Qwen3-Coder 30B-A3B-Instruct / b6060 Vulkan / FA off / PP512 TG128

Historical first-party llama-bench measurements by robustonian (display name 金のニワトリ), published August 2025, inspected October 13, 2026. Source's EVO-X2 section updated August 3, 2025. Exact measurement timestamp is not published. This report covers only Vulkan, Flash Attention off, on the EVO-X2. It does not combine the source's Mac Studio, CPU-only, RTX 3060 or RTX 3090 measurements. No local benchmark rerun. Hardware: EVO-X2 with AMD Ryzen AI Max+ 395, integrated Radeon 8060S / gfx1151, 128 GB unified installed memory. Source explicitly enumerates exactly one Vulkan GPU in this benchmark invocation and the native output binds backend Vulkan and ngl=100. This establishes one participating iGPU rather than inferring GPU quantity from one host or a model name. GPU core/CU count, physical CPU-core count, clock, TDP, thermal conditions and per-run memory usage are not measured in this log. 128 GB is installed unified RAM, not dedicated VRAM or resident model allocation. Native model size 16.45 GiB is the GGUF tensor/model footprint, not measured RAM use. Model: Qwen3-Coder-30B-A3B-Instruct, source-linked Unsloth GGUF artifact Qwen3-Coder-30B-A3B-Instruct-UD-Q4_K_XL.gguf. Preserve exact UD-Q4_K_XL identity; llama-bench's coarse model description is qwen3moe 30B.A3B Q4_K - Medium, 30.53 B total parameters. A3B is the family active-parameter label, not a measurement of activated weights. Current matching artifact metadata at HF revision b17cb02dd882d5b6ab62fc777ad2995f19668350: 17,665,334,432 bytes; LFS SHA256 2841aa314d916434860cfb8990347528dcdfe5c350dbcb9d1461dbee88ff2533. Current size is consistent with the source's rounded 16.45 GiB, but source did not publish a historical file hash or HF snapshot. This current reference is not claimed to be the tested historical bytes. No weights downloaded. Source-native rates, tokens/s (mean +/- printed deviation): headline pp512 391.54 +/- 1.50; separate tg128 72.99 +/- 0.31. Longer tests in the same backend/FA arm: pp8192 284.71 +/- 0.45; separate tg8192 46.60 +/- 1.34. These are separate native prefill and generation microbenchmarks, not an input prompt followed by a same-request answer, and tg8192 is not decode after a prefilled 8192-token prompt. Neither rate is derived from request time or TTFT. No TTFT is published or calculated. Native test labels identify executed fixed-count token work; these are synthetic benchmark token evaluations, not verified natural-language output tokens. Runtime: llama.cpp build 6060, displayed 9c35706b9, resolved to 9c35706b98ea271858acef4194f526a71b24cdc9, Vulkan/RPC compiled backends. Driver identifies AMD Radeon Graphics (RADV GFX1151) (radv), uma=1, fp16=1, bf16=0, warp size64, shared memory65536, int dot1, matrix cores KHR_coopmat. Exact Mesa/RADV driver revision is unreported. RPC is compiled in, but no RPC server is requested by the shown commands and pinned default is empty; it does not indicate remote participation. Source short command uses -ngl100 -fa0,1; long command adds -p8192 -n8192. The long command repeats the one-device log, but not the build line; matching revision for that table is source-section continuity rather than an independent second build receipt. Read-only audit of pinned tools/llama-bench/llama-bench.cpp: defaults are five repetitions, depth0, requested batch2048/microbatch512, F16 K/V cache, main GPU0, mmap on, warmup enabled; source does not override them. Source does not print the effective CPU thread count in these Vulkan rows; CPU-only rows elsewhere are not substituted. PP and TG are generated as separate parameter instances. Context request is n_prompt+n_gen+n_depth:512 for pp512,128 for tg128,8192 for either longer phase. Effective allocation can be rounded by runtime; no 640-token combined request or262K context claim. Model/context setup and warmup lie outside the measured windows; KV is cleared before each repeat. Prompt warmup uses the full prompt count; generation warmup uses one token. test_prompt feeds random vocabulary IDs and synchronizes after all prompt batches; test_gen performs and synchronizes one llama_decode per step for exactly128/8192 steps, without EOS sampling. get_time_ns uses std::chrono::high_resolution_clock; get_ts uses fixed token count / elapsed nanoseconds, then arithmetic mean and sample standard deviation across the five repetitions. No first-token arrival measurement, sampler-quality gate, uncertainty beyond reported spread, or application-level latency is established. Sources: https://zenn.dev/robustonian/scraps/445f2143217f75 https://huggingface.co/unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF/blob/b17cb02dd882d5b6ab62fc777ad2995f19668350/Qwen3-Coder-30B-A3B-Instruct-UD-Q4_K_XL.gguf https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct https://github.com/ggml-org/llama.cpp/blob/9c35706b98ea271858acef4194f526a71b24cdc9/tools/llama-bench/llama-bench.cpp https://github.com/ggml-org/llama.cpp/commit/9c35706b98ea271858acef4194f526a71b24cdc9 The form rounds the structured PP/TG rates to one decimal; the exact source values are retained above.