List models available in the local LM Studio instance.

Queries /api/v0/models which returns every downloaded model with rich metadata: type (llm / vlm / embeddings), publisher, arch, quantization, state (loaded / not-loaded), and max_context_length.

Examples: list_models() list_models(type="llm") list_models(type="embeddings")

Get detailed info about a single model.

Examples: get_model(model_key="qwen/qwen3-4b-2507") get_model(model_key="text-embedding-nomic-embed-text-v1.5")

List models currently loaded into memory (ready for inference).

Examples: get_loaded_models()

Load a model into memory so it is ready for inference.

If context_length is omitted, the model's configured default is used. Only LLMs loaded via LM Studio's llama.cpp engine honor flash_attention, num_experts, eval_batch_size and offload_kv_cache_to_gpu.

Examples: load_model(model_key="qwen/qwen3-4b-2507") load_model(model_key="openai/gpt-oss-20b", context_length=16384, flash_attention=True)

Unload a model instance from memory, freeing RAM / VRAM.

The instance_id is the identifier returned by load_model (usually equal to the model key, but may differ when multiple instances of the same model are loaded). Use get_loaded_models to discover currently loaded instance_ids.

Examples: unload_model(instance_id="qwen/qwen3-4b-2507")

Send a chat completion request to a model (OpenAI-compatible /v1/chat/completions).

The model is auto-loaded if not already in memory (JIT loading enabled by default in LM Studio). Set stream=True only when the MCP client supports streamed responses; most do not.

Examples: chat(model="qwen/qwen3-4b-2507", messages=[{"role":"user","content":"Hello"}]) chat(model="qwen/qwen3-4b-2507", messages=[{"role":"system","content":"Be terse."},{"role":"user","content":"Hi"}], temperature=0.2, max_tokens=64)

Send a raw text-completion request to a model (OpenAI-compatible /v1/completions).

Prefer chat() for instruction-tuned conversational models. complete() is useful for base / completion models or for prompt-template experimentation.

Examples: complete(model="qwen/qwen3-4b-2507", prompt="The meaning of life is", max_tokens=20)

Generate an embedding vector for the given text (OpenAI-compatible /v1/embeddings).

input can be a single string or a list of strings for batch embedding.

Examples: embed(model="text-embedding-nomic-embed-text-v1.5", input="hello world") embed(model="text-embedding-nomic-embed-text-v1.5", input=["hello", "world"], normalize=True)

Escape hatch: send an arbitrary request to the LM Studio REST API.

Use this when you need an endpoint not covered by a dedicated tool (e.g. /api/v1/chat stateful chats, /api/v1/models/download, /v1/responses, the Anthropic-compatible /v1/messages, etc.). path must start with a slash and is appended to the configured base URL.

Examples: raw_request(method="GET", path="/api/v0/models") raw_request(method="POST", path="/api/v1/chat", json_body={"model":"qwen/qwen3-4b-2507","messages":[{"role":"user","content":"hi"}]})