ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no ggml_cuda_init: found 1 ROCm devices: Device 0: AMD Radeon Graphics, gfx1151 (0x1151), VMM: no, Wave Size: 32 build: 6066 (4cb208c9) 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 ROCm0 (AMD Radeon Graphics) - 124523 MiB free llama_model_loader: additional 1 GGUFs metadata loaded. llama_model_loader: loaded meta data with 39 key-value pairs and 808 tensors from /home/kyuz0/models/gemma-3-27b-it-BF16/gemma-3-27b-it-BF16-00001-of-00002.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 = gemma3 llama_model_loader: - kv 1: general.type str = model llama_model_loader: - kv 2: general.name str = Gemma-3-27B-It llama_model_loader: - kv 3: general.finetune str = it llama_model_loader: - kv 4: general.basename str = Gemma-3-27B-It llama_model_loader: - kv 5: general.quantized_by str = Unsloth llama_model_loader: - kv 6: general.size_label str = 27B llama_model_loader: - kv 7: general.repo_url str = https://huggingface.co/unsloth llama_model_loader: - kv 8: gemma3.context_length u32 = 131072 llama_model_loader: - kv 9: gemma3.embedding_length u32 = 5376 llama_model_loader: - kv 10: gemma3.block_count u32 = 62 llama_model_loader: - kv 11: gemma3.feed_forward_length u32 = 21504 llama_model_loader: - kv 12: gemma3.attention.head_count u32 = 32 llama_model_loader: - kv 13: gemma3.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 14: gemma3.attention.key_length u32 = 128 llama_model_loader: - kv 15: gemma3.attention.value_length u32 = 128 llama_model_loader: - kv 16: general.file_type u32 = 32 llama_model_loader: - kv 17: gemma3.rope.freq_base f32 = 1000000.000000 llama_model_loader: - kv 18: gemma3.attention.sliding_window u32 = 1024 llama_model_loader: - kv 19: gemma3.attention.head_count_kv u32 = 16 llama_model_loader: - kv 20: gemma3.rope.scaling.type str = linear llama_model_loader: - kv 21: gemma3.rope.scaling.factor f32 = 8.000000 llama_model_loader: - kv 22: general.quantization_version u32 = 2 llama_model_loader: - kv 23: tokenizer.ggml.model str = llama llama_model_loader: - kv 24: tokenizer.ggml.pre str = default llama_model_loader: - kv 25: tokenizer.ggml.tokens arr[str,262208] = ["", "", "", "", ... llama_model_loader: - kv 26: tokenizer.ggml.scores arr[f32,262208] = [-1000.000000, -1000.000000, -1000.00... llama_model_loader: - kv 27: tokenizer.ggml.token_type arr[i32,262208] = [3, 3, 3, 3, 3, 4, 3, 3, 3, 3, 3, 3, ... llama_model_loader: - kv 28: tokenizer.ggml.bos_token_id u32 = 2 llama_model_loader: - kv 29: tokenizer.ggml.eos_token_id u32 = 106 llama_model_loader: - kv 30: tokenizer.ggml.unknown_token_id u32 = 3 llama_model_loader: - kv 31: tokenizer.ggml.padding_token_id u32 = 0 llama_model_loader: - kv 32: tokenizer.ggml.add_bos_token bool = true llama_model_loader: - kv 33: tokenizer.ggml.add_eos_token bool = false llama_model_loader: - kv 34: tokenizer.chat_template str = {{ bos_token }}\n{%- if messages[0]['r... llama_model_loader: - kv 35: tokenizer.ggml.add_space_prefix bool = false llama_model_loader: - kv 36: split.no u16 = 0 llama_model_loader: - kv 37: split.count u16 = 2 llama_model_loader: - kv 38: split.tensors.count i32 = 808 llama_model_loader: - type f32: 373 tensors llama_model_loader: - type bf16: 435 tensors print_info: file format = GGUF V3 (latest) print_info: file type = BF16 print_info: file size = 50.31 GiB (16.00 BPW) load: special tokens cache size = 6415 load: token to piece cache size = 1.9446 MB print_info: arch = gemma3 print_info: vocab_only = 0 print_info: n_ctx_train = 131072 print_info: n_embd = 5376 print_info: n_layer = 62 print_info: n_head = 32 print_info: n_head_kv = 16 print_info: n_rot = 128 print_info: n_swa = 1024 print_info: is_swa_any = 1 print_info: n_embd_head_k = 128 print_info: n_embd_head_v = 128 print_info: n_gqa = 2 print_info: n_embd_k_gqa = 2048 print_info: n_embd_v_gqa = 2048 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 = 7.7e-02 print_info: n_ff = 21504 print_info: n_expert = 0 print_info: n_expert_used = 0 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 = 1000000.0 print_info: freq_scale_train = 0.125 print_info: n_ctx_orig_yarn = 131072 print_info: rope_finetuned = unknown print_info: model type = 27B print_info: model params = 27.01 B print_info: general.name = Gemma-3-27B-It print_info: vocab type = SPM print_info: n_vocab = 262208 print_info: n_merges = 0 print_info: BOS token = 2 '' print_info: EOS token = 106 '' print_info: EOT token = 106 '' print_info: UNK token = 3 '' print_info: PAD token = 0 '' print_info: LF token = 248 '<0x0A>' print_info: EOG token = 106 '' print_info: max token length = 48 load_tensors: loading model tensors, this can take a while... (mmap = false) load_tensors: offloading 62 repeating layers to GPU load_tensors: offloading output layer to GPU load_tensors: offloaded 63/63 layers to GPU load_tensors: ROCm0 model buffer size = 51518.82 MiB load_tensors: ROCm_Host model buffer size = 2688.66 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 = 1000000.0 llama_context: freq_scale = 0.125 llama_context: n_ctx_per_seq (4096) < n_ctx_train (131072) -- the full capacity of the model will not be utilized llama_context: ROCm_Host output buffer size = 1.00 MiB llama_kv_cache_unified_iswa: creating non-SWA KV cache, size = 4096 cells llama_kv_cache_unified: ROCm0 KV buffer size = 320.00 MiB llama_kv_cache_unified: size = 320.00 MiB ( 4096 cells, 10 layers, 1/ 1 seqs), K (f16): 160.00 MiB, V (f16): 160.00 MiB llama_kv_cache_unified: LLAMA_SET_ROWS=0, using old ggml_cpy() method for backwards compatibility llama_kv_cache_unified_iswa: creating SWA KV cache, size = 1536 cells llama_kv_cache_unified: ROCm0 KV buffer size = 624.00 MiB llama_kv_cache_unified: size = 624.00 MiB ( 1536 cells, 52 layers, 1/ 1 seqs), K (f16): 312.00 MiB, V (f16): 312.00 MiB llama_kv_cache_unified: LLAMA_SET_ROWS=0, using old ggml_cpy() method for backwards compatibility llama_context: ROCm0 compute buffer size = 522.62 MiB llama_context: ROCm_Host compute buffer size = 11.01 MiB llama_context: graph nodes = 2613 llama_context: graph splits = 1 common_init_from_params: KV cache shifting is not supported for this context, disabling KV cache shifting common_init_from_params: added 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 | ROCm : NO_VMM = 1 | PEER_MAX_BATCH_SIZE = 128 | 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: 1422263455 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 = 1 Hello, llama_perf_sampler_print: sampling time = 0.09 ms / 3 runs ( 0.03 ms per token, 35294.12 tokens per second) llama_perf_context_print: load time = 9620.16 ms llama_perf_context_print: prompt eval time = 256.55 ms / 2 tokens ( 128.27 ms per token, 7.80 tokens per second) llama_perf_context_print: eval time = 0.00 ms / 1 runs ( 0.00 ms per token, inf tokens per second) llama_perf_context_print: total time = 261.63 ms / 3 tokens llama_perf_context_print: graphs reused = 0 Elapsed #3: 10.587027979s Run #3 status: 0 → Avg over 3 runs: 10.417s