ-32B": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen QwQ 32B via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 1.2,
+      "output_per_1m": 1.2
+    }
+  },
+  "Qwen/Qwen2-1.5B-Instruct": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen2 1.5B Instruct via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.02,
+      "output_per_1m": 0.02
+    }
+  },
+  "Qwen/Qwen2-72B-Instruct": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen2 72B Instruct via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.9,
+      "output_per_1m": 0.9
+    }
+  },
+  "Qwen/Qwen2-VL-72B-Instruct": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen2 VL 72B Instruct via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 1.2,
+      "output_per_1m": 1.2
+    }
+  },
+  "Qwen/Qwen2.5-14B-Instruct": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen2.5 14B Instruct via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.8,
+      "output_per_1m": 0.8
+    }
+  },
+  "Qwen/Qwen2.5-72B-Instruct": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen2.5 72B Instruct via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 1.2,
+      "output_per_1m": 1.2
+    }
+  },
+  "Qwen/Qwen2.5-72B-Instruct-Turbo": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen2.5 72B Instruct Turbo via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 1.2,
+      "output_per_1m": 1.2
+    }
+  },
+  "Qwen/Qwen2.5-7B-Instruct-Turbo": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen2.5 7B Instruct Turbo via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.3,
+      "output_per_1m": 0.3
+    }
+  },
+  "Qwen/Qwen2.5-Coder-32B-Instruct": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen2.5 Coder 32B Instruct via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.8,
+      "output_per_1m": 0.8
+    }
+  },
+  "Qwen/Qwen2.5-VL-72B-Instruct": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen2.5 VL 72B Instruct via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 1.95,
+      "output_per_1m": 8.0
+    }
+  },
+  "Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen3 Coder 480B A35B Instruct FP8 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 2.0,
+      "output_per_1m": 2.0
+    }
+  },
+  "Qwen/Qwen3-Coder-Next-FP8": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen3 Coder Next FP8 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.5,
+      "output_per_1m": 1.2
+    }
+  },
+  "Qwen/Qwen3-Next-80B-A3B-Instruct": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen3 Next 80B A3B Instruct via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.15,
+      "output_per_1m": 1.5
+    }
+  },
+  "Qwen/Qwen3-Next-80B-A3B-Thinking": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen3 Next 80B A3B Thinking via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.15,
+      "output_per_1m": 1.5
+    }
+  },
+  "Qwen/Qwen3-VL-32B-Instruct": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen3 VL 32B Instruct via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.5,
+      "output_per_1m": 1.5
+    }
+  },
+  "Qwen/Qwen3-VL-8B-Instruct": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen3 VL 8B Instruct via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.18,
+      "output_per_1m": 0.68
+    }
+  },
+  "Qwen/Qwen3.5-397B-A17B": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen3.5 397B A17B via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.6,
+      "output_per_1m": 3.6,
+      "cache_read_per_1m": 0.35
+    }
+  },
+  "Qwen/Qwen3.5-9B": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen3.5 9B via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.17,
+      "output_per_1m": 0.25
+    }
+  },
+  "Qwen/Qwen3.6-Plus": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen3.6 Plus via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.5,
+      "output_per_1m": 3.0
+    }
+  },
+  "Qwen/Qwen3.7-Max": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen3.7 Max via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 1.5,
+      "output_per_1m": 4.5,
+      "cache_read_per_1m": 0.3
+    }
+  },
+  "Qwen/Qwen3.7-Plus": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen3.7 Plus via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.32,
+      "output_per_1m": 1.28
+    }
+  },
+  "Qwen/Qwen3.8-2.4T-A95B": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen3.8 2.4T A95B via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 2.0,
+      "output_per_1m": 6.0,
+      "cache_read_per_1m": 0.25
+    }
+  },
+  "Qwen/Qwen3.8-Flash": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "Qwen Qwen3.8 Flash via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.09,
+      "output_per_1m": 0.282
+    }
+  },
+  "arcee-ai/trinity-mini": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "arcee ai trinity mini via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.045,
+      "output_per_1m": 0.15
+    }
+  },
+  "arize-ai/qwen-2-1.5b-instruct": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "arize ai qwen 2 1.5b instruct via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.1,
+      "output_per_1m": 0.1
+    }
+  },
+  "deepseek-ai/DeepSeek-R1-0528": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "deepseek ai DeepSeek R1 0528 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 3.0,
+      "output_per_1m": 7.0
+    }
+  },
+  "deepseek-ai/DeepSeek-R1-Distill-Llama-70B": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "deepseek ai DeepSeek R1 Distill Llama 70B via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 2.0,
+      "output_per_1m": 2.0
+    }
+  },
+  "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "deepseek ai DeepSeek R1 Distill Qwen 1.5B via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.18,
+      "output_per_1m": 0.18
+    }
+  },
+  "deepseek-ai/DeepSeek-R1-Distill-Qwen-14B": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "deepseek ai DeepSeek R1 Distill Qwen 14B via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 1.6,
+      "output_per_1m": 1.6
+    }
+  },
+  "deepseek-ai/DeepSeek-V3": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "deepseek ai DeepSeek V3 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 1.25,
+      "output_per_1m": 1.25
+    }
+  },
+  "deepseek-ai/DeepSeek-V3.1": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "deepseek ai DeepSeek V3.1 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.6,
+      "output_per_1m": 1.7
+    }
+  },
+  "deepseek-ai/DeepSeek-V4-Flash-0731": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "deepseek ai DeepSeek V4 Flash 0731 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.14,
+      "output_per_1m": 0.28,
+      "cache_read_per_1m": 0.03
+    }
+  },
+  "deepseek-ai/DeepSeek-V4-Pro-0813": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "deepseek ai DeepSeek V4 Pro 0813 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 1.32,
+      "output_per_1m": 3.96,
+      "cache_read_per_1m": 0.13
+    }
+  },
+  "deepseek-ai/DeepSeek-V4.1-Flash": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "deepseek ai DeepSeek V4.1 Flash via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.3,
+      "output_per_1m": 1.2,
+      "cache_read_per_1m": 0.006
+    }
+  },
+  "deepseek-ai/deepseek-coder-33b-instruct": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "deepseek ai deepseek coder 33b instruct via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.8,
+      "output_per_1m": 0.8
+    }
+  },
+  "google/gemma-2-27b-it": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "google gemma 2 27b it via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.8,
+      "output_per_1m": 0.8
+    }
+  },
+  "google/gemma-4-31B-it": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "google gemma 4 31B it via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.39,
+      "output_per_1m": 0.97
+    }
+  },
+  "meta-llama/Llama-3-8b-chat-hf": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "meta llama Llama 3 8b chat hf via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.2,
+      "output_per_1m": 0.2
+    }
+  },
+  "meta-llama/Llama-3.1-405B-Instruct": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "meta llama Llama 3.1 405B Instruct via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 3.5,
+      "output_per_1m": 3.5
+    }
+  },
+  "meta-llama/Llama-3.2-1B-Instruct": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "meta llama Llama 3.2 1B Instruct via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.06,
+      "output_per_1m": 0.06
+    }
+  },
+  "meta-llama/Llama-3.2-3B-Instruct": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "meta llama Llama 3.2 3B Instruct via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.06,
+      "output_per_1m": 0.06
+    }
+  },
+  "meta-llama/Llama-3.3-70B-Instruct-Turbo": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "meta llama Llama 3.3 70B Instruct Turbo via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 1.04,
+      "output_per_1m": 1.04
+    }
+  },
+  "meta-llama/Llama-4-Scout-17B-16E-Instruct": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "meta llama Llama 4 Scout 17B 16E Instruct via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.18,
+      "output_per_1m": 0.59
+    }
+  },
+  "meta-llama/Meta-Llama-3-70B-Instruct-Turbo": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "meta llama Meta Llama 3 70B Instruct Turbo via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.88,
+      "output_per_1m": 0.88
+    }
+  },
+  "meta-llama/Meta-Llama-3-8B-Instruct": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "meta llama Meta Llama 3 8B Instruct via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.2,
+      "output_per_1m": 0.2
+    }
+  },
+  "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "meta llama Meta Llama 3.1 70B Instruct Turbo via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.88,
+      "output_per_1m": 0.88
+    }
+  },
+  "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "meta llama Meta Llama 3.1 8B Instruct Turbo via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.18,
+      "output_per_1m": 0.18
+    }
+  },
+  "meta-models/Muse-Glimmer-30B": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "meta models Muse Glimmer 30B via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.35,
+      "output_per_1m": 1.5,
+      "cache_read_per_1m": 0.04
+    }
+  },
+  "mistralai/Ministral-3-14B-Instruct-2512": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "mistralai Ministral 3 14B Instruct 2512 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.2,
+      "output_per_1m": 0.2
+    }
+  },
+  "mistralai/Mistral-7B-Instruct-v0.1": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "mistralai Mistral 7B Instruct v0.1 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.2,
+      "output_per_1m": 0.2
+    }
+  },
+  "mistralai/Mistral-7B-Instruct-v0.3": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "mistralai Mistral 7B Instruct v0.3 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.2,
+      "output_per_1m": 0.2
+    }
+  },
+  "mistralai/Mistral-Small-24B-Instruct-2501": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "mistralai Mistral Small 24B Instruct 2501 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.1,
+      "output_per_1m": 0.3
+    }
+  },
+  "mistralai/Mixtral-8x7B-Instruct-v0.1": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "mistralai Mixtral 8x7B Instruct v0.1 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.6,
+      "output_per_1m": 0.6
+    }
+  },
+  "moonshotai/Kimi-K2-Instruct": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "moonshotai Kimi K2 Instruct via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 1.0,
+      "output_per_1m": 3.0
+    }
+  },
+  "moonshotai/Kimi-K2.5-fp4": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "moonshotai Kimi K2.5 fp4 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.5,
+      "output_per_1m": 2.8
+    }
+  },
+  "moonshotai/Kimi-K2.6": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "moonshotai Kimi K2.6 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 1.2,
+      "output_per_1m": 4.5,
+      "cache_read_per_1m": 0.2
+    }
+  },
+  "moonshotai/Kimi-K2.7-Code": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "moonshotai Kimi K2.7 Code via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.95,
+      "output_per_1m": 4.0,
+      "cache_read_per_1m": 0.19
+    }
+  },
+  "moonshotai/Kimi-K3": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "moonshotai Kimi K3 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 3.0,
+      "output_per_1m": 15.0,
+      "cache_read_per_1m": 0.3
+    }
+  },
+  "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "nvidia Llama 3.1 Nemotron 70B Instruct HF via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.88,
+      "output_per_1m": 0.88
+    }
+  },
+  "nvidia/NVIDIA-Nemotron-Nano-9B-v2": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "nvidia NVIDIA Nemotron Nano 9B v2 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.06,
+      "output_per_1m": 0.25
+    }
+  },
+  "nvidia/nemotron-3-ultra-550b-a55b": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "nvidia nemotron 3 ultra 550b a55b via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.6,
+      "output_per_1m": 3.6,
+      "cache_read_per_1m": 0.2
+    }
+  },
+  "openai/gpt-oss-120b": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "openai gpt oss 120b via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.15,
+      "output_per_1m": 0.6
+    }
+  },
+  "openai/gpt-oss-20b": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "openai gpt oss 20b via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.05,
+      "output_per_1m": 0.2
+    }
+  },
+  "thinkingmachines/Inkling": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "thinkingmachines Inkling via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 1.0,
+      "output_per_1m": 4.05,
+      "cache_read_per_1m": 0.17
+    }
+  },
+  "together/Tev1-4B-experimental": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "together Tev1 4B experimental via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.042,
+      "cache_read_per_1m": 0.042
+    }
+  },
+  "zai-org/GLM-4.5-Air-FP8": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "zai org GLM 4.5 Air FP8 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.2,
+      "output_per_1m": 1.1
+    }
+  },
+  "zai-org/GLM-4.6": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "zai org GLM 4.6 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.6,
+      "output_per_1m": 2.2
+    }
+  },
+  "zai-org/GLM-4.7": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "zai org GLM 4.7 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.45,
+      "output_per_1m": 2.0
+    }
+  },
+  "zai-org/GLM-5": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "zai org GLM 5 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 1.0,
+      "output_per_1m": 3.2
+    }
+  },
+  "zai-org/GLM-5.1": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "zai org GLM 5.1 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 1.4,
+      "output_per_1m": 4.4,
+      "cache_read_per_1m": 0.26
+    }
+  },
+  "zai-org/GLM-5.2": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "zai org GLM 5.2 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 1.4,
+      "output_per_1m": 4.4,
+      "cache_read_per_1m": 0.26
+    }
+  },
+  "zai-org/GLM-5.3": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "zai org GLM 5.3 via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 1.4,
+      "output_per_1m": 4.4,
+      "cache_read_per_1m": 0.26
+    }
+  },
+  "zai-org/GLM-5.3-Flash": {
+    "provider": "together",
+    "model_type": "llm",
+    "description": "zai org GLM 5.3 Flash via Together",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.15,
+      "output_per_1m": 0.5,
+      "cache_read_per_1m": 0.03
+    }
+  },
+  "jev-1.13.0": {
+    "provider": "typesafe",
+    "model_type": "llm",
+    "description": "jev 1.13.0 via TypeSafe",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.042
+    }
+  },
+  "jev-latest": {
+    "provider": "typesafe",
+    "model_type": "llm",
+    "description": "jev latest via TypeSafe",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.042
+    }
+  },
+  "jev-preview": {
+    "provider": "typesafe",
+    "model_type": "llm",
+    "description": "jev preview via TypeSafe",
+    "pricing": {
+      "source": "litellm_import",
+      "usage_kind": "llm",
+      "input_per_1m": 0.042
+    }
+  },
   "google-speech-v2": {
     "provider": "google",
     "model_type": "stt",
diff --git a/app/models/enums.py b/app/models/enums.py
index 020acecf..dd4519f0 100644
--- a/app/models/enums.py
+++ b/app/models/enums.py
@@ -145,6 +145,7 @@ class ModelProvider(str, enum.Enum):
     MISTRAL = "mistral"
     META = "meta"
     TOGETHER = "together"
+    TYPESAFE = "typesafe"
     PERPLEXITY = "perplexity"
     AZURE = "azure"
     AWS = "aws"
diff --git a/app/services/ai/llm_service.py b/app/services/ai/llm_service.py
index 95e64488..e310194e 100644
--- a/app/services/ai/llm_service.py
+++ b/app/services/ai/llm_service.py
@@ -45,6 +45,8 @@
     "groq": "groq",
     "xai": "xai",
     "fireworks": "fireworks_ai",
+    "together": "together_ai",
+    "typesafe": "typesafe",
     "sarvam": "sarvam",
 }
 
diff --git a/app/services/judge_alignment/model_catalog.py b/app/services/judge_alignment/model_catalog.py
index 6fb7416f..4c1b130c 100644
--- a/app/services/judge_alignment/model_catalog.py
+++ b/app/services/judge_alignment/model_catalog.py
@@ -43,6 +43,7 @@
     ModelProvider.MISTRAL.value,
     ModelProvider.META.value,
     ModelProvider.TOGETHER.value,
+    ModelProvider.TYPESAFE.value,
     ModelProvider.PERPLEXITY.value,
     ModelProvider.AZURE.value,
     ModelProvider.AWS.value,
@@ -51,6 +52,15 @@
     ModelProvider.SARVAM.value,
 }
 
+# Judge/evaluator LLM providers that are not wired into live voice pipelines.
+_LLM_JUDGE_ONLY_PROVIDERS = frozenset(
+    {
+        ModelProvider.TYPESAFE.value,
+    }
+)
+
+_LLM_VOICE_CAPABLE_PROVIDERS = _LLM_CAPABLE_PROVIDERS - _LLM_JUDGE_ONLY_PROVIDERS
+
 # Voice-platform integrations that also expose LLM models (credentials
 # live in the Integration table rather than AIProvider).
 _INTEGRATION_LLM_PLATFORMS = {
@@ -70,6 +80,7 @@ def _provider_label(provider_value: str) -> str:
         "mistral": "Mistral",
         "meta": "Meta",
         "together": "Together",
+        "typesafe": "TypeSafe",
         "perplexity": "Perplexity",
         "azure": "Azure",
         "aws": "AWS",
diff --git a/docs-fumadocs/content/docs/(docs)/integrations/index.mdx b/docs-fumadocs/content/docs/(docs)/integrations/index.mdx
index 58b61a93..ec914516 100644
--- a/docs-fumadocs/content/docs/(docs)/integrations/index.mdx
+++ b/docs-fumadocs/content/docs/(docs)/integrations/index.mdx
@@ -56,6 +56,7 @@ This section focuses on platform-level integration guides for teams connecting e
     { name: 'Mistral', logo: '/mistral.svg' },
     { name: 'Meta', logo: '/metaai.png' },
     { name: 'Together', logo: '/togetherai.svg' },
+    { name: 'TypeSafe', logo: '/typesafe.png' },
     { name: 'Perplexity', logo: '/perplexity-ai.svg' },
     { name: 'Azure', logo: '/azureai.png' },
     { name: 'AWS', logo: '/AWS_logo.png' },
diff --git a/frontend/public/typesafe.png b/frontend/public/typesafe.png
new file mode 100644
index 00000000..9d4a8cea
Binary files /dev/null and b/frontend/public/typesafe.png differ
diff --git a/frontend/src/components/providers/ProviderModelPicker.tsx b/frontend/src/components/providers/ProviderModelPicker.tsx
index 81021841..e723c0c0 100644
--- a/frontend/src/components/providers/ProviderModelPicker.tsx
+++ b/frontend/src/components/providers/ProviderModelPicker.tsx
@@ -52,6 +52,7 @@ const PROVIDER_LABELS: Record<string, string> = {
   mistral: 'Mistral',
   meta: 'Meta',
   together: 'Together',
+  typesafe: 'TypeSafe',
   perplexity: 'Perplexity',
   azure: 'Azure',
   aws: 'AWS',
diff --git a/frontend/src/config/llmGenerationParams.ts b/frontend/src/config/llmGenerationParams.ts
index 189cb8e9..277b2c25 100644
--- a/frontend/src/config/llmGenerationParams.ts
+++ b/frontend/src/config/llmGenerationParams.ts
@@ -107,6 +107,7 @@ const NO_TOP_K = new Set([
   'mistral',
   'meta',
   'together',
+  'typesafe',
   'perplexity',
   'aws',
 ])
diff --git a/frontend/src/config/providers.ts b/frontend/src/config/providers.ts
index 995f4091..e2070b2f 100644
--- a/frontend/src/config/providers.ts
+++ b/frontend/src/config/providers.ts
@@ -57,6 +57,11 @@ export const MODEL_PROVIDER_CONFIG: Record<ModelProvider, ProviderMetadata> = {
     logo: '/togetherai.svg',
     description: 'Hosted open-source models via Together',
   },
+  [ModelProvider.TYPESAFE]: {
+    label: 'TypeSafe',
+    logo: '/typesafe.png',
+    description: 'Jev decision classifiers via TypeSafe',
+  },
   [ModelProvider.PERPLEXITY]: {
     label: 'Perplexity',
     logo: '/perplexity-ai.svg',
diff --git a/frontend/src/pages/configurations/Integrations.tsx b/frontend/src/pages/configurations/Integrations.tsx
index d492552f..d9d8dfd6 100644
--- a/frontend/src/pages/configurations/Integrations.tsx
+++ b/frontend/src/pages/configurations/Integrations.tsx
@@ -36,6 +36,7 @@ const AI_INTEGRATION_PROVIDERS: ModelProvider[] = [
   ModelProvider.MISTRAL,
   ModelProvider.META,
   ModelProvider.TOGETHER,
+  ModelProvider.TYPESAFE,
   ModelProvider.PERPLEXITY,
   ModelProvider.AZURE,
   ModelProvider.AWS,
diff --git a/frontend/src/types/api.ts b/frontend/src/types/api.ts
index db86ed9b..4cf0ee23 100644
--- a/frontend/src/types/api.ts
+++ b/frontend/src/types/api.ts
@@ -395,6 +395,7 @@ export enum ModelProvider {
   MISTRAL = 'mistral',
   META = 'meta',
   TOGETHER = 'together',
+  TYPESAFE = 'typesafe',
   PERPLEXITY = 'perplexity',
   AZURE = 'azure',
   AWS = 'aws',
diff --git a/scripts/sync_pricing_catalog_from_litellm.py b/scripts/sync_pricing_catalog_from_litellm.py
index af1131e2..de7ee316 100644
--- a/scripts/sync_pricing_catalog_from_litellm.py
+++ b/scripts/sync_pricing_catalog_from_litellm.py
@@ -26,6 +26,8 @@
     "groq": "groq",
     "xai": "xai",
     "fireworks": "fireworks_ai",
+    "together": "together_ai",
+    "typesafe": "typesafe",
     "sarvam": "sarvam",
     "deepgram": "deepgram",
     "elevenlabs": "elevenlabs",
@@ -90,6 +92,21 @@
 
 FIREWORKS_LONG_FORM_PREFIX = "fireworks_ai/accounts/fireworks/models/"
 
+TOGETHER_SKIP_MODES = frozenset(
+    {
+        "embedding",
+        "image_generation",
+        "audio_transcription",
+        "moderation",
+        "rerank",
+    }
+)
+
+TEV1_CATALOG_NAME = "together/Tev1-4B-experimental"
+TEV1_LITELLM_KEY = f"together_ai/{TEV1_CATALOG_NAME}"
+
+TYPESAFE_SKIP_MODES = TOGETHER_SKIP_MODES
+
 
 def _azure_deployment_name(catalog_model: str) -> str:
     if catalog_model == "azure-openai-gpt4":
@@ -168,6 +185,20 @@ def _litellm_candidates(
                 catalog_name,
             ]
         )
+    elif provider == "together" and model_type == "llm":
+        candidates.extend(
+            [
+                f"together_ai/{catalog_name}",
+                catalog_name,
+            ]
+        )
+    elif provider == "typesafe" and model_type == "llm":
+        candidates.extend(
+            [
+                f"typesafe/{catalog_name}",
+                catalog_name,
+            ]
+        )
     elif provider == "elevenlabs":
         candidates.extend([f"elevenlabs/{catalog_name}", catalog_name])
     elif provider == "google" and catalog_name.endswith("-stt"):
@@ -411,6 +442,253 @@ def import_missing_fireworks(*, remote: bool = True) -> Tuple[int, List[str]]:
     return len(new_entries), sorted(new_entries.keys())
 
 
+def _together_catalog_name(litellm_key: str, info: Dict[str, Any]) -> Optional[str]:
+    """Return models.json key for an importable Together chat model, else None."""
+    mode = str(info.get("mode") or "").lower()
+    if mode in TOGETHER_SKIP_MODES:
+        return None
+
+    if not litellm_key.startswith("together_ai/"):
+        return None
+
+    slug = litellm_key[len("together_ai/") :]
+    if not slug:
+        return None
+
+    if mode and mode not in {"chat", "completion"}:
+        return None
+
+    has_llm_cost = _first_cost(info, "input_cost_per_token") or _first_cost(
+        info, "output_cost_per_token"
+    )
+    if not has_llm_cost:
+        return None
+
+    return slug
+
+
+def _together_description(catalog_name: str) -> str:
+    return f"{catalog_name.replace('/', ' ').replace('-', ' ')} via Together"
+
+
+def discover_missing_together_models(
+    model_cost: Dict[str, Dict[str, Any]],
+    existing_models: Dict[str, Any],
+) -> Dict[str, Tuple[str, Dict[str, Any]]]:
+    """Map catalog_name -> (litellm_key, info) for Together models to import."""
+    discovered: Dict[str, Tuple[str, Dict[str, Any]]] = {}
+    for litellm_key, info in model_cost.items():
+        if litellm_key == "sample_spec" or not isinstance(info, dict):
+            continue
+        catalog_name = _together_catalog_name(litellm_key, info)
+        if not catalog_name or catalog_name in existing_models:
+            continue
+        discovered[catalog_name] = (litellm_key, info)
+    return discovered
+
+
+def _insert_after_together_block(
+    models: Dict[str, Any], new_entries: Dict[str, Any]
+) -> Dict[str, Any]:
+    if not new_entries:
+        return models
+
+    keys = [key for key in models if not key.startswith("_")]
+    insert_at = 0
+    for index, key in enumerate(keys):
+        cfg = models[key]
+        if isinstance(cfg, dict) and cfg.get("provider") == "together":
+            insert_at = index + 1
+
+    if insert_at == 0:
+        for index, key in enumerate(keys):
+            cfg = models[key]
+            if isinstance(cfg, dict) and cfg.get("provider") == "fireworks":
+                insert_at = index + 1
+
+    ordered_keys = keys[:insert_at] + sorted(new_entries.keys()) + keys[insert_at:]
+    ordered: Dict[str, Any] = {}
+    for key in ordered_keys:
+        if key in new_entries:
+            ordered[key] = new_entries[key]
+        else:
+            ordered[key] = models[key]
+    for key, value in models.items():
+        if key.startswith("_"):
+            ordered[key] = value
+    return ordered
+
+
+def _tev1_manual_entry() -> Dict[str, Any]:
+    return {
+        "provider": "together",
+        "model_type": "llm",
+        "description": "Tev1 4B Jev-style decision classifier on Qwen3.5 4B via Together",
+        "pricing": {
+            "source": "together.ai serverless listing",
+            "usage_kind": "llm",
+            "input_per_1m": 0.042,
+            "output_per_1m": 0,
+        },
+    }
+
+
+def import_missing_together(*, remote: bool = True) -> Tuple[int, List[str]]:
+    """Add current Together serverless chat models missing from models.json."""
+    models = json.loads(MODELS_JSON.read_text(encoding="utf-8"))
+    model_cost = _load_model_cost(remote=remote)
+    missing = discover_missing_together_models(model_cost, models)
+
+    new_entries: Dict[str, Any] = {}
+    for catalog_name in sorted(missing):
+        _litellm_key, info = missing[catalog_name]
+        micro = _convert_litellm_pricing(info, usage_kind="llm")
+        pricing = _micro_pricing_to_plan(micro, usage_kind="llm")
+        if not pricing.get("input_per_1m") and not pricing.get("output_per_1m"):
+            continue
+        new_entries[catalog_name] = {
+            "provider": "together",
+            "model_type": "llm",
+            "description": _together_description(catalog_name),
+            "pricing": pricing,
+        }
+
+    if TEV1_CATALOG_NAME not in models and TEV1_CATALOG_NAME not in new_entries:
+        tev1_info = model_cost.get(TEV1_LITELLM_KEY)
+        if tev1_info:
+            micro = _convert_litellm_pricing(tev1_info, usage_kind="llm")
+            pricing = _micro_pricing_to_plan(micro, usage_kind="llm")
+            if pricing.get("input_per_1m") or pricing.get("output_per_1m"):
+                new_entries[TEV1_CATALOG_NAME] = {
+                    "provider": "together",
+                    "model_type": "llm",
+                    "description": _tev1_manual_entry()["description"],
+                    "pricing": pricing,
+                }
+            else:
+                new_entries[TEV1_CATALOG_NAME] = _tev1_manual_entry()
+        else:
+            new_entries[TEV1_CATALOG_NAME] = _tev1_manual_entry()
+
+    if not new_entries:
+        return 0, []
+
+    updated_models = _insert_after_together_block(models, new_entries)
+    MODELS_JSON.write_text(
+        json.dumps(updated_models, indent=2, ensure_ascii=False) + "\n",
+        encoding="utf-8",
+    )
+    return len(new_entries), sorted(new_entries.keys())
+
+
+def _typesafe_catalog_name(litellm_key: str, info: Dict[str, Any]) -> Optional[str]:
+    """Return models.json key for an importable TypeSafe chat model, else None."""
+    mode = str(info.get("mode") or "").lower()
+    if mode in TYPESAFE_SKIP_MODES:
+        return None
+
+    if not litellm_key.startswith("typesafe/"):
+        return None
+
+    slug = litellm_key[len("typesafe/") :]
+    if not slug:
+        return None
+
+    if mode and mode not in {"chat", "completion", "evaluation"}:
+        return None
+
+    has_llm_cost = _first_cost(info, "input_cost_per_token") or _first_cost(
+        info, "output_cost_per_token"
+    )
+    if not has_llm_cost:
+        return None
+
+    return slug
+
+
+def _typesafe_description(catalog_name: str) -> str:
+    return f"{catalog_name.replace('-', ' ')} via TypeSafe"
+
+
+def discover_missing_typesafe_models(
+    model_cost: Dict[str, Dict[str, Any]],
+    existing_models: Dict[str, Any],
+) -> Dict[str, Tuple[str, Dict[str, Any]]]:
+    """Map catalog_name -> (litellm_key, info) for TypeSafe models to import."""
+    discovered: Dict[str, Tuple[str, Dict[str, Any]]] = {}
+    for litellm_key, info in model_cost.items():
+        if litellm_key == "sample_spec" or not isinstance(info, dict):
+            continue
+        catalog_name = _typesafe_catalog_name(litellm_key, info)
+        if not catalog_name or catalog_name in existing_models:
+            continue
+        discovered[catalog_name] = (litellm_key, info)
+    return discovered
+
+
+def _insert_after_typesafe_block(
+    models: Dict[str, Any], new_entries: Dict[str, Any]
+) -> Dict[str, Any]:
+    if not new_entries:
+        return models
+
+    keys = [key for key in models if not key.startswith("_")]
+    insert_at = 0
+    for index, key in enumerate(keys):
+        cfg = models[key]
+        if isinstance(cfg, dict) and cfg.get("provider") == "typesafe":
+            insert_at = index + 1
+
+    if insert_at == 0:
+        for index, key in enumerate(keys):
+            cfg = models[key]
+            if isinstance(cfg, dict) and cfg.get("provider") == "together":
+                insert_at = index + 1
+
+    ordered_keys = keys[:insert_at] + sorted(new_entries.keys()) + keys[insert_at:]
+    ordered: Dict[str, Any] = {}
+    for key in ordered_keys:
+        if key in new_entries:
+            ordered[key] = new_entries[key]
+        else:
+            ordered[key] = models[key]
+    for key, value in models.items():
+        if key.startswith("_"):
+            ordered[key] = value
+    return ordered
+
+
+def import_missing_typesafe(*, remote: bool = True) -> Tuple[int, List[str]]:
+    """Add current TypeSafe chat models missing from models.json."""
+    models = json.loads(MODELS_JSON.read_text(encoding="utf-8"))
+    model_cost = _load_model_cost(remote=remote)
+    missing = discover_missing_typesafe_models(model_cost, models)
+
+    new_entries: Dict[str, Any] = {}
+    for catalog_name in sorted(missing):
+        _litellm_key, info = missing[catalog_name]
+        micro = _convert_litellm_pricing(info, usage_kind="llm")
+        pricing = _micro_pricing_to_plan(micro, usage_kind="llm")
+        if not pricing.get("input_per_1m") and not pricing.get("output_per_1m"):
+            continue
+        new_entries[catalog_name] = {
+            "provider": "typesafe",
+            "model_type": "llm",
+            "description": _typesafe_description(catalog_name),
+            "pricing": pricing,
+        }
+
+    if not new_entries:
+        return 0, []
+
+    updated_models = _insert_after_typesafe_block(models, new_entries)
+    MODELS_JSON.write_text(
+        json.dumps(updated_models, indent=2, ensure_ascii=False) + "\n",
+        encoding="utf-8",
+    )
+    return len(new_entries), sorted(new_entries.keys())
+
+
 def _load_model_cost(*, remote: bool) -> Dict[str, Dict[str, Any]]:
     if remote:
         from litellm.litellm_core_utils.get_model_cost_map import get_model_cost_map
@@ -553,6 +831,16 @@ def main() -> int:
         action="store_true",
         help="Add current Fireworks serverless chat models missing from models.json",
     )
+    parser.add_argument(
+        "--import-missing-together",
+        action="store_true",
+        help="Add current Together serverless chat models missing from models.json",
+    )
+    parser.add_argument(
+        "--import-missing-typesafe",
+        action="store_true",
+        help="Add current TypeSafe chat models missing from models.json",
+    )
     args = parser.parse_args()
 
     if args.import_missing_fireworks:
@@ -564,6 +852,24 @@ def main() -> int:
         for name in names:
             print(f"  added: {name}", file=sys.stderr)
 
+    if args.import_missing_together:
+        imported, names = import_missing_together(remote=not args.local)
+        print(
+            f"together import: {imported} model(s) added to models.json",
+            file=sys.stderr,
+        )
+        for name in names:
+            print(f"  added: {name}", file=sys.stderr)
+
+    if args.import_missing_typesafe:
+        imported, names = import_missing_typesafe(remote=not args.local)
+        print(
+            f"typesafe import: {imported} model(s) added to models.json",
+            file=sys.stderr,
+        )
+        for name in names:
+            print(f"  added: {name}", file=sys.stderr)
+
     catalog, meta = build_catalog(remote=not args.local)
     payload = json.dumps(catalog, indent=2, sort_keys=True) + "\n"
     if args.stdout:
diff --git a/tests/test_scripts/test_sync_together_import.py b/tests/test_scripts/test_sync_together_import.py
new file mode 100644
index 00000000..aa17b409
--- /dev/null
+++ b/tests/test_scripts/test_sync_together_import.py
@@ -0,0 +1,104 @@
+"""Tests for Together model import filter in sync_pricing_catalog_from_litellm."""
+
+from __future__ import annotations
+
+import importlib.util
+from pathlib import Path
+
+import pytest
+
+REPO_ROOT = Path(__file__).resolve().parents[2]
+SYNC_SCRIPT = REPO_ROOT / "scripts" / "sync_pricing_catalog_from_litellm.py"
+
+
+def _load_sync_module():
+    spec = importlib.util.spec_from_file_location(
+        "sync_pricing_catalog_from_litellm", SYNC_SCRIPT
+    )
+    module = importlib.util.module_from_spec(spec)
+    assert spec.loader is not None
+    spec.loader.exec_module(module)
+    return module
+
+
+@pytest.fixture(name="sync_mod")
+def fixture_sync_mod():
+    return _load_sync_module()
+
+
+def _chat_cost(**overrides):
+    base = {
+        "mode": "chat",
+        "input_cost_per_token": 0.000000042,
+        "output_cost_per_token": 0.0,
+    }
+    base.update(overrides)
+    return base
+
+
+def test_together_catalog_name_accepts_slash_slug(sync_mod):
+    key = "together_ai/meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo"
+    assert (
+        sync_mod._together_catalog_name(key, _chat_cost())
+        == "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo"
+    )
+
+
+def test_together_catalog_name_accepts_tev1(sync_mod):
+    key = "together_ai/together/Tev1-4B-experimental"
+    assert (
+        sync_mod._together_catalog_name(key, _chat_cost())
+        == "together/Tev1-4B-experimental"
+    )
+
+
+def test_together_catalog_name_skips_embeddings(sync_mod):
+    key = "together_ai/togethercomputer/m2-bert-80M-8k-retrieval"
+    info = {
+        "mode": "embedding",
+        "input_cost_per_token": 0.000000008,
+        "output_cost_per_token": 0,
+    }
+    assert sync_mod._together_catalog_name(key, info) is None
+
+
+def test_discover_missing_together_models_skips_existing(sync_mod):
+    model_cost = {
+        "together_ai/meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo": _chat_cost(),
+        "together_ai/together/Tev1-4B-experimental": _chat_cost(),
+        "together_ai/togethercomputer/m2-bert-80M-8k-retrieval": {
+            "mode": "embedding",
+            "input_cost_per_token": 0.000000008,
+        },
+    }
+    existing = {
+        "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo": {
+            "provider": "together",
+            "model_type": "llm",
+        },
+    }
+    discovered = sync_mod.discover_missing_together_models(model_cost, existing)
+    assert set(discovered) == {"together/Tev1-4B-experimental"}
+
+
+def test_insert_after_together_block_preserves_existing(sync_mod):
+    models = {
+        "gpt-4o": {"provider": "openai", "model_type": "llm"},
+        "deepseek-v4-pro": {"provider": "fireworks", "model_type": "llm"},
+        "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo": {
+            "provider": "together",
+            "model_type": "llm",
+        },
+        "google-speech-v2": {"provider": "google", "model_type": "stt"},
+    }
+    new_entries = {
+        "together/Tev1-4B-experimental": {"provider": "together", "model_type": "llm"},
+    }
+    ordered = sync_mod._insert_after_together_block(models, new_entries)
+    assert list(ordered.keys()) == [
+        "gpt-4o",
+        "deepseek-v4-pro",
+        "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo",
+        "together/Tev1-4B-experimental",
+        "google-speech-v2",
+    ]
diff --git a/tests/test_scripts/test_sync_typesafe_import.py b/tests/test_scripts/test_sync_typesafe_import.py
new file mode 100644
index 00000000..c94330e1
--- /dev/null
+++ b/tests/test_scripts/test_sync_typesafe_import.py
@@ -0,0 +1,73 @@
+"""Tests for TypeSafe model import filter in sync_pricing_catalog_from_litellm."""
+
+from __future__ import annotations
+
+import importlib.util
+from pathlib import Path
+
+import pytest
+
+REPO_ROOT = Path(__file__).resolve().parents[2]
+SYNC_SCRIPT = REPO_ROOT / "scripts" / "sync_pricing_catalog_from_litellm.py"
+
+
+def _load_sync_module():
+    spec = importlib.util.spec_from_file_location(
+        "sync_pricing_catalog_from_litellm", SYNC_SCRIPT
+    )
+    module = importlib.util.module_from_spec(spec)
+    assert spec.loader is not None
+    spec.loader.exec_module(module)
+    return module
+
+
+@pytest.fixture(name="sync_mod")
+def fixture_sync_mod():
+    return _load_sync_module()
+
+
+def _chat_cost(**overrides):
+    base = {
+        "mode": "chat",
+        "input_cost_per_token": 0.00000015,
+        "output_cost_per_token": 0.0000006,
+    }
+    base.update(overrides)
+    return base
+
+
+def test_typesafe_catalog_name_accepts_jev_slug(sync_mod):
+    key = "typesafe/jev-1.13.0"
+    assert sync_mod._typesafe_catalog_name(key, _chat_cost()) == "jev-1.13.0"
+
+
+def test_typesafe_catalog_name_accepts_evaluation_mode(sync_mod):
+    key = "typesafe/jev-1.13.0"
+    info = {
+        "mode": "evaluation",
+        "input_cost_per_token": 0.000000042,
+        "output_cost_per_token": 0.0,
+    }
+    assert sync_mod._typesafe_catalog_name(key, info) == "jev-1.13.0"
+
+
+def test_typesafe_catalog_name_skips_embeddings(sync_mod):
+    key = "typesafe/jev-embed-v1"
+    info = {
+        "mode": "embedding",
+        "input_cost_per_token": 0.000000008,
+        "output_cost_per_token": 0,
+    }
+    assert sync_mod._typesafe_catalog_name(key, info) is None
+
+
+def test_discover_missing_typesafe_models_skips_existing(sync_mod):
+    model_cost = {
+        "typesafe/jev-1.13.0": _chat_cost(),
+        "typesafe/jev-1.12.0": _chat_cost(),
+    }
+    existing = {
+        "jev-1.13.0": {"provider": "typesafe", "model_type": "llm"},
+    }
+    discovered = sync_mod.discover_missing_typesafe_models(model_cost, existing)
+    assert set(discovered) == {"jev-1.12.0"}
diff --git a/tests/test_services/test_ai/test_llm_service.py b/tests/test_services/test_ai/test_llm_service.py
index f9dcb666..f8aa26af 100644
--- a/tests/test_services/test_ai/test_llm_service.py
+++ b/tests/test_services/test_ai/test_llm_service.py
@@ -53,6 +53,22 @@ def test_litellm_model_name_maps_known_provider_prefixes():
         LLMService._litellm_model_name(ModelProvider.FIREWORKS, "deepseek-v4-pro")
         == "fireworks_ai/accounts/fireworks/models/deepseek-v4-pro"
     )
+    assert (
+        LLMService._litellm_model_name(
+            ModelProvider.TOGETHER, "together/Tev1-4B-experimental"
+        )
+        == "together_ai/together/Tev1-4B-experimental"
+    )
+    assert (
+        LLMService._litellm_model_name(
+            ModelProvider.TOGETHER, "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo"
+        )
+        == "together_ai/meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo"
+    )
+    assert (
+        LLMService._litellm_model_name(ModelProvider.TYPESAFE, "jev-1.13.0")
+        == "typesafe/jev-1.13.0"
+    )
     assert (
         LLMService._litellm_model_name(ModelProvider.SARVAM, "sarvam-30b")
         == "sarvam/sarvam-30b"
diff --git a/tests/test_services/test_ai/test_model_config_together.py b/tests/test_services/test_ai/test_model_config_together.py
new file mode 100644
index 00000000..08859e91
--- /dev/null
+++ b/tests/test_services/test_ai/test_model_config_together.py
@@ -0,0 +1,10 @@
+"""Ensure Together LLM models are present in the model catalog."""
+
+from app.models.database import ModelProvider
+from app.services.ai.model_config_service import model_config_service
+
+
+def test_together_llm_models_in_catalog():
+    llm_models = model_config_service.get_models_by_type(ModelProvider.TOGETHER, "llm")
+    assert "together/Tev1-4B-experimental" in llm_models
+    assert "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo" in llm_models
diff --git a/tests/test_services/test_ai/test_model_config_typesafe.py b/tests/test_services/test_ai/test_model_config_typesafe.py
new file mode 100644
index 00000000..88f42c56
--- /dev/null
+++ b/tests/test_services/test_ai/test_model_config_typesafe.py
@@ -0,0 +1,9 @@
+"""Ensure TypeSafe LLM models are present in the model catalog."""
+
+from app.models.database import ModelProvider
+from app.services.ai.model_config_service import model_config_service
+
+
+def test_typesafe_llm_models_in_catalog():
+    llm_models = model_config_service.get_models_by_type(ModelProvider.TYPESAFE, "llm")
+    assert "jev-1.13.0" in llm_models
diff --git a/tests/test_services/test_voice_agent/test_llm_voice_providers.py b/tests/test_services/test_voice_agent/test_llm_voice_providers.py
index 999b95ab..75ae5286 100644
--- a/tests/test_services/test_voice_agent/test_llm_voice_providers.py
+++ b/tests/test_services/test_voice_agent/test_llm_voice_providers.py
@@ -1,6 +1,6 @@
 """Tests for live voice pipeline LLM provider registry."""
 
-from app.services.judge_alignment.model_catalog import _LLM_CAPABLE_PROVIDERS
+from app.services.judge_alignment.model_catalog import _LLM_VOICE_CAPABLE_PROVIDERS
 from app.services.voice_agent.llm_voice_providers import (
     LLM_VOICE_PROVIDER_KEYS,
     get_llm_provider_registry,
@@ -9,7 +9,7 @@
 
 
 def test_voice_llm_registry_covers_configurable_providers():
-    assert LLM_VOICE_PROVIDER_KEYS == _LLM_CAPABLE_PROVIDERS
+    assert LLM_VOICE_PROVIDER_KEYS == _LLM_VOICE_CAPABLE_PROVIDERS
 
     def _fake_get_service(name: str):
         return lambda **kwargs: (name, kwargs)