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amd-strix-halo-toolboxes/benchmark/loadtime_results/Qwen3-235B-A22B-Instruct-2507-UD-Q3_K_XL-00001-of-00003__vulkan_radv.log
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Donato Capitella e7e27e6cf3 Benchmark and container updates
2025-08-03 13:05:52 +01:00

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ggml_vulkan: Found 1 Vulkan devices:
ggml_vulkan: 0 = Radeon 8060S Graphics (RADV GFX1151) (radv) | uma: 1 | fp16: 1 | bf16: 0 | warp size: 64 | shared memory: 65536 | int dot: 1 | matrix cores: KHR_coopmat
build: 6040 (66625a59) with cc (GCC) 15.1.1 20250719 (Red Hat 15.1.1-5) for x86_64-redhat-linux
main: llama backend init
main: load the model and apply lora adapter, if any
llama_model_load_from_file_impl: using device Vulkan0 (Radeon 8060S Graphics (RADV GFX1151)) - 87722 MiB free
llama_model_loader: additional 2 GGUFs metadata loaded.
llama_model_loader: loaded meta data with 48 key-value pairs and 1131 tensors from /home/kyuz0/models/qwen-3-235B-Q3_K-XL/UD-Q3_K_XL/Qwen3-235B-A22B-Instruct-2507-UD-Q3_K_XL-00001-of-00003.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = qwen3moe
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Qwen3-235B-A22B-Instruct-2507
llama_model_loader: - kv 3: general.version str = 2507
llama_model_loader: - kv 4: general.finetune str = Instruct
llama_model_loader: - kv 5: general.basename str = Qwen3-235B-A22B-Instruct-2507
llama_model_loader: - kv 6: general.quantized_by str = Unsloth
llama_model_loader: - kv 7: general.size_label str = 235B-A22B
llama_model_loader: - kv 8: general.license str = apache-2.0
llama_model_loader: - kv 9: general.license.link str = https://huggingface.co/Qwen/Qwen3-235...
llama_model_loader: - kv 10: general.repo_url str = https://huggingface.co/unsloth
llama_model_loader: - kv 11: general.base_model.count u32 = 1
llama_model_loader: - kv 12: general.base_model.0.name str = Qwen3 235B A22B Instruct 2507
llama_model_loader: - kv 13: general.base_model.0.version str = 2507
llama_model_loader: - kv 14: general.base_model.0.organization str = Qwen
llama_model_loader: - kv 15: general.base_model.0.repo_url str = https://huggingface.co/Qwen/Qwen3-235...
llama_model_loader: - kv 16: general.tags arr[str,2] = ["unsloth", "text-generation"]
llama_model_loader: - kv 17: qwen3moe.block_count u32 = 94
llama_model_loader: - kv 18: qwen3moe.context_length u32 = 262144
llama_model_loader: - kv 19: qwen3moe.embedding_length u32 = 4096
llama_model_loader: - kv 20: qwen3moe.feed_forward_length u32 = 12288
llama_model_loader: - kv 21: qwen3moe.attention.head_count u32 = 64
llama_model_loader: - kv 22: qwen3moe.attention.head_count_kv u32 = 4
llama_model_loader: - kv 23: qwen3moe.rope.freq_base f32 = 5000000.000000
llama_model_loader: - kv 24: qwen3moe.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 25: qwen3moe.expert_used_count u32 = 8
llama_model_loader: - kv 26: qwen3moe.attention.key_length u32 = 128
llama_model_loader: - kv 27: qwen3moe.attention.value_length u32 = 128
llama_model_loader: - kv 28: qwen3moe.expert_count u32 = 128
llama_model_loader: - kv 29: qwen3moe.expert_feed_forward_length u32 = 1536
llama_model_loader: - kv 30: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 31: tokenizer.ggml.pre str = qwen2
llama_model_loader: - kv 32: tokenizer.ggml.tokens arr[str,151936] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 33: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 34: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 35: tokenizer.ggml.eos_token_id u32 = 151645
llama_model_loader: - kv 36: tokenizer.ggml.padding_token_id u32 = 151654
llama_model_loader: - kv 37: tokenizer.ggml.add_bos_token bool = false
llama_model_loader: - kv 38: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>...
llama_model_loader: - kv 39: general.quantization_version u32 = 2
llama_model_loader: - kv 40: general.file_type u32 = 12
llama_model_loader: - kv 41: quantize.imatrix.file str = Qwen3-235B-A22B-Instruct-2507-GGUF/im...
llama_model_loader: - kv 42: quantize.imatrix.dataset str = unsloth_calibration_Qwen3-235B-A22B-I...
llama_model_loader: - kv 43: quantize.imatrix.entries_count u32 = 745
llama_model_loader: - kv 44: quantize.imatrix.chunks_count u32 = 693
llama_model_loader: - kv 45: split.no u16 = 0
llama_model_loader: - kv 46: split.tensors.count i32 = 1131
llama_model_loader: - kv 47: split.count u16 = 3
llama_model_loader: - type f32: 471 tensors
llama_model_loader: - type q3_K: 267 tensors
llama_model_loader: - type q4_K: 362 tensors
llama_model_loader: - type q5_K: 20 tensors
llama_model_loader: - type q6_K: 11 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q3_K - Medium
print_info: file size = 96.99 GiB (3.54 BPW)
load: special tokens cache size = 26
load: token to piece cache size = 0.9311 MB
print_info: arch = qwen3moe
print_info: vocab_only = 0
print_info: n_ctx_train = 262144
print_info: n_embd = 4096
print_info: n_layer = 94
print_info: n_head = 64
print_info: n_head_kv = 4
print_info: n_rot = 128
print_info: n_swa = 0
print_info: is_swa_any = 0
print_info: n_embd_head_k = 128
print_info: n_embd_head_v = 128
print_info: n_gqa = 16
print_info: n_embd_k_gqa = 512
print_info: n_embd_v_gqa = 512
print_info: f_norm_eps = 0.0e+00
print_info: f_norm_rms_eps = 1.0e-06
print_info: f_clamp_kqv = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale = 0.0e+00
print_info: f_attn_scale = 0.0e+00
print_info: n_ff = 12288
print_info: n_expert = 128
print_info: n_expert_used = 8
print_info: causal attn = 1
print_info: pooling type = 0
print_info: rope type = 2
print_info: rope scaling = linear
print_info: freq_base_train = 5000000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn = 262144
print_info: rope_finetuned = unknown
print_info: model type = 235B.A22B
print_info: model params = 235.09 B
print_info: general.name = Qwen3-235B-A22B-Instruct-2507
print_info: n_ff_exp = 1536
print_info: vocab type = BPE
print_info: n_vocab = 151936
print_info: n_merges = 151387
print_info: BOS token = 11 ','
print_info: EOS token = 151645 '<|im_end|>'
print_info: EOT token = 151645 '<|im_end|>'
print_info: PAD token = 151654 '<|vision_pad|>'
print_info: LF token = 198 'Ċ'
print_info: FIM PRE token = 151659 '<|fim_prefix|>'
print_info: FIM SUF token = 151661 '<|fim_suffix|>'
print_info: FIM MID token = 151660 '<|fim_middle|>'
print_info: FIM PAD token = 151662 '<|fim_pad|>'
print_info: FIM REP token = 151663 '<|repo_name|>'
print_info: FIM SEP token = 151664 '<|file_sep|>'
print_info: EOG token = 151643 '<|endoftext|>'
print_info: EOG token = 151645 '<|im_end|>'
print_info: EOG token = 151662 '<|fim_pad|>'
print_info: EOG token = 151663 '<|repo_name|>'
print_info: EOG token = 151664 '<|file_sep|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = false)
load_tensors: offloading 94 repeating layers to GPU
load_tensors: offloading output layer to GPU
load_tensors: offloaded 95/95 layers to GPU
load_tensors: Vulkan0 model buffer size = 98988.40 MiB
load_tensors: CPU model buffer size = 333.84 MiB
....................................................................................................
llama_context: constructing llama_context
llama_context: non-unified KV cache requires ggml_set_rows() - forcing unified KV cache
llama_context: n_seq_max = 1
llama_context: n_ctx = 4096
llama_context: n_ctx_per_seq = 4096
llama_context: n_batch = 2048
llama_context: n_ubatch = 512
llama_context: causal_attn = 1
llama_context: flash_attn = 1
llama_context: kv_unified = true
llama_context: freq_base = 5000000.0
llama_context: freq_scale = 1
llama_context: n_ctx_per_seq (4096) < n_ctx_train (262144) -- the full capacity of the model will not be utilized
llama_context: Vulkan_Host output buffer size = 0.58 MiB
llama_kv_cache_unified: Vulkan0 KV buffer size = 752.00 MiB
llama_kv_cache_unified: size = 752.00 MiB ( 4096 cells, 94 layers, 1/ 1 seqs), K (f16): 376.00 MiB, V (f16): 376.00 MiB
llama_kv_cache_unified: LLAMA_SET_ROWS=0, using old ggml_cpy() method for backwards compatibility
llama_context: Vulkan0 compute buffer size = 304.75 MiB
llama_context: Vulkan_Host compute buffer size = 16.01 MiB
llama_context: graph nodes = 6023
llama_context: graph splits = 2
common_init_from_params: added <|endoftext|> logit bias = -inf
common_init_from_params: added <|im_end|> logit bias = -inf
common_init_from_params: added <|fim_pad|> logit bias = -inf
common_init_from_params: added <|repo_name|> logit bias = -inf
common_init_from_params: added <|file_sep|> logit bias = -inf
common_init_from_params: setting dry_penalty_last_n to ctx_size = 4096
common_init_from_params: warming up the model with an empty run - please wait ... (--no-warmup to disable)
main: llama threadpool init, n_threads = 16
system_info: n_threads = 16 (n_threads_batch = 16) / 32 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | AVX2 = 1 | F16C = 1 | FMA = 1 | BMI2 = 1 | AVX512 = 1 | AVX512_VBMI = 1 | AVX512_VNNI = 1 | LLAMAFILE = 1 | OPENMP = 1 | REPACK = 1 |
sampler seed: 1959920459
sampler params:
repeat_last_n = 64, repeat_penalty = 1.000, frequency_penalty = 0.000, presence_penalty = 0.000
dry_multiplier = 0.000, dry_base = 1.750, dry_allowed_length = 2, dry_penalty_last_n = 4096
top_k = 40, top_p = 0.950, min_p = 0.050, xtc_probability = 0.000, xtc_threshold = 0.100, typical_p = 1.000, top_n_sigma = -1.000, temp = 0.800
mirostat = 0, mirostat_lr = 0.100, mirostat_ent = 5.000
sampler chain: logits -> logit-bias -> penalties -> dry -> top-n-sigma -> top-k -> typical -> top-p -> min-p -> xtc -> temp-ext -> dist
generate: n_ctx = 4096, n_batch = 2048, n_predict = 1, n_keep = 0
Hello,
llama_perf_sampler_print: sampling time = 0.08 ms / 2 runs ( 0.04 ms per token, 25641.03 tokens per second)
llama_perf_context_print: load time = 40114.24 ms
llama_perf_context_print: prompt eval time = 0.00 ms / 1 tokens ( 0.00 ms per token, inf tokens per second)
llama_perf_context_print: eval time = 67.08 ms / 1 runs ( 67.08 ms per token, 14.91 tokens per second)
llama_perf_context_print: total time = 86.46 ms / 2 tokens
llama_perf_context_print: graphs reused = 0
Elapsed #3: 40.621909942s
Run #3 status: 0
→ Avg over 3 runs: 40.722s
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