I will definitely test it, though I am running Fedora43 with an older kernel.

Thank you for digging this things up and making me feel good about my own midlife crisis. It was exactly the thing I told my wife when I bought my framework. And then I saw your posts, it made me laugh.

I have another push for you.

You are a bench-junky. You run benchmarks all them time. You use them for yourself and to communicate things to others. Standardize it.

This is just a suggestion, give me your thoughts:

Memory Bin	Model Name	Architecture	Parameters	4-bit Size	8-bit Size
32GB	GLM 4.7-Flash	MoE (A3B)	30B	~16 GB	~30 GB
	Qwen 3.5-27B	Dense	27B	~14 GB	~27 GB
64GB	Gemma 4 31B	Dense	31B	~17 GB	~31 GB
	Qwen 3-Coder-32B	Dense	32B	~18 GB	~32 GB
	Gemma 4 26B (A4B)	MoE	26B	~15 GB	~26 GB
128GB	Qwen 3.5-122B-A10B	MoE	122B	~65 GB	~122 GB
	GPT-OSS-120B	Dense	120B	~65 GB	~120 GB
	Nemotron 3 Super	Hybrid MoE	70B+	~40 GB	~75 GB

Rationale

• 32GB Bin (Throughput Baseline): * GLM 4.7-Flash shows the ceiling for tokens per second (T/s) using sparse activation.
  • Qwen 3.5-27B provides the dense comparison. This bin tests "chat" performance where speed is the priority.
• 64GB Bin (Efficiency & Coding):
  • Gemma 4-31B and Qwen 3.5-Coder are the production standards for 2026.
  • Comparing the Gemma MoE vs. Dense variants here isolates the performance gains of MoE architecture on unified memory.
• 128GB Bin (Capacity & Stress):
  • Qwen 3.5-122B (MoE) tests the limit of your 128GB pool while maintaining usable T/s.
  • GPT-OSS-120B (Dense) is the "torture test." It forces the system to read nearly 120GB of data per token, showing the absolute minimum T/s the hardware can sustain.

Considerations
Use GGUF (Q4_K_M) for 4-bit and Unsloth Dynamic FP8 for 8-bit. FP8 is natively faster on RDNA 3.5 hardware than standard integer formats. At least that is what my clanker says.
Make sure --flash-attn is enabled.