GLM-5.2 UD-IQ1_M on llama.cpp — 5090 + 3090 Ti speed test (~ 579 t/s prefill @ 8k ctx, ~324 t/s prefill @ 57k ctx, ~10.6 t/s decode)

Just sharing some speed test numbers for GLM-5.2 running on llama.cpp.

Setup:

• Model: unsloth/GLM-5.2-GGUF, UD-IQ1_M quant
• GPUs: RTX 5090 + RTX 3090 Ti
• 186 GB DDR5 used
• Debian 13
• CUDA 13.3
• 128k context, q8_0 KV cache

Prefill (prompt processing):

Decode (generation):
Holds steady around 10.6 t/s through 580+ decoded tokens. 9.37 t/s on 60k context.

Start command:

llama-server \ -m GLM-5.2-UD-IQ1_M.gguf \ -fa 1 \ --fit off \ --tensor-split 100,0 \ --override-tensor "blk\.[0-3]\.(ffn_(up|down|gate)_exps\.weight)=CUDA0,blk\.([4-9]|10])\.(ffn_(up|down|gate)_exps\.weight)=CUDA1,blk\.11\.(ffn_down_exps\.weight)=CUDA1" \ --main-gpu 0 \ --n-cpu-moe 99 \ --no-mmap \ --mlock \ --cpu-range 0-23 \ --cpu-range-batch 0-23 \ --ctx-size 131072 \ --parallel 1 \ --jinja --no-warmup --threads 24 --numa isolate \ --batch-size 8192 --ubatch-size 8192 --threads-batch 24 \ -cms 24000 \ -ctxcp 5 \ --cache-type-k q8_0 --cache-type-v q8_0 \ --alias glm.5.2 \ --host 0.0.0.0 --port 8080