LM Studio can run both MLX and GGUF models but does so from an Ollama style (but more full-featured) macOS GUI. They also have a very actively maintained model catalog at https://lmstudio.ai/models
LM Studio can run both MLX and GGUF models but does so from an Ollama style (but more full-featured) macOS GUI. They also have a very actively maintained model catalog at https://lmstudio.ai/models
but people should use llama.cpp instead
I had no problems with ROCm 6.x but couldn't get it to run with ROCm 7.x. I switched to Vulkan and the performance seems ok for my use cases
MLX is a lot more performant than Ollama and llama.cpp on Apple Silicon, comparing both peak memory usage + tok/s output.
edit: LM Studio benefits from MLX optimizations when running MLX compatible models.
and why should that affect usage? it's not like ollama users fork the repo before installing it.
But vLLM and Sglang tend to be faster than both of those.
It's cross-platform (Win/Mac/Linux), detects the most appropriate GPU in your system and tells you whether the model you want to download will run within it's RAM footprint.
It lets you set up a local server that you can access through API calls as if you were remotely connected to an online service.
- Cross-platform
- Sets up a local API server
The tradeoff is a somewhat higher learning curve, since you need to manually browse the model library and choose the model/quantization that best fit your workflow and hardware. OTOH, it's also open-source unlike LMStudio which is proprietary.
[edit] Oh and apparently you can also directly run some models directly from HuggingFace: https://huggingface.co/docs/hub/ollama
If you've ever used a terminal, use llama.cpp. You can also directly run models from llama.cpp afaik.
I mean, what's the point of using local models if you can't trust the app itself?
and you think ollama doesn't do telemetry/etc. just because it's open source?