diff --git a/config.toml b/config.toml
index 89e94ed52..a407989fd 100644
--- a/config.toml
+++ b/config.toml
@@ -26,6 +26,21 @@ simple_model = "gemini-3-flash"
 complex_model = "gemini-3-pro"
 embeddings_model = "text-embedding-004"
 
+[minimax]
+simple_model = "MiniMax-M2.7"
+complex_model = "MiniMax-M3"
+embeddings_model = ""
+protocol = "openai"
+region = "global_en"
+
+[minimax.endpoints.global_en]
+openai_base_url = "https://api.minimax.io/v1"
+anthropic_base_url = "https://api.minimax.io/anthropic"
+
+[minimax.endpoints.cn_zh]
+openai_base_url = "https://api.minimaxi.com/v1"
+anthropic_base_url = "https://api.minimaxi.com/anthropic"
+
 [tracing]
 project = "rai"
 
diff --git a/docs/setup/vendors.md b/docs/setup/vendors.md
index 855f0add7..e17167829 100644
--- a/docs/setup/vendors.md
+++ b/docs/setup/vendors.md
@@ -9,9 +9,9 @@ Alternatively vendors can be configured manually in `config.toml` file.
 
 The table summarizes vendor alternative for core AI service and optional RAI modules:
 
-| Module                                          | Open source        | Alternative             | Why to consider alternative?                                             | More information                                                                                                                                                                 |
-| ----------------------------------------------- | ------------------ | ----------------------- | ------------------------------------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| [LLM service](#llm-model-configuration-in-rai)  | Ollama             | OpenAI, Bedrock         | Overall performance of the LLM models, supported modalities and features | [LangChain models](https://docs.langchain4j.dev/integrations/language-models/)                                                                                                   |
+| Module                                          | Open source        | Alternative                      | Why to consider alternative?                                             | More information                                                                                                                                                                 |
+| ----------------------------------------------- | ------------------ | -------------------------------- | ------------------------------------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| [LLM service](#llm-model-configuration-in-rai)  | Ollama             | OpenAI, Bedrock, MiniMax         | Overall performance of the LLM models, supported modalities and features | [LangChain models](https://docs.langchain4j.dev/integrations/language-models/)                                                                                                   |
 | **Optional:** [Tracing tool](./tracing.md)      | Langfuse           | LangSmith               | Better integration with LangChain                                        | [Comparison](https://langfuse.com/faq/all/langsmith-alternative)                                                                                                                 |
 | **Optional:** [Text to speech](#text-to-speech) | KokoroTTS, OpenTTS | ElevenLabs              | Arguably, significantly better voice synthesis                           | <li> [KokoroTTS](https://huggingface.co/hexgrad/Kokoro-82M#usage) </li><li> [OpenTTS GitHub](https://github.com/synesthesiam/opentts) </li><li> [RAI voice interface][s2s] </li> |
 | **Optional:** [Speech to text](#speech-to-text) | Whisper            | OpenAI Whisper (hosted) | When suitable local GPU is not an option                                 | <li> [Whisper GitHub](https://github.com/openai/whisper) </li><li> [RAI voice interface][s2s] </li>                                                                              |
@@ -67,6 +67,47 @@ Ollama can be used to host models locally.
 
 2. Use [RAI Configurator][configurator] -> `Model Selection` -> `bedrock` vendor
 
+### MiniMax
+
+MiniMax can be configured through either its OpenAI-compatible or Anthropic-compatible
+chat API. Set the API key before starting RAI:
+
+```bash
+export MINIMAX_API_KEY="your-api-key"
+```
+
+The generated `config.toml` contains both supported regions and both protocols. Select the
+active combination with `protocol` and `region`:
+
+```toml
+[vendor]
+simple_model = "minimax"
+complex_model = "minimax"
+
+[minimax]
+simple_model = "MiniMax-M2.7"
+complex_model = "MiniMax-M3"
+embeddings_model = ""
+protocol = "openai"
+region = "global_en"
+
+[minimax.endpoints.global_en]
+openai_base_url = "https://api.minimax.io/v1"
+anthropic_base_url = "https://api.minimax.io/anthropic"
+
+[minimax.endpoints.cn_zh]
+openai_base_url = "https://api.minimaxi.com/v1"
+anthropic_base_url = "https://api.minimaxi.com/anthropic"
+```
+
+The Anthropic-compatible base URL must end in `/anthropic`; the client appends the
+`/v1/messages` request path. MiniMax does not provide an embeddings model in this
+configuration, so keep `embeddings_model` assigned to a separate supported vendor.
+
+See the [global API documentation](https://platform.minimax.io/docs/api-reference/api-overview)
+or the [China API documentation](https://platform.minimaxi.com/docs/api-reference/api-overview)
+for service-specific details.
+
 ## Complex LLM Model Configuration
 
 For custom setups please use LangChain API.
diff --git a/src/rai_core/pyproject.toml b/src/rai_core/pyproject.toml
index d7c3e5ae8..51c78bdbc 100644
--- a/src/rai_core/pyproject.toml
+++ b/src/rai_core/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "rai_core"
-version = "2.12.1"
+version = "2.13.0"
 description = "Core functionality for RAI framework"
 readme = "README.md"
 requires-python = ">=3.10,<3.13"
@@ -21,6 +21,7 @@ dependencies = [
     "langchain>=1.0.0,<2.0.0",
     "langchain-aws",
     "langchain-openai",
+    "langchain-anthropic",
     "langchain-ollama",
     "langchain-google-genai",
     "langchain-community",
diff --git a/src/rai_core/rai/initialization/config_initialization.py b/src/rai_core/rai/initialization/config_initialization.py
index 94028b252..5b16ff690 100644
--- a/src/rai_core/rai/initialization/config_initialization.py
+++ b/src/rai_core/rai/initialization/config_initialization.py
@@ -47,6 +47,21 @@
 complex_model = "gemini-3-pro"
 embeddings_model = "text-embedding-004"
 
+[minimax]
+simple_model = "MiniMax-M2.7"
+complex_model = "MiniMax-M3"
+embeddings_model = ""
+protocol = "openai"
+region = "global_en"
+
+[minimax.endpoints.global_en]
+openai_base_url = "https://api.minimax.io/v1"
+anthropic_base_url = "https://api.minimax.io/anthropic"
+
+[minimax.endpoints.cn_zh]
+openai_base_url = "https://api.minimaxi.com/v1"
+anthropic_base_url = "https://api.minimaxi.com/anthropic"
+
 [tracing]
 project = "rai"
 
diff --git a/src/rai_core/rai/initialization/model_initialization.py b/src/rai_core/rai/initialization/model_initialization.py
index 6cd5d7e42..22fc8d6bb 100644
--- a/src/rai_core/rai/initialization/model_initialization.py
+++ b/src/rai_core/rai/initialization/model_initialization.py
@@ -67,6 +67,19 @@ class GoogleConfig(ModelConfig):
     pass
 
 
+@dataclass
+class MiniMaxEndpointConfig:
+    openai_base_url: str
+    anthropic_base_url: str
+
+
+@dataclass
+class MiniMaxConfig(ModelConfig):
+    protocol: Literal["openai", "anthropic"]
+    region: str
+    endpoints: Dict[str, MiniMaxEndpointConfig]
+
+
 @dataclass
 class LangfuseConfig:
     use_langfuse: bool
@@ -93,6 +106,7 @@ class RAIConfig:
     openai: OpenAIConfig
     ollama: OllamaConfig
     google: GoogleConfig
+    minimax: MiniMaxConfig
     tracing: TracingConfig
 
 
@@ -107,6 +121,14 @@ class RAIConfig:
     simple_model="", complex_model="", embeddings_model="", base_url=""
 )
 _DEFAULT_GOOGLE = GoogleConfig(simple_model="", complex_model="", embeddings_model="")
+_DEFAULT_MINIMAX = MiniMaxConfig(
+    simple_model="",
+    complex_model="",
+    embeddings_model="",
+    protocol="openai",
+    region="global_en",
+    endpoints={},
+)
 _DEFAULT_TRACING = TracingConfig(
     project="",
     langfuse=LangfuseConfig(use_langfuse=False, host=""),
@@ -140,6 +162,21 @@ def load_config(config_path: Optional[str] = None) -> RAIConfig:
         if "google" in config_dict
         else _DEFAULT_GOOGLE
     )
+    if "minimax" in config_dict:
+        minimax_dict = config_dict["minimax"]
+        minimax = MiniMaxConfig(
+            simple_model=minimax_dict["simple_model"],
+            complex_model=minimax_dict["complex_model"],
+            embeddings_model=minimax_dict.get("embeddings_model", ""),
+            protocol=minimax_dict.get("protocol", "openai"),
+            region=minimax_dict.get("region", "global_en"),
+            endpoints={
+                region: MiniMaxEndpointConfig(**endpoint)
+                for region, endpoint in minimax_dict.get("endpoints", {}).items()
+            },
+        )
+    else:
+        minimax = _DEFAULT_MINIMAX
 
     if "tracing" in config_dict:
         tracing = TracingConfig(
@@ -156,10 +193,48 @@ def load_config(config_path: Optional[str] = None) -> RAIConfig:
         openai=openai,
         ollama=ollama,
         google=google,
+        minimax=minimax,
         tracing=tracing,
     )
 
 
+def _create_minimax_chat_model(
+    model: str,
+    model_config: MiniMaxConfig,
+    kwargs: Dict[str, Any],
+) -> Any:
+    try:
+        endpoint = model_config.endpoints[model_config.region]
+    except KeyError as exc:
+        raise ValueError(
+            f"MiniMax endpoint is not configured for region: {model_config.region}"
+        ) from exc
+
+    model_kwargs = dict(kwargs)
+    if "api_key" not in model_kwargs:
+        api_key = os.getenv("MINIMAX_API_KEY")
+        if api_key:
+            model_kwargs["api_key"] = api_key
+
+    if model_config.protocol == "openai":
+        from langchain_openai import ChatOpenAI
+
+        return ChatOpenAI(
+            model=model,
+            base_url=endpoint.openai_base_url,
+            **model_kwargs,
+        )
+    if model_config.protocol == "anthropic":
+        from langchain_anthropic import ChatAnthropic
+
+        return ChatAnthropic(
+            model=model,
+            base_url=endpoint.anthropic_base_url,
+            **model_kwargs,
+        )
+    raise ValueError(f"Unknown MiniMax protocol: {model_config.protocol}")
+
+
 def get_llm_model_config_and_vendor(
     model_type: Literal["simple_model", "complex_model"],
     vendor: Optional[str] = None,
@@ -213,6 +288,12 @@ def get_llm_model(
 
         model_config = cast(GoogleConfig, model_config)
         return ChatGoogleGenerativeAI(model=model, **kwargs)
+    elif vendor == "minimax":
+        return _create_minimax_chat_model(
+            model,
+            cast(MiniMaxConfig, model_config),
+            kwargs,
+        )
     else:
         raise ValueError(f"Unknown LLM vendor: {vendor}")
 
@@ -255,6 +336,12 @@ def get_llm_model_direct(
 
         model_config = cast(GoogleConfig, model_config)
         return ChatGoogleGenerativeAI(model=model_name, **kwargs)
+    elif vendor == "minimax":
+        return _create_minimax_chat_model(
+            model_name,
+            cast(MiniMaxConfig, model_config),
+            kwargs,
+        )
     else:
         raise ValueError(f"Unknown LLM vendor: {vendor}")
 
@@ -268,6 +355,12 @@ def get_embeddings_model(
 
     model_config = getattr(config, vendor)
 
+    if vendor == "minimax":
+        raise ValueError(
+            "MiniMax does not provide an embeddings model. "
+            "Configure embeddings with a separate supported vendor."
+        )
+
     logger.info(f"Using embeddings model: {vendor}-{model_config.embeddings_model}")
     if vendor == "openai":
         from langchain_openai import OpenAIEmbeddings
diff --git a/tests/initialization/test_minimax_initialization.py b/tests/initialization/test_minimax_initialization.py
new file mode 100644
index 000000000..a6e779c20
--- /dev/null
+++ b/tests/initialization/test_minimax_initialization.py
@@ -0,0 +1,183 @@
+# Copyright (C) 2026 Robotec.AI
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#         http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import json
+import threading
+from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
+from pathlib import Path
+
+import pytest
+from rai.initialization import model_initialization
+
+MINIMAX_CONFIG_TEMPLATE = """
+[vendor]
+simple_model = "minimax"
+complex_model = "minimax"
+embeddings_model = "openai"
+
+[openai]
+simple_model = "gpt-4o-mini"
+complex_model = "gpt-4o"
+embeddings_model = "text-embedding-3-small"
+base_url = "https://api.openai.com/v1"
+
+[minimax]
+simple_model = "MiniMax-M2.7"
+complex_model = "MiniMax-M3"
+embeddings_model = ""
+protocol = "openai"
+region = "global_en"
+
+[minimax.endpoints.global_en]
+openai_base_url = "https://api.minimax.io/v1"
+anthropic_base_url = "https://api.minimax.io/anthropic"
+
+[minimax.endpoints.cn_zh]
+openai_base_url = "https://api.minimaxi.com/v1"
+anthropic_base_url = "https://api.minimaxi.com/anthropic"
+"""
+
+
+class DummyModel:
+    def __init__(self, *args, **kwargs):
+        self.args = args
+        self.kwargs = kwargs
+
+
+def write_config(path: Path, config: str = MINIMAX_CONFIG_TEMPLATE) -> Path:
+    path.write_text(config, encoding="utf-8")
+    return path
+
+
+def test_load_config_preserves_models_and_endpoints(tmp_path):
+    config = model_initialization.load_config(
+        str(write_config(tmp_path / "config.toml"))
+    )
+
+    assert config.minimax.simple_model == "MiniMax-M2.7"
+    assert config.minimax.complex_model == "MiniMax-M3"
+    assert config.minimax.endpoints["global_en"].openai_base_url.endswith("/v1")
+    assert config.minimax.endpoints["global_en"].anthropic_base_url.endswith(
+        "/anthropic"
+    )
+    assert config.minimax.endpoints["cn_zh"].openai_base_url.endswith("/v1")
+    assert config.minimax.endpoints["cn_zh"].anthropic_base_url.endswith("/anthropic")
+
+
+def test_get_llm_model_uses_openai_protocol_and_selected_region(monkeypatch, tmp_path):
+    config_path = write_config(tmp_path / "config.toml")
+    monkeypatch.setenv("MINIMAX_API_KEY", "test-key")
+    monkeypatch.setattr("langchain_openai.ChatOpenAI", DummyModel)
+
+    model = model_initialization.get_llm_model(
+        "complex_model", vendor="minimax", config_path=str(config_path)
+    )
+
+    assert isinstance(model, DummyModel)
+    assert model.kwargs["model"] == "MiniMax-M3"
+    assert model.kwargs["base_url"] == "https://api.minimax.io/v1"
+    assert model.kwargs["api_key"] == "test-key"
+
+
+def test_get_llm_model_uses_anthropic_protocol(monkeypatch, tmp_path):
+    config = MINIMAX_CONFIG_TEMPLATE.replace(
+        'protocol = "openai"', 'protocol = "anthropic"'
+    )
+    config_path = write_config(tmp_path / "config.toml", config)
+    monkeypatch.setattr("langchain_anthropic.ChatAnthropic", DummyModel)
+
+    model = model_initialization.get_llm_model(
+        "simple_model", vendor="minimax", config_path=str(config_path)
+    )
+
+    assert isinstance(model, DummyModel)
+    assert model.kwargs["model"] == "MiniMax-M2.7"
+    assert model.kwargs["base_url"] == "https://api.minimax.io/anthropic"
+
+
+def test_get_llm_model_direct_preserves_explicit_api_key(monkeypatch, tmp_path):
+    config_path = write_config(tmp_path / "config.toml")
+    monkeypatch.setenv("MINIMAX_API_KEY", "environment-key")
+    monkeypatch.setattr("langchain_openai.ChatOpenAI", DummyModel)
+
+    model = model_initialization.get_llm_model_direct(
+        "MiniMax-M3",
+        vendor="minimax",
+        config_path=str(config_path),
+        api_key="explicit-key",
+    )
+
+    assert model.kwargs["api_key"] == "explicit-key"
+
+
+def test_get_embeddings_model_rejects_minimax(tmp_path):
+    config = MINIMAX_CONFIG_TEMPLATE.replace(
+        'embeddings_model = "openai"', 'embeddings_model = "minimax"'
+    )
+    config_path = write_config(tmp_path / "config.toml", config)
+
+    with pytest.raises(ValueError, match="does not provide an embeddings model"):
+        model_initialization.get_embeddings_model(config_path=str(config_path))
+
+
+class CaptureHandler(BaseHTTPRequestHandler):
+    request_path = ""
+
+    def do_POST(self):  # noqa: N802
+        self.__class__.request_path = self.path
+        content_length = int(self.headers.get("content-length", "0"))
+        self.rfile.read(content_length)
+        response = {
+            "id": "message-test",
+            "type": "message",
+            "role": "assistant",
+            "model": "MiniMax-M3",
+            "content": [{"type": "text", "text": "ok"}],
+            "stop_reason": "end_turn",
+            "stop_sequence": None,
+            "usage": {"input_tokens": 1, "output_tokens": 1},
+        }
+        payload = json.dumps(response).encode("utf-8")
+        self.send_response(200)
+        self.send_header("Content-Type", "application/json")
+        self.send_header("Content-Length", str(len(payload)))
+        self.end_headers()
+        self.wfile.write(payload)
+
+    def log_message(self, format, *args):  # noqa: A002
+        return
+
+
+def test_anthropic_client_appends_messages_path(tmp_path, monkeypatch):
+    server = ThreadingHTTPServer(("127.0.0.1", 0), CaptureHandler)
+    thread = threading.Thread(target=server.serve_forever, daemon=True)
+    thread.start()
+    try:
+        base_url = f"http://127.0.0.1:{server.server_port}/anthropic"
+        config = MINIMAX_CONFIG_TEMPLATE.replace(
+            'protocol = "openai"', 'protocol = "anthropic"'
+        ).replace("https://api.minimax.io/anthropic", base_url)
+        config_path = write_config(tmp_path / "config.toml", config)
+        monkeypatch.setenv("MINIMAX_API_KEY", "test-key")
+
+        model = model_initialization.get_llm_model(
+            "complex_model", vendor="minimax", config_path=str(config_path)
+        )
+        response = model.invoke("Say hello")
+
+        assert response.content == "ok"
+        assert CaptureHandler.request_path == "/anthropic/v1/messages"
+    finally:
+        server.shutdown()
+        thread.join(timeout=5)
diff --git a/uv.lock b/uv.lock
index a430dfcd9..5218b1228 100644
--- a/uv.lock
+++ b/uv.lock
@@ -186,6 +186,25 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" },
 ]
 
+[[package]]
+name = "anthropic"
+version = "0.116.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "anyio" },
+    { name = "distro" },
+    { name = "docstring-parser" },
+    { name = "httpx" },
+    { name = "jiter" },
+    { name = "pydantic" },
+    { name = "sniffio" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/66/a2/d31f14e28d49bae983a3634e38dfb4b31c50110b5e403596c5c6a20b23f8/anthropic-0.116.0.tar.gz", hash = "sha256:5fc248fbb9fe03ef686f8a774f81586bca31a043260aab88b387ea3660f4a396", size = 949149, upload-time = "2026-07-02T19:08:10.534Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/c7/dd/2a1e81cf1b163acc340afc4ec74ed1d86f5eed1a809fabdeed3e0997b346/anthropic-0.116.0-py3-none-any.whl", hash = "sha256:6c0a7698e8d652455da3499978279bb2588c7264d0a35be3666009a4258c8256", size = 956896, upload-time = "2026-07-02T19:08:08.756Z" },
+]
+
 [[package]]
 name = "antlr4-python3-runtime"
 version = "4.9.3"
@@ -1088,6 +1107,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/da/90/022c79d6e5e6f843268c10b84d4a021ee3afba0621d3c176d3ff2024bfc8/dlinfo-2.0.0-py3-none-any.whl", hash = "sha256:b32cc18e3ea67c0ca9ca409e5b41eed863bd1363dbc9dd3de90fedf11b61e7bc", size = 3654, upload-time = "2025-01-16T15:43:09.474Z" },
 ]
 
+[[package]]
+name = "docstring-parser"
+version = "0.18.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/e0/4d/f332313098c1de1b2d2ff91cf2674415cc7cddab2ca1b01ae29774bd5fdf/docstring_parser-0.18.0.tar.gz", hash = "sha256:292510982205c12b1248696f44959db3cdd1740237a968ea1e2e7a900eeb2015", size = 29341, upload-time = "2026-04-14T04:09:19.867Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/a7/5f/ed01f9a3cdffbd5a008556fc7b2a08ddb1cc6ace7effa7340604b1d16699/docstring_parser-0.18.0-py3-none-any.whl", hash = "sha256:b3fcbed555c47d8479be0796ef7e19c2670d428d72e96da63f3a40122860374b", size = 22484, upload-time = "2026-04-14T04:09:18.638Z" },
+]
+
 [[package]]
 name = "donfig"
 version = "0.8.1.post1"
@@ -2307,6 +2335,20 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/3f/e8/a3b8cb0005553f6a876865073c81ef93bd7c5b18381bcb9ba4013af96ebc/langchain-1.2.15-py3-none-any.whl", hash = "sha256:e349db349cb3e9550c4044077cf90a1717691756cc236438404b23500e615874", size = 112714, upload-time = "2026-04-03T14:26:02.557Z" },
 ]
 
+[[package]]
+name = "langchain-anthropic"
+version = "1.4.8"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "anthropic" },
+    { name = "langchain-core" },
+    { name = "pydantic" },
+]
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 version = "1.4.3"
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-version = "1.2.28"
+version = "1.4.9"
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 dependencies = [
     { name = "jsonpatch" },
+    { name = "langchain-protocol" },
     { name = "langsmith" },
     { name = "packaging" },
     { name = "pydantic" },
@@ -2359,9 +2402,9 @@ dependencies = [
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+[[package]]
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+version = "0.0.18"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
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+]
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+
 [[package]]
 name = "langfuse"
 version = "3.14.6"
@@ -4714,12 +4769,13 @@ requires-dist = [
 
 [[package]]
 name = "rai-core"
-version = "2.12.1"
+version = "2.13.0"
 source = { editable = "src/rai_core" }
 dependencies = [
     { name = "coloredlogs" },
     { name = "deprecated" },
     { name = "langchain" },
+    { name = "langchain-anthropic" },
     { name = "langchain-aws" },
     { name = "langchain-community" },
     { name = "langchain-core" },
@@ -4748,6 +4804,7 @@ requires-dist = [
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     { name = "langchain", specifier = ">=1.0.0,<2.0.0" },
+    { name = "langchain-anthropic" },
     { name = "langchain-aws" },
     { name = "langchain-community" },
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