llamaperf
Oct 13, 2026
Throughput
13.2 t/s gen · 370.9 tokens/s prompt processing (prefill)Prompt processing measures input prefill speed; it does not tell you the time to first token.
Quant
Q4_K_M (GGUF)
KV cache
F16
Flash Attention
on
MTP (Multi-Token Prediction)
off
System RAM
128 GB

Summary

Source: https://github.com/hogeheer499-commits/strix-halo-guide/blob/f5d9e6dac1ec9aeeeeb1165ae85d305b33cee234/data/raw/2026-09-26/64gb-tier-30b-candidates-b11146/README.md Author: hogeheer499-commits. Historical measurement 2026-09-26, recovered 2026-10-13; source snapshot f5d9e6dac1ec9aeeeeb1165ae85d305b33cee234. Raw CSV and JSON, per-run commands and stderr retained. This is routine-load first-party benchmark evidence, not independent reproduction. Hardware: Beelink GTR9 Pro, AMD Ryzen AI Max+ 395 / Radeon 8060S, nominal 128GB unified RAM. Each of the four measured processes explicitly enumerates exactly one Vulkan device, Radeon 8060S; native rows say Vulkan. RPC library being loaded is not RPC participation. Native CPU threads16. Separate May1 hardware audit says16 physical cores/32 threads; these are historical same-host topology, not an active-core measurement in September. GPU CU count unknown. No dedicated VRAM or resident/peak model memory measurement. Runtime: official Ubuntu x64 Vulkan llama.cpp v0.5.0 release asset, executable reports0.5.0-dev build11146 commit7fe450e19, GNU11.4.0. Kernel7.0.0-31, Mesa/RADV26.2.3, AMD_VULKAN_ICD=RADV. All rows use ngl999, FA1, batch2048, ubatch512, F16 K/V, load/lazy auto, devices:auto, main_gpu0, layer split, no CPU MoE override. Host: balanced power, DPMauto, VM/desktop/browser/video-call/remote-access processes active; Ollama empty; preexisting swap nearly full. No strict-clean or causal cross-campaign comparison. Model: Muse Glimmer 30B, Q4_K_M; publisher meta-models; Muse-Glimmer-30B-KQuant-17GB-Q4_K_M.gguf. GGUF text file is dense with 27.85B-class parameters, despite marketed 30B name. Text-only; no mmproj, vision, DFlash or speculative decoding. Artifact: pinned HF 70bf1b61ac09f91b24d39038091b41c582bc5d7a; 16756683904 disk bytes; SHA256 4cc57c0f51040a226e5a72cc47b7613f7772950e460a665f7083de89f183f60e. Source's local hash and byte count match independently retrieved pinned HF metadata. Actual tested bytes remain author-attested; no weight download or independent rehash. Native model_size=16743567360 is tensor storage, not disk file size or residency. HF: https://huggingface.co/meta-models/Muse-Glimmer-30B-GGUF/blob/70bf1b61ac09f91b24d39038091b41c582bc5d7a/Muse-Glimmer-30B-KQuant-17GB-Q4_K_M.gguf Native rows (mean +/- sample SD; pass2 is a distinct repeated control, not pooled or best-of): - Pass 1 pp512, prepared depth 0, r10: 370.886965 +/- 1.316720 t/s; mean native duration 1380490185 ns. - Pass 1 tg128, prepared depth 0, r10: 13.239989 +/- 0.009645 t/s; mean native duration 9667686709 ns. - Pass 2 pp512, prepared depth 0, r10: 369.722541 +/- 0.872760 t/s; mean native duration 1384829181 ns. - Pass 2 tg128, prepared depth 0, r10: 13.241908 +/- 0.006578 t/s; mean native duration 9666282889 ns. - Pass 1 pp8192, prepared depth 0, r3: 346.515729 +/- 0.886785 t/s; mean native duration 23641165577 ns. - Pass 1 tg128, prepared depth 8192, r3: 13.014330 +/- 0.022881 t/s; mean native duration 9835332625 ns. The headline pair is pass1 PP512/TG128. Separate synthetic tests, not a512-input/128-output chat request. Exact commit's llama-bench timer inspected: load, context creation, warmup and depth preparation precede timing; PP processes random token batches and synchronizes; TG does128 single-token decode calls with synchronization. Numerator is n_prompt+n_gen, not useful natural-language output. The depth8192 TG test preloads/restores8192 tokens outside timing, then measures128 new decode steps. PP8192 starts at depth0. Requested n_ctx is512/128/8192/8320 per corresponding shape; effective allocated capacity is not logged and stays unknown. Native durations are not TTFT. Measured TTFT unknown; no reciprocal-rate or prompt/time proxy supplied. No server/client rate, concurrency, speculation or quality inference imported. Timer: https://github.com/ggml-org/llama.cpp/blob/7fe450e19/tools/llama-bench/llama-bench.cpp LlamaPerf numeric fields are rounded to the supported 0.1 tok/s step; exact source means and standard deviations are retained above.