Qwen 3.8
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Headlines · 2
- Local GPU server benchmarks 12 models from 4B to 35B parameters
A Reddit developer says they built a Linux server with two RTX 5060 Ti cards providing 32 GB of total VRAM, running vLLM in Docker. The developer reports testing 12 models from 4B to 35B parameters on complete datasets including IFEval, IFBench, ARC AGI 1, SimpleQA, SimpleQA Verified and SciCode, both with thinking enabled and disabled. The system also records wall-clock duration and token throughput to produce a time-efficiency score, although the methodology and results are self-reported.
r/LocalLLaMA · 🔥 0 - Apple MLX runs 816B Muse Spark Open locally on Mac Studio cluster
Apple Machine Learning Research published a post on October 15, 2026, detailing how the latest MLX release runs the nearly trillion-parameter Muse Spark Open (816B total, 42B active) locally on Mac Studio. It says a single Mac Studio offers up to 512GB of unified memory and can scale across multiple Macs using an RDMA over Thunderbolt driver; on a cluster of four M5 Ultra Mac Studios, the model generated over 36 tokens per second at an 8,192-token context. Apple also compared M5 Ultra with M3 Ultra and benchmarked Mistral Medium 3.5, Qwen 3.8, and pipeline and tensor parallelization schemes, claiming up to 4.6x the start-up time-to-first-token speed of the previous Mac Studio generation.
Apple Machine Learning Research · 🔥 0
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