```Qwen3-4B-Thinking-2507-Q4_K_M.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 = qwen3 llama_model_loader: - kv 1: general.type str = model llama_model_loader: - kv 2: general.name str = Qwen3 4B Thinking 2507 llama_model_loader: - kv 3: general.version str = 2507 llama_model_loader: - kv 4: general.finetune str = Thinking llama_model_loader: - kv 5: general.basename str = Qwen3 llama_model_loader: - kv 6: general.size_label str = 4B llama_model_loader: - kv 7: general.license str = apache-2.0 llama_model_loader: - kv 8: general.license.link str = https://huggingface.co/Qwen/Qwen3-4B-... llama_model_loader: - kv 9: general.tags arr[str,1] = ["text-generation"] llama_model_loader: - kv 10: qwen3.block_count u32 = 36 llama_model_loader: - kv 11: qwen3.context_length u32 = 262144 llama_model_loader: - kv 12: qwen3.embedding_length u32 = 2560 llama_model_loader: - kv 13: qwen3.feed_forward_length u32 = 9728 llama_model_loader: - kv 14: qwen3.attention.head_count u32 = 32 llama_model_loader: - kv 15: qwen3.attention.head_count_kv u32 = 8 llama_model_loader: - kv 16: qwen3.rope.freq_base f32 = 5000000.000000 llama_model_loader: - kv 17: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001 llama_model_loader: - kv 18: qwen3.attention.key_length u32 = 128 llama_model_loader: - kv 19: qwen3.attention.value_length u32 = 128 llama_model_loader: - kv 20: tokenizer.ggml.model str = gpt2 llama_model_loader: - kv 21: tokenizer.ggml.pre str = qwen2 llama_model_loader: - kv 22: tokenizer.ggml.tokens arr[str,151936] = ["!", "\"", "#", "$", "%", "&", "'", ... llama_model_loader: - kv 23: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ... llama_model_loader: - kv 24: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",... llama_model_loader: - kv 25: tokenizer.ggml.eos_token_id u32 = 151645 llama_model_loader: - kv 26: tokenizer.ggml.padding_token_id u32 = 151643 llama_model_loader: - kv 27: tokenizer.ggml.bos_token_id u32 = 151643 llama_model_loader: - kv 28: tokenizer.ggml.add_bos_token bool = false llama_model_loader: - kv 29: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>... llama_model_loader: - kv 30: general.quantization_version u32 = 2 llama_model_loader: - kv 31: general.file_type u32 = 15 llama_model_loader: - type f32: 145 tensors llama_model_loader: - type q4_K: 216 tensors llama_model_loader: - type q6_K: 37 tensors print_info: file format = GGUF V3 (latest) print_info: file type = Q4_K - Medium print_info: file size = 2.32 GiB (4.95 BPW) load: printing all EOG tokens: load: - 151643 ('<|endoftext|>') load: - 151645 ('<|im_end|>') load: - 151662 ('<|fim_pad|>') load: - 151663 ('<|repo_name|>') load: - 151664 ('<|file_sep|>') load: special tokens cache size = 26 load: token to piece cache size = 0.9311 MB print_info: arch = qwen3 print_info: vocab_only = 0 print_info: n_ctx_train = 262144 print_info: n_embd = 2560 print_info: n_embd_inp = 2560 print_info: n_layer = 36 print_info: n_head = 32 print_info: n_head_kv = 8 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 = 4 print_info: n_embd_k_gqa = 1024 print_info: n_embd_v_gqa = 1024 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 = 9728 print_info: n_expert = 0 print_info: n_expert_used = 0 print_info: n_expert_groups = 0 print_info: n_group_used = 0 print_info: causal attn = 1 print_info: pooling type = -1 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 = 4B print_info: model params = 4.02 B print_info: general.name = Qwen3 4B Thinking 2507 print_info: vocab type = BPE print_info: n_vocab = 151936 print_info: n_merges = 151387 print_info: BOS token = 151643 '<|endoftext|>' print_info: EOS token = 151645 '<|im_end|>' print_info: EOT token = 151645 '<|im_end|>' print_info: PAD token = 151643 '<|endoftext|>' 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 = true) load_tensors: offloading 36 repeating layers to GPU load_tensors: offloading output layer to GPU load_tensors: offloaded 37/37 layers to GPU load_tensors: CPU_Mapped model buffer size = 304.28 MiB load_tensors: Metal_Mapped model buffer size = 2375.91 MiB ................................................................................ llama_context: constructing llama_context llama_context: n_seq_max = 4 llama_context: n_ctx = 10240 llama_context: n_ctx_seq = 10240 llama_context: n_batch = 2048 llama_context: n_ubatch = 512 llama_context: causal_attn = 1 llama_context: flash_attn = auto llama_context: kv_unified = true llama_context: freq_base = 5000000.0 llama_context: freq_scale = 1 llama_context: n_ctx_seq (10240) < n_ctx_train (262144) -- the full capacity of the model will not be utilized ggml_metal_init: allocating ggml_metal_init: found device: Apple M3 ggml_metal_init: picking default device: Apple M3 ggml_metal_init: use fusion = true ggml_metal_init: use concurrency = true ggml_metal_init: use graph optimize = true llama_context: CPU output buffer size = 2.32 MiB llama_kv_cache: Metal KV buffer size = 1440.00 MiB llama_kv_cache: size = 1440.00 MiB ( 10240 cells, 36 layers, 4/1 seqs), K (f16): 720.00 MiB, V (f16): 720.00 MiB llama_context: Flash Attention was auto, set to enabled llama_context: Metal compute buffer size = 301.75 MiB llama_context: CPU compute buffer size = 25.01 MiB```