Meta's Muse Spark Open: full specs, Helion kernel speedups and benchmark tables
AIatMeta · reddit · 2026-10-16
Meta detailed Muse Spark Open on r/LocalLlama: 816B total / 42B active params, 1M context, natively multimodal (text/image/video/audio), aimed at coding and long-horizon agentic work, with extra safety post-training evaluated under Meta's Superintelligence Scaling Framework.
Inference & deployment
- Ships auto-tunable Helion GPU kernels in SGLang: 1.03–3.95× kernel speedups on NVIDIA/AMD GPUs, 3% E2E gain on MI350.
- Runs on SGLang, vLLM, TensorRT-LLM, HF Transformers, Apple MLX, llama.cpp, Unsloth across AMD/Apple/Intel/NVIDIA silicon.
- Optimized to run on two Apple M5 Ultra Mac Studios with MLX; fine-tuning via PyTorch/TorchTitan.
- API platforms: Baseten, Fireworks, Groq, Modal, Nebius, OpenRouter, Together AI; weights on SageMaker, Google Cloud Model Garden, HF, Microsoft Foundry under the Muse Model License (free for many commercial uses).
Benchmarks (vs GLM 5.3, Kimi K3, Qwen3.8): leads MCP-Atlas 89.2, HLE-Diamond 26.1, AA-Omniscience 25, ZeroBench 50.0, JobBench 61.8; trails Kimi K3 on Terminal-Bench 2.1 (76.4 vs 85.0) and DeepSWE (60 vs 68); GDPval-AA v2 1401 vs GLM 5.3's 1653.
Related event: Meta Open-Sources Muse Spark Open, an 816B-Parameter Frontier Model(45 posts)→
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