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Betelgeuse reaches 24 tok/s for Qwen 3.8 Flash Next on dual-channel RAM

AI summary

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.

In-depth insight

The controlled memory-channel comparison suggests that host RAM bandwidth is a meaningful constraint for this Betelgeuse inference setup, but the results are developer-reported and have not received independent output-parity verification.

In my last thread on Betelgeuse (bel-cli / bel-server), the main pushback in the comments was:

  • "Okay cool, 22 tok/s on IQ2_XS, but 2-bit is too low—what happens on an actual 4-bit quant like IQ4_XS where the experts are almost 2x larger?"
  • "Why were you testing on a single 16GB stick of DDR4 instead of normal dual-channel 2x 8GB?"

Fair questions. So I upgraded the oracle + victim-cache DMA path, packed IQ4_XS (~100GB+ class, full 4-bit experts), and tested it on the exact same RTX 3060 12GB under both RAM configs (still 16GB total system RAM in both tests):

  • Config A: 1x 16GB DDR4 (single-channel, ~19 GB/s host bandwidth)
  • Config B: 2x 8GB DDR4 (normal dual-channel 16GB gaming PC setup, ~38 GB/s host bandwidth)

Measured Results on IQ4_XS (RTX 3060 12GB + 16GB Total RAM)

Model / QuantRAM Config (16GB Total)Stock llama.cppStrata (--low-ram)Betelgeuse (bel-server)Output Parity vs. Stock
IQ4_XS (4-bit)1x 16GB (Single-Channel)~0.5 tok/s (thrash)~4–5 tok/s14.0 tok/s100% Byte-Exact
IQ4_XS (4-bit)2x 8GB (Dual-Channel)~0.6 tok/s (thrash)~5–6 tok/s24.0 tok/s100% Byte-Exact
IQ2_XS (GSQ-RCO)1x 16GB (Single-Channel)1.47 tok/s8.11 tok/s22.03 tok/s (48 tok/s bursts)100% Byte-Exact
Q8_K_XL (8-bit)1x 16GB (Single-Channel)OOM / <0.1 tok/sDoes not fit8.0 cold / 12.0 warm tok/s100% Byte-Exact

#Betelgeuse#Qwen 3.8 Flash Next#RTX 3060#llama.cpp#Strata

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