kitio.aillama.cpp vs MLX
A side-by-side look at pricing plans, free tiers, features, pros and cons, updated for 2026. llama.cpp starts at Free and MLX starts at Free. Check both pricing pages for current plans.
At a glance
Best for
Category
Pricing model
Starting price
Free plan
Made by
Based in
Rating
Key features
- GGUF format
- Low-bit quantization
- Many GPU backends
- OpenAI-compatible server
- Built-in web UI
- Unified memory use
- NumPy-like API
- mlx-lm for LLMs
- LoRA fine-tuning
- Swift bindings
| Feature | llama.cpp | MLX |
|---|---|---|
| Best for | C/C++ engine for running LLMs efficiently on CPUs and GPUs | Apple's array framework for running and training models on Apple Silicon |
| Category | Models & APIs | Models & APIs |
| Pricing model | Free | Free |
| Starting price | Free | Free |
| Free plan | Yes, fully free | Yes, fully free |
| Made by | ggml-org | Apple |
| Based in | – | United States |
| Rating | No ratings yet | No ratings yet |
| Key features |
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Pricing compared
llama.cpp starts at Free and MLX starts at Free. Check both pricing pages for current plans.
Free plan
Cheapest paid plan
Top plan
Free trial
Prices in USD, checked Oct 28, 2026 or later. Plans change often, so confirm on each tool's site before you buy.
Pros and cons
llama.cpp
- Runs on modest hardware
- Very fast new-model support
- Foundation of many apps
- Command-line heavy
- Build options can confuse
- Less suited to high-concurrency serving
MLX
- Fast on Apple Silicon
- Runs big models on high-RAM Macs
- Simple Python API
- Mac only
- Smaller ecosystem than PyTorch
- Some models need conversion
Which one should you choose?
Choose llama.cpp if you want:
- Runs on modest hardware
- Very fast new-model support
- Foundation of many apps
Watch out: command-line heavy.
Choose MLX if you want:
- Fast on Apple Silicon
- Runs big models on high-RAM Macs
- Simple Python API
Watch out: mac only.
llama.cpp vs MLX FAQ
What is the difference between llama.cpp and MLX?
llama.cpp: C/C++ engine for running LLMs efficiently on CPUs and GPUs. MLX: Apple's array framework for running and training models on Apple Silicon. Both are models & apis tools.
Is llama.cpp or MLX cheaper?
llama.cpp starts at Free and MLX starts at Free. Check both pricing pages for current plans.
Do llama.cpp and MLX have free plans?
llama.cpp: Yes, fully free. MLX: Yes, fully free.
Who makes llama.cpp?
llama.cpp is made by ggml-org.
Who makes MLX?
MLX is made by Apple, based in United States.
Which should I choose, llama.cpp or MLX?
Choose llama.cpp if you value runs on modest hardware and very fast new-model support. Choose MLX if you value fast on apple silicon and runs big models on high-ram macs.