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model: add Muse Spark Open (text, vision and audio) (#30616) model: add Muse Spark Open (text, vision and audio) Muse Spark Open is a latent space MoE: the residual stream stays at 8192 while the 256 experts live in 4096, with a projection down and up around them, top-8 sigmoid routing with a correction bias. Attention interleaves three sliding layers at a 2048 window with rope for one global layer without rope, with a sigmoid output gate and a weightless QK-norm. Residuals are norm preserving, their gate is folded at conversion time. Vision reuses the Muse Glimmer tower. Audio is a causal convolutional pyramid with no attention and no spectrogram, four stages folding 16, 6, 5 and 4 samples into the channel dim, one embedding per 80 ms of 24 kHz. The quantizer keeps the latent projections and the attention gate at Q8_0, a little over 1% of the weights, since the whole residual stream passes through them and the low-bit types turned the output into a repeating loop. The model saver writes the post norm epsilon, and the arch is registered in test-llama-archs. Co-authored-by: Xuan Son Nguyen son@huggingface.co Co-authored-by: Pedro Cuenca pedro@huggingface.co Muse Spark: drop the redundant forward expand Muse Spark: drop the redundant forward expand and tighten the comments Update src/llama-quant.cpp Co-authored-by: Sigbjørn Skjæret sigbjorn.skjaeret@huggingface.co Update src/llama-graph.cpp Co-authored-by: Sigbjørn Skjæret sigbjorn.skjaeret@huggingface.co Update conversion/muse_spark.py Co-authored-by: Sigbjørn Skjæret sigbjorn.skjaeret@huggingface.co Update conversion/muse_spark.py Co-authored-by: Sigbjørn Skjæret sigbjorn.skjaeret@huggingface.co Update conversion/muse_spark.py Co-authored-by: Sigbjørn Skjæret sigbjorn.skjaeret@huggingface.co Update conversion/muse_spark.py Co-authored-by: Sigbjørn Skjæret sigbjorn.skjaeret@huggingface.co Co-authored-by: Xuan Son Nguyen son@huggingface.co Co-authored-by: Pedro Cuenca pedro@huggingface.co Co-authored-by: Sigbjørn Skjæret sigbjorn.skjaeret@huggingface.co Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/56481361 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED macOS Intel (x64) iOS XCFramework Linux: Ubuntu x64 (CPU) Ubuntu arm64 (CPU) Ubuntu s390x (CPU) Ubuntu x64 (Vulkan) Ubuntu arm64 (Vulkan) Ubuntu x64 (CUDA 12) - CUDA 12.8 libraries Ubuntu x64 (CUDA 13) - CUDA 13.4 libraries Ubuntu arm64 (CUDA 13) - CUDA 13.4 libraries Ubuntu x64 (ROCm 10.0) Ubuntu x64 (OpenVINO) Ubuntu x64 (SYCL FP32) Ubuntu x64 (SYCL FP16) Linux arm64 (Snapdragon: CPU, Adreno GPU, Hexagon NPU) - setup guide Android: Android arm64 (CPU) Android arm64 (Snapdragon: CPU, Adreno GPU, Hexagon NPU) - setup guide Windows: Windows x64 (CPU) Windows arm64 (CPU) Windows arm64 (OpenCL Adreno) Windows x64 (CUDA 12) - CUDA 12.4 DLLs Windows x64 (CUDA 13) - CUDA 13.4 DLLs Windows arm64 (CUDA 13) - CUDA 13.4 DLLs Windows x64 (Vulkan) Windows arm64 (Vulkan) Windows x64 (OpenVINO) Windows x64 (SYCL) Windows x64 (ROCm 10.0) openEuler: DISABLED openEuler x86 (310p) openEuler x86 (910b, ACL Graph) openEuler aarch64 (310p) openEuler aarch64 (910b, ACL Graph) UI: UI

Source: llama.cpp Releases | 2026-10-16

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