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Kyle Hessling announces the upcoming release of the Qwopus-Coder-35B-A3B coding model, demonstrating its capability by using it with OpenCode to develop a fully functional real-time strategy game. The model achieves high speed and draft acceptance on a GeForce RTX 5090.
A new Japanese AI model achieves performance comparable to leading American frontier models, marking a significant advancement.
A setup using RTX 5080 and RTX 3090 GPUs achieves 80 tokens per second on the Qwen 3.6 27B Q8 model.
A performance test demonstrates the impact of Low, Automatic, and High power modes on LLM inference speed on an M5 Max MacBook, showing significant differences in token generation rates and power consumption.
Luce releases DFlash and PFlash support for AMD Strix Halo APUs, achieving 2.23x decode and 3.05x prefill speedups over llama.cpp HIP on Qwen3.6-27B.
The article asks for community evaluations of HIPfire's performance and quality on AMD Strix Halo hardware, specifically regarding long context support compared to llama.cpp.
A user demonstrates successful local inference of a 27B parameter Qwen model across three GTX 1080 Ti GPUs, achieving approximately 28-30 tokens per second using TurboQuant optimization.