Running Minimax 2.7 at 100k Context on Strix Halo

The Reddit post details how to run the Minimax 2.7 model on a Strix Halo GPU with a 100,000 token context window. The author uses llama-server with the unsloth/MiniMax-M2.7-GGUF:UD-IQ3_XXS checkpoint and a long list of command‑line flags. Key flags include --no-context-shift to detect context exhaustion, --no-mmap to avoid memory mapping, and -np 2 with --kv-unified to share a single cache across two concurrent sessions. The configuration also sets --cache-ram 0 so the cache stays in VRAM, and uses -b 1024 -ub 1024 to speed up prefill. The author recommends increasing swap size and setting OOMScoreAdjust=500 in systemd to prevent the kernel OOM killer from terminating the process. The post explains that the model performs well at coding tasks but is less balanced than Qwen3.6 27b for non‑coding scenarios. Performance screenshots show the model handling 100k context without corruption. This configuration demonstrates that with careful flag tuning, Minimax can run at high context on modest hardware, offering a practical approach for developers needing large‑context inference.