Expose Ollama models to LM Studio by symlinking its model files. Just run `python3 link-ollama-models-to-lm-studio.py`. On Windows, run it as admin.

link-ollama-models-to-lm-studio.py

#!/usr/bin/env python3
"""
Expose Ollama models to LM Studio by symlinking its model files.
NOTE: On Windows, you need to run this script with administrator privileges.
"""

import json
import os
from pathlib import Path


USER_HOME_DIR = Path(os.path.expanduser("~"))

# The path where Ollama stores its models.
OLLAMA_MODEL_DIR = Path(
    os.environ.get("OLLAMA_MODELS")
    or USER_HOME_DIR / ".ollama" / "models"
)

# The path where LM Studio stores its models.
LM_STUDIO_MODEL_DIR = USER_HOME_DIR / ".lmstudio" / "models"


def get_model_gguf_path(ollama_model_tag_manifest_path):
    """Parse Ollama's model tag manifest to extract its GGUF file path."""
    with open(ollama_model_tag_manifest_path) as mf:
        manifest = json.load(mf)

    model_layer = next(
        layer
        for layer in manifest["layers"]
        if layer["mediaType"] == "application/vnd.ollama.image.model"
    )
    gguf_hash = model_layer["digest"]
    gguf_filename = gguf_hash.replace(":", "-")
    gguf_path = OLLAMA_MODEL_DIR / "blobs" / gguf_filename

    return gguf_path


def main():
    ollama_library_path = OLLAMA_MODEL_DIR / "manifests" / "registry.ollama.ai" / "library"
    lmstudio_ollama_root_path = LM_STUDIO_MODEL_DIR / "ollama"

    print(f"Ensuring the target directory for LM Studio models exists: {lmstudio_ollama_root_path}")
    lmstudio_ollama_root_path.mkdir(parents=True, exist_ok=True)

    # Iterate through Ollama models.
    print(f"Scanning the Ollama model directory: {OLLAMA_MODEL_DIR}")
    for model_family_path in ollama_library_path.iterdir():
        # We're looking for subdirectories. Skip if it's a file.
        if not model_family_path.is_dir():
            continue

        model_family_name = model_family_path.name

        # Scan the model directory for tags.
        for model_tag_manifest_path in model_family_path.iterdir():
            if not model_tag_manifest_path.is_file():
                continue

            # If it's a tag manifest, extract the GGUF path.
            model_tag_name = model_tag_manifest_path.name
            try:
                gguf_path = get_model_gguf_path(model_tag_manifest_path)
                print(
                    f"Discovered Ollama model '{model_family_name}:{model_tag_name}' "
                    f"with GGUF at {gguf_path}"
                )
            except Exception:
                print(f"WARNING: Failed to parse the Ollama tag manifest at {model_tag_manifest_path}.")
                continue

            # Create a model in LM Studio, symlinking it to Ollama's GGUF file.
            lmstudio_model_dir_path = lmstudio_ollama_root_path / f"{model_family_name}-{model_tag_name}"
            print(f"Creating LM Studio model directory: {lmstudio_model_dir_path}")
            lmstudio_model_dir_path.mkdir(parents=True, exist_ok=True)

            symlink_path = lmstudio_model_dir_path / f"{model_family_name}-{model_tag_name}.gguf"
            if symlink_path.exists() and symlink_path.is_symlink():
                print(f"Skipping {model_family_name}:{model_tag_name}: already linked")
            else:
                print(f"Linking {model_family_name}:{model_tag_name} at {symlink_path}")
                os.symlink(gguf_path, symlink_path)


if __name__ == "__main__":
    main()

thanks it works

Please put "continue" in to the exception block at line 70

If Ollama has cloud model, exception is thrown and script trying to sym-linking the path but it can't and throws another exception and exits.

If you have different location to store lmstudio models (e.g., another hard drive with free space), you will have to move ~/.lmstudio/models/ollama folder manually to a new location.

Anyway, kudos to the author - it works nicely, and it helps a lot since gollama dropped the support for the functionality.