Betelgeuse
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Headlines · 2
- Betelgeuse reaches 24 tok/s for Qwen 3.8 Flash Next on dual-channel RAM
In a self-published r/LocalLLaMA report, the Betelgeuse developer tested Qwen 3.8 Flash Next IQ4_XS on an RTX 3060 12GB with 16GB of system RAM. Betelgeuse reached 24.0 tok/s with dual-channel 2x8GB DDR4 and 14.0 tok/s with a single 16GB stick, while the developer reported byte-exact output and no dropped experts; stock llama.cpp and Strata were slower in the same tests.
r/LocalLLaMA · 🔥 6 - Betelgeuse Runs Qwen 3.8 Flash Next on Budget Hardware
Developer /u/zyxciss reported on r/LocalLLaMA that Betelgeuse, a llama.cpp fork, ran the 68GB Qwen 3.8 Flash Next MoE model on an RTX 3060 12GB with 16GB DDR4 RAM. The developer recorded 16.80 tokens per second cold, 22.03 warm, and bursts up to 48 tokens per second, while claiming byte-exact output without pruning any routed experts. Betelgeuse uses a VRAM expert-slot pool, a RAM victim cache, and io_uring paging to reduce storage reads.
r/LocalLLaMA · 🔥 5
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