ggml_cuda_init: found 1 CUDA devices (Total VRAM: 12287 MiB):
  Device 0: NVIDIA GeForce RTX 3060, compute capability 8.6, VMM: yes, VRAM: 12287 MiB
load_backend: loaded CUDA backend from C:\djl\bin\ggml-cuda.dll
load_backend: loaded RPC backend from C:\djl\bin\ggml-rpc.dll
load_backend: loaded CPU backend from C:\djl\bin\ggml-cpu-haswell.dll
build_info: b8766-547765a93
system_info: n_threads = 4 (n_threads_batch = 4) / 8 | CUDA : ARCHS = 750,800,860,890,1200,1210 | USE_GRAPHS = 1 | PEER_MAX_BATCH_SIZE = 128 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | AVX2 = 1 | F16C = 1 | FMA = 1 | BMI2 = 1 | LLAMAFILE = 1 | OPENMP = 1 | REPACK = 1 |
Running without SSL
init: using 7 threads for HTTP server
start: binding port with default address family
main: loading model
srv    load_model: loading model 'models\gemma-4-E4B-it.-UDQ8_K_XL.gguf'
common_init_result: fitting params to device memory, for bugs during this step try to reproduce them with -fit off, or provide --verbose logs if the bug only occurs with -fit on
llama_params_fit_impl: projected to use 6290 MiB of device memory vs. 11245 MiB of free device memory
llama_params_fit_impl: will leave 4954 >= 1024 MiB of free device memory, no changes needed
llama_params_fit: successfully fit params to free device memory
llama_params_fit: fitting params to free memory took 1.00 seconds
llama_model_load_from_file_impl: using device CUDA0 (NVIDIA GeForce RTX 3060) (0000:01:00.0) - 11245 MiB free
llama_model_loader: loaded meta data with 52 key-value pairs and 720 tensors from models\gemma-4-E4B-it.-UDQ8_K_XL.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              = gemma4
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                     general.sampling.top_k i32              = 64
llama_model_loader: - kv   3:                     general.sampling.top_p f32              = 0.950000
llama_model_loader: - kv   4:                      general.sampling.temp f32              = 1.000000
llama_model_loader: - kv   5:                               general.name str              = Gemma-4-E4B-It
llama_model_loader: - kv   6:                           general.basename str              = Gemma-4-E4B-It
llama_model_loader: - kv   7:                       general.quantized_by str              = Unsloth
llama_model_loader: - kv   8:                         general.size_label str              = 7.5B
llama_model_loader: - kv   9:                            general.license str              = apache-2.0
llama_model_loader: - kv  10:                       general.license.link str              = https://ai.google.dev/gemma/docs/gemm...
llama_model_loader: - kv  11:                           general.repo_url str              = https://huggingface.co/unsloth
llama_model_loader: - kv  12:                               general.tags arr[str,1]       = ["any-to-any"]
llama_model_loader: - kv  13:                         gemma4.block_count u32              = 42
llama_model_loader: - kv  14:                      gemma4.context_length u32              = 131072
llama_model_loader: - kv  15:                    gemma4.embedding_length u32              = 2560
llama_model_loader: - kv  16:                 gemma4.feed_forward_length u32              = 10240
llama_model_loader: - kv  17:                gemma4.attention.head_count u32              = 8
llama_model_loader: - kv  18:             gemma4.attention.head_count_kv u32              = 2
llama_model_loader: - kv  19:                      gemma4.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv  20:                  gemma4.rope.freq_base_swa f32              = 10000.000000
llama_model_loader: - kv  21:    gemma4.attention.layer_norm_rms_epsilon f32              = 0.000001
llama_model_loader: - kv  22:                gemma4.attention.key_length u32              = 512
llama_model_loader: - kv  23:              gemma4.attention.value_length u32              = 512
llama_model_loader: - kv  24:             gemma4.final_logit_softcapping f32              = 30.000000
llama_model_loader: - kv  25:            gemma4.attention.sliding_window u32              = 512
llama_model_loader: - kv  26:          gemma4.attention.shared_kv_layers u32              = 18
llama_model_loader: - kv  27:    gemma4.embedding_length_per_layer_input u32              = 256
llama_model_loader: - kv  28:    gemma4.attention.sliding_window_pattern arr[bool,42]     = [true, true, true, true, true, false,...
llama_model_loader: - kv  29:            gemma4.attention.key_length_swa u32              = 256
llama_model_loader: - kv  30:          gemma4.attention.value_length_swa u32              = 256
llama_model_loader: - kv  31:                gemma4.rope.dimension_count u32              = 512
llama_model_loader: - kv  32:            gemma4.rope.dimension_count_swa u32              = 256
llama_model_loader: - kv  33:                       tokenizer.ggml.model str              = gemma4
llama_model_loader: - kv  34:                      tokenizer.ggml.tokens arr[str,262144]  = ["<pad>", "<eos>", "<bos>", "<unk>", ...
llama_model_loader: - kv  35:                      tokenizer.ggml.scores arr[f32,262144]  = [-1000.000000, -1000.000000, -1000.00...
llama_model_loader: - kv  36:                  tokenizer.ggml.token_type arr[i32,262144]  = [3, 1, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  37:                      tokenizer.ggml.merges arr[str,514906]  = ["\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n", ...
llama_model_loader: - kv  38:                tokenizer.ggml.bos_token_id u32              = 2
llama_model_loader: - kv  39:                tokenizer.ggml.eos_token_id u32              = 106
llama_model_loader: - kv  40:            tokenizer.ggml.unknown_token_id u32              = 3
llama_model_loader: - kv  41:            tokenizer.ggml.padding_token_id u32              = 0
llama_model_loader: - kv  42:               tokenizer.ggml.mask_token_id u32              = 4
llama_model_loader: - kv  43:                    tokenizer.chat_template str              = {%- macro format_parameters(propertie...
llama_model_loader: - kv  44:            tokenizer.ggml.add_space_prefix bool             = false
llama_model_loader: - kv  45:               tokenizer.ggml.add_bos_token bool             = false
llama_model_loader: - kv  46:               general.quantization_version u32              = 2
llama_model_loader: - kv  47:                          general.file_type u32              = 7
llama_model_loader: - kv  48:                      quantize.imatrix.file str              = gemma-4-E4B-it-GGUF/imatrix_unsloth.gguf
llama_model_loader: - kv  49:                   quantize.imatrix.dataset str              = unsloth_calibration_gemma-4-E4B-it.txt
llama_model_loader: - kv  50:             quantize.imatrix.entries_count u32              = 342
llama_model_loader: - kv  51:              quantize.imatrix.chunks_count u32              = 142
llama_model_loader: - type  f32:  423 tensors
llama_model_loader: - type  f16:   67 tensors
llama_model_loader: - type q8_0:  229 tensors
llama_model_loader: - type bf16:    1 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q8_0
print_info: file size   = 8.05 GiB (9.20 BPW)
load: override 'tokenizer.ggml.add_bos_token' to 'true' for Gemma4
load: 0 unused tokens
load: control-looking token:      1 '<eos>' was not control-type; this is probably a bug in the model. its type will be overridden
load: control-looking token:     50 '<|tool_response>' was not control-type; this is probably a bug in the model. its type will be overridden
load: control-looking token:    212 '</s>' was not control-type; this is probably a bug in the model. its type will be overridden
load: printing all EOG tokens:
load:   - 1 ('<eos>')
load:   - 50 ('<|tool_response>')
load:   - 106 ('<turn|>')
load:   - 212 ('</s>')
load: special_eog_ids contains '<|tool_response>', removing '</s>' token from EOG list
load: special tokens cache size = 24
load: token to piece cache size = 1.9445 MB
print_info: arch                  = gemma4
print_info: vocab_only            = 0
print_info: no_alloc              = 0
print_info: n_ctx_train           = 131072
print_info: n_embd                = 2560
print_info: n_embd_inp            = 2560
print_info: n_layer               = 42
print_info: n_head                = 8
print_info: n_head_kv             = 2
print_info: n_rot                 = 512
print_info: n_swa                 = 512
print_info: is_swa_any            = 1
print_info: n_embd_head_k         = 512
print_info: n_embd_head_v         = 512
print_info: n_gqa                 = 4
print_info: n_embd_k_gqa          = [512, 512, 512, 512, 512, 1024, 512, 512, 512, 512, 512, 1024, 512, 512, 512, 512, 512, 1024, 512, 512, 512, 512, 512, 1024, 512, 512, 512, 512, 512, 1024, 512, 512, 512, 512, 512, 1024, 512, 512, 512, 512, 512, 1024]
print_info: n_embd_v_gqa          = [512, 512, 512, 512, 512, 1024, 512, 512, 512, 512, 512, 1024, 512, 512, 512, 512, 512, 1024, 512, 512, 512, 512, 512, 1024, 512, 512, 512, 512, 512, 1024, 512, 512, 512, 512, 512, 1024, 512, 512, 512, 512, 512, 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          = 1.0e+00
print_info: n_ff                  = 10240
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       = 1000000.0
print_info: freq_scale_train      = 1
print_info: freq_base_swa         = 10000.0
print_info: freq_scale_swa        = 1
print_info: n_embd_head_k_swa     = 256
print_info: n_embd_head_v_swa     = 256
print_info: n_rot_swa             = 256
print_info: n_ctx_orig_yarn       = 131072
print_info: rope_yarn_log_mul     = 0.0000
print_info: rope_finetuned        = unknown
print_info: model type            = E4B
print_info: model params          = 7.52 B
print_info: general.name          = Gemma-4-E4B-It
print_info: vocab type            = BPE
print_info: n_vocab               = 262144
print_info: n_merges              = 514906
print_info: BOS token             = 2 '<bos>'
print_info: EOS token             = 106 '<turn|>'
print_info: UNK token             = 3 '<unk>'
print_info: PAD token             = 0 '<pad>'
print_info: MASK token            = 4 '<mask>'
print_info: LF token              = 107 '
'
print_info: EOG token             = 1 '<eos>'
print_info: EOG token             = 50 '<|tool_response>'
print_info: EOG token             = 106 '<turn|>'
print_info: max token length      = 93
load_tensors: loading model tensors, this can take a while... (mmap = false, direct_io = false)
load_tensors: offloading output layer to GPU
load_tensors: offloading 41 repeating layers to GPU
load_tensors: offloaded 43/43 layers to GPU
load_tensors:        CUDA0 model buffer size =  5386.46 MiB
load_tensors:    CUDA_Host model buffer size =  3536.00 MiB
srv  log_server_r: done request: GET / 127.0.0.1 503
srv  log_server_r: done request: GET /favicon.ico 127.0.0.1 503
..............srv  log_server_r: done request: GET / 127.0.0.1 503
.srv  log_server_r: done request: GET /favicon.ico 127.0.0.1 503
...............srv  log_server_r: done request: GET / 127.0.0.1 503
srv  log_server_r: done request: GET /favicon.ico 127.0.0.1 503
..............srv  log_server_r: done request: GET / 127.0.0.1 503
.srv  log_server_r: done request: GET /favicon.ico 127.0.0.1 503
.........srv  log_server_r: done request: GET / 127.0.0.1 503
srv  log_server_r: done request: GET /favicon.ico 127.0.0.1 503
.srv  log_server_r: done request: GET / 127.0.0.1 503
srv  log_server_r: done request: GET /favicon.ico 127.0.0.1 503
srv  log_server_r: done request: GET / 127.0.0.1 503
srv  log_server_r: done request: GET /favicon.ico 127.0.0.1 503
.
common_init_result: added <eos> logit bias = -inf
common_init_result: added <|tool_response> logit bias = -inf
common_init_result: added <turn|> logit bias = -inf
llama_context: constructing llama_context
llama_context: n_seq_max     = 1
llama_context: n_ctx         = 32768
llama_context: n_ctx_seq     = 32768
llama_context: n_batch       = 2048
llama_context: n_ubatch      = 512
llama_context: causal_attn   = 1
llama_context: flash_attn    = enabled
llama_context: kv_unified    = false
llama_context: freq_base     = 1000000.0
llama_context: freq_scale    = 1
llama_context: n_ctx_seq (32768) < n_ctx_train (131072) -- the full capacity of the model will not be utilized
�[0mllama_context:  CUDA_Host  output buffer size =     1.00 MiB
llama_kv_cache_iswa: creating non-SWA KV cache, size = 32768 cells
llama_kv_cache:      CUDA0 KV buffer size =   272.00 MiB
llama_kv_cache: size =  272.00 MiB ( 32768 cells,   4 layers,  1/1 seqs), K (q8_0):  136.00 MiB, V (q8_0):  136.00 MiB
llama_kv_cache: attn_rot_k = 1, n_embd_head_k_all = 512
llama_kv_cache: attn_rot_v = 1, n_embd_head_k_all = 512
llama_kv_cache_iswa: creating     SWA KV cache, size = 1024 cells
llama_kv_cache:      CUDA0 KV buffer size =    21.25 MiB
llama_kv_cache: size =   21.25 MiB (  1024 cells,  20 layers,  1/1 seqs), K (q8_0):   10.62 MiB, V (q8_0):   10.62 MiB
llama_kv_cache: attn_rot_k = 1, n_embd_head_k_all = 256
llama_kv_cache: attn_rot_v = 1, n_embd_head_k_all = 256
sched_reserve: reserving ...
sched_reserve: resolving fused Gated Delta Net support:
sched_reserve: fused Gated Delta Net (autoregressive) enabled
sched_reserve: fused Gated Delta Net (chunked) enabled
sched_reserve:      CUDA0 compute buffer size =   610.30 MiB
sched_reserve:  CUDA_Host compute buffer size =    98.30 MiB
sched_reserve: graph nodes  = 2263
sched_reserve: graph splits = 2
sched_reserve: reserve took 23.93 ms, sched copies = 1
common_init_from_params: warming up the model with an empty run - please wait ... (--no-warmup to disable)
�[0mclip_model_loader: model name:   Gemma-4-E4B-It
clip_model_loader: description:
clip_model_loader: GGUF version: 3
clip_model_loader: alignment:    32
clip_model_loader: n_tensors:    1411
clip_model_loader: n_kv:         40

clip_model_loader: has vision encoder
clip_model_loader: has audio encoder
clip_ctx: CLIP using CUDA0 backend
load_hparams: projector:          gemma4v
load_hparams: n_embd:             768
load_hparams: n_head:             12
load_hparams: n_ff:               3072
load_hparams: n_layer:            16
load_hparams: ffn_op:             gelu_quick
load_hparams: projection_dim:     2560

--- vision hparams ---
load_hparams: image_size:         224
load_hparams: patch_size:         16
load_hparams: has_llava_proj:     0
load_hparams: minicpmv_version:   0
load_hparams: n_merge:            3
load_hparams: n_wa_pattern: 0
load_hparams: image_min_pixels:   580608
load_hparams: image_max_pixels:   645120

load_hparams: model size:         945.51 MiB
load_hparams: metadata size:      0.50 MiB
srv  log_server_r: done request: GET / 127.0.0.1 503
srv  log_server_r: done request: GET /favicon.ico 127.0.0.1 503
warmup: warmup with image size = 768 x 768
alloc_compute_meta:      CUDA0 compute buffer size =    94.52 MiB
alloc_compute_meta:        CPU compute buffer size =     6.77 MiB
alloc_compute_meta: graph splits = 1, nodes = 940
warmup: flash attention is enabled
clip_ctx: CLIP using CUDA0 backend
load_hparams: projector:          gemma4a
load_hparams: n_embd:             1024
load_hparams: n_head:             8
load_hparams: n_ff:               4096
load_hparams: n_layer:            12
load_hparams: ffn_op:             gelu_quick
load_hparams: projection_dim:     2560

--- audio hparams ---
load_hparams: n_mel_bins:         128
load_hparams: proj_stack_factor:  0
load_hparams: audio_chunk_len:    0
load_hparams: audio_sample_rate:  16000
load_hparams: audio_n_fft:        512
load_hparams: audio_window_len:   320
load_hparams: audio_hop_len:      160

load_hparams: model size:         945.51 MiB
load_hparams: metadata size:      0.50 MiB
srv  log_server_r: done request: GET / 127.0.0.1 503
srv  log_server_r: done request: GET /favicon.ico 127.0.0.1 503
warmup: warmup with audio size = 3000
alloc_compute_meta:      CUDA0 compute buffer size =   153.93 MiB
alloc_compute_meta:        CPU compute buffer size =     1.58 MiB
alloc_compute_meta: graph splits = 1, nodes = 1448
warmup: flash attention is enabled
init_audio: audio input is in experimental stage and may have reduced quality:
    https://github.com/ggml-org/llama.cpp/discussions/13759
�[0msrv    load_model: loaded multimodal model, 'models\gemma-4-E4B-it.mmproj-BF16.gguf'
srv    load_model: initializing slots, n_slots = 1
no implementations specified for speculative decoding
�[0mslot   load_model: id  0 | task -1 | speculative decoding context not initialized
slot   load_model: id  0 | task -1 | new slot, n_ctx = 32768
srv    load_model: prompt cache is enabled, size limit: 8192 MiB
�[0msrv    load_model: use `--cache-ram 0` to disable the prompt cache
�[0msrv    load_model: for more info see https://github.com/ggml-org/llama.cpp/pull/16391
�[0msrv          init: init: --clear-idle requires --kv-unified, disabling
�[0mcommon_chat_try_specialized_template: detected an outdated gemma4 chat template, applying compatibility workarounds. Consider updating to the official template.
�[0minit: chat template, example_format: '<|turn>system
<|think|>You are a helpful assistant<turn|>
<|turn>user
Hello<turn|>
<|turn>model
Hi there<turn|>
<|turn>user
How are you?<turn|>
<|turn>model
'
common_chat_try_specialized_template: detected an outdated gemma4 chat template, applying compatibility workarounds. Consider updating to the official template.
�[0msrv          init: init: chat template, thinking = 1
main: model loaded
main: server is listening on http://127.0.0.1:8080
main: starting the main loop...
srv  update_slots: all slots are idle
srv  log_server_r: done request: GET / 127.0.0.1 200
srv  log_server_r: done request: GET /bundle.css 127.0.0.1 200
srv  log_server_r: done request: GET /bundle.js 127.0.0.1 200
srv  log_server_r: done request: HEAD /cors-proxy 127.0.0.1 404
common_chat_try_specialized_template: detected an outdated gemma4 chat template, applying compatibility workarounds. Consider updating to the official template.
�[0msrv  params_from_: Chat format: peg-gemma4
slot get_availabl: id  0 | task -1 | selected slot by LRU, t_last = -1
srv  get_availabl: updating prompt cache
�[0msrv          load:  - looking for better prompt, base f_keep = -1.000, sim = 0.000
�[0msrv        update:  - cache state: 0 prompts, 0.000 MiB (limits: 8192.000 MiB, 32768 tokens, 8589934592 est)
�[0msrv  get_availabl: prompt cache update took 0.01 ms
�[0mslot launch_slot_: id  0 | task -1 | sampler chain: logits -> ?penalties -> dry -> ?top-n-sigma -> top-k -> ?typical -> top-p -> min-p -> ?xtc -> temp-ext -> dist
slot launch_slot_: id  0 | task 0 | processing task, is_child = 0
slot update_slots: id  0 | task 0 | new prompt, n_ctx_slot = 32768, n_keep = 0, task.n_tokens = 617
slot update_slots: id  0 | task 0 | n_tokens = 0, memory_seq_rm [0, end)
slot update_slots: id  0 | task 0 | prompt processing progress, n_tokens = 11, batch.n_tokens = 11, progress = 0.017828
srv  log_server_r: done request: POST /v1/chat/completions 127.0.0.1 200
slot update_slots: id  0 | task 0 | n_tokens = 11, memory_seq_rm [11, end)
srv  process_chun: processing audio...
encoding audio slice...
audio slice encoded in 646 ms
decoding audio batch 1/1, n_tokens_batch = 600
D:/a/llama.cpp/llama.cpp/src/llama-context.cpp:1601: GGML_ASSERT((cparams.causal_attn || cparams.n_ubatch >= n_tokens_all) && "non-causal attention requires n_ubatch >= n_tokens") failed

[CRITICAL] Server crashed. Check your CUDA DLLs or VRAM.