Based on advice from LocalLLama implemented a n+2 lookahead prediction for ssd streaming Qwen Flash Next - and it worked!
My project is optimising qwen flash next on Mac Mini m5 64gb through SSD streaming.
Proof1 community thread
Key points
- I recently asked LocalLLama for guidance on how to optimise token output.
- Today a popular method to do this is a lookahead guesser which fetches experts one layer ahead of the current layer.
- The way the various optimisations stack on top of each other this may actually net alot more on a base vanilla setup.
- Edit: Kudos to sdroege for og suggestion!
Sources (1)
- [1]Based on advice from LocalLLama implemented a n+2 lookahead prediction for ssd streaming Qwen Flash Next - and it worked!r/LocalLLaMA (top, daily) · Oct 13, 09:57 AM
My project is optimising qwen flash next on Mac Mini m5 64gb through SSD streaming.
I recently asked LocalLLama for guidance on how to optimise token output.
Extractive summary: sentences quoted from the sources.
Before this
- Oct 13, 2026SonicBoom: 52 tok/s decode on a laptop RTX 3050 (llama.cpp: 45) with the same quantized kernels, the difference is a graph compiler. No Python.
- Oct 13, 2026Hybrid Reasoning Agents
- Oct 12, 2026Qwen 3.8 Flash Next Q3 S - Benchmark creation
- Oct 12, 2026LSearch - Spotlight for windows with embedding
- Oct 12, 2026AReA: Adaptive Receptive-Field Attention for Efficient High-Resolution Diffusion Transformers
- Oct 11, 2026I ran Qwen 3.8 Flash-Next on my AMD 7900 XTX at 500k context. All local and what a shift it has been.
