The MLX library released version 0.32.1, introducing support for a head dimension of 72 within its Metal full attention implementation.
- The update enables the use of head dimension 72 in Metal full attention via pull request #4330.
The MLX library released version 0.32.1, introducing support for a head dimension of 72 within its Metal full attention implementation.
Apple has introduced a new architecture for its third-generation foundation models (AFM3) that utilizes "Instruction-Following Pruning" to significantly reduce active parameter count. The model is designed to activate approximately 20% of its MLP layers by making routing decisions once per prompt rather than per token.
Apple is currently in discussions with the startup PrismML regarding technology that compresses artificial intelligence models for deployment on iPhones.
The MLX library released version 0.32.0, which addresses a specific bug in the Metal backend.
Researchers present BaseRT, a native Metal inference runtime for large language models on Apple Silicon that achieves the highest reported inference throughput to date. By utilizing chip-specific kernel fusion and unified memory-aware optimization, it overcomes the overhead found in existing frameworks like llama.cpp and MLX.
Users can now convert and run EXL3 quantized models on Apple Silicon Macs with 64GB+ RAM. Tests show that models like MiniCPM5 and Qwen3.6-27B achieve performance on par with or slightly behind RTX-card-based conversions, with EXL3 offering superior quantization quality compared to MLX.
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