DescriptionThis AI tool simplifies the process of running machine learning models locally, enabling developers to easily deploy and interact with various models without extensive setup. Its user-friendly interface streamlines the integration of AI into applications.
MLX safetensors ollama create no longer experimental. GGUF model creation now requires using llama.cpp tooling for safetensor conversion and quantization.
Improved MLX memory handling on Apple Silicon
Runaway repeat token detection now requires 100 repeat tokens for reduced false positives (e.g. OCR)
/api/tags is much faster on large model libraries (3.1 s → 294 ms cold in testing), and model capabilities are now reported consistently.
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Ollama models can now be used directly in ChatGPT Desktop, so you can keep your existing workflow while running open models.
This release also improves structured output performance on Apple Silicon, adds support for OpenAI-compatible client tool search and response compaction, and makes images work correctly through compacted responses.
Developers can now easily configure Claude Desktop to seamlessly work with Ollama as a third-party gateway provider.
Improved caching
Fixed a hang where agent clients that cancel long prefills
Prefill restore points are now trustworthy by construction: a cancelled prefill keeps every restore point it crossed, so retries resume where they stopped instead of restarting from scratch
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Use Ollama models in ChatGPT Desktop
Ollama models can now be used directly in ChatGPT Desktop, so you can keep your existing workflow while running open models. Setup is available from the Ollama app on MacOS.
This release also improves structured output performance on Apple Silicon, adds support for OpenAI-compatible client tool search and response compaction, and makes images work correctly through compacted responses.