ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 2 CUDA devices:
  Device 0: NVIDIA GeForce RTX 4060 Ti, compute capability 8.9, VMM: yes
  Device 1: NVIDIA GeForce RTX 3060, compute capability 8.6, VMM: yes
main: setting n_parallel = 4 and kv_unified = true
build: 6934 (72545ce2b) with cc (Debian 15.2.0-7) 15.2.0 for x86_64-linux-gnu
system info: n_threads = 16, n_threads_batch = 16, total_threads = 32

system_info: n_threads = 16 (n_threads_batch = 16) / 32 | CUDA : ARCHS = 860,890 | 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 | 

main: binding port with default address family
main: HTTP server is listening, hostname: 127.0.0.1, port: 8080, http threads: 31
main: loading model
srv    load_model: loading model 'Qwen3VL-32B-Instruct-Q4_K_M.gguf'
llama_model_load_from_file_impl: using device CUDA0 (NVIDIA GeForce RTX 4060 Ti) (0000:2b:00.0) - 15001 MiB free
llama_model_load_from_file_impl: using device CUDA1 (NVIDIA GeForce RTX 3060) (0000:04:00.0) - 11822 MiB free
llama_model_loader: loaded meta data with 32 key-value pairs and 707 tensors from Qwen3VL-32B-Instruct-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              = qwen3vl
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                               general.name str              = Qwen3Vl 32b Instruct
llama_model_loader: - kv   3:                           general.finetune str              = instruct
llama_model_loader: - kv   4:                           general.basename str              = qwen3vl
llama_model_loader: - kv   5:                         general.size_label str              = 32B
llama_model_loader: - kv   6:                            general.license str              = apache-2.0
llama_model_loader: - kv   7:                               general.tags arr[str,1]       = ["image-text-to-text"]
llama_model_loader: - kv   8:                        qwen3vl.block_count u32              = 64
llama_model_loader: - kv   9:                     qwen3vl.context_length u32              = 262144
llama_model_loader: - kv  10:                   qwen3vl.embedding_length u32              = 5120
llama_model_loader: - kv  11:                qwen3vl.feed_forward_length u32              = 25600
llama_model_loader: - kv  12:               qwen3vl.attention.head_count u32              = 64
llama_model_loader: - kv  13:            qwen3vl.attention.head_count_kv u32              = 8
llama_model_loader: - kv  14:                     qwen3vl.rope.freq_base f32              = 5000000.000000
llama_model_loader: - kv  15:   qwen3vl.attention.layer_norm_rms_epsilon f32              = 0.000001
llama_model_loader: - kv  16:               qwen3vl.attention.key_length u32              = 128
llama_model_loader: - kv  17:             qwen3vl.attention.value_length u32              = 128
llama_model_loader: - kv  18:            qwen3vl.rope.dimension_sections arr[i32,4]       = [24, 20, 20, 0]
llama_model_loader: - kv  19:                 qwen3vl.n_deepstack_layers u32              = 3
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:  257 tensors
llama_model_loader: - type q4_K:  385 tensors
llama_model_loader: - type q6_K:   65 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q4_K - Medium
print_info: file size   = 18.40 GiB (4.82 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             = qwen3vl
print_info: vocab_only       = 0
print_info: n_ctx_train      = 262144
print_info: n_embd           = 20480
print_info: n_layer          = 64
print_info: n_head           = 64
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            = 8
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             = 25600
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     = 0
print_info: rope type        = 40
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: mrope sections   = [24, 20, 20, 0]
print_info: model type       = 32B
print_info: model params     = 32.76 B
print_info: general.name     = Qwen3Vl 32b Instruct
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 64 repeating layers to GPU
load_tensors: offloading output layer to GPU
load_tensors: offloaded 65/65 layers to GPU
load_tensors:   CPU_Mapped model buffer size =   417.30 MiB
load_tensors:        CUDA0 model buffer size = 10249.06 MiB
load_tensors:        CUDA1 model buffer size =  8174.59 MiB
.................................................................................................
llama_context: constructing llama_context
llama_context: n_seq_max     = 4
llama_context: n_ctx         = 8192
llama_context: n_ctx_seq     = 8192
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 (8192) < n_ctx_train (262144) -- the full capacity of the model will not be utilized
llama_context:  CUDA_Host  output buffer size =     2.32 MiB
llama_kv_cache:      CUDA0 KV buffer size =  1184.00 MiB
llama_kv_cache:      CUDA1 KV buffer size =   864.00 MiB
llama_kv_cache: size = 2048.00 MiB (  8192 cells,  64 layers,  4/1 seqs), K (f16): 1024.00 MiB, V (f16): 1024.00 MiB
llama_context: Flash Attention was auto, set to enabled
llama_context:      CUDA0 compute buffer size =   194.02 MiB
llama_context:      CUDA1 compute buffer size =   306.75 MiB
llama_context:  CUDA_Host compute buffer size =    26.02 MiB
llama_context: graph nodes  = 2247
llama_context: graph splits = 3
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 = 8192
common_init_from_params: warming up the model with an empty run - please wait ... (--no-warmup to disable)
clip_model_loader: model name:   Qwen3Vl 32b Instruct
clip_model_loader: description:  
clip_model_loader: GGUF version: 3
clip_model_loader: alignment:    32
clip_model_loader: n_tensors:    352
clip_model_loader: n_kv:         25

clip_model_loader: has vision encoder
clip_ctx: CLIP using CUDA0 backend
load_hparams: projector:          qwen3vl_merger
load_hparams: n_embd:             1152
load_hparams: n_head:             16
load_hparams: n_ff:               4304
load_hparams: n_layer:            27
load_hparams: ffn_op:             gelu
load_hparams: projection_dim:     5120

--- vision hparams ---
load_hparams: image_size:         768
load_hparams: patch_size:         16
load_hparams: has_llava_proj:     0
load_hparams: minicpmv_version:   0
load_hparams: n_merge:            2
load_hparams: n_wa_pattern:       0
load_hparams: image_min_pixels:   8192
load_hparams: image_max_pixels:   2097152

load_hparams: model size:         1141.33 MiB
load_hparams: metadata size:      0.12 MiB
alloc_compute_meta: warmup with image size = 512 x 512
alloc_compute_meta:      CUDA0 compute buffer size =    50.52 MiB
alloc_compute_meta:        CPU compute buffer size =     3.02 MiB
alloc_compute_meta: graph splits = 1, nodes = 853
warmup: flash attention is enabled
srv    load_model: loaded multimodal model, 'mmproj-Qwen3VL-32B-Instruct-F16.gguf'
srv          init: initializing slots, n_slots = 4
slot         init: id  0 | task -1 | new slot, n_ctx = 8192
slot         init: id  1 | task -1 | new slot, n_ctx = 8192
slot         init: id  2 | task -1 | new slot, n_ctx = 8192
slot         init: id  3 | task -1 | new slot, n_ctx = 8192
srv          init: prompt cache is enabled, size limit: 8192 MiB
srv          init: use `--cache-ram 0` to disable the prompt cache
srv          init: for more info see https://github.com/ggml-org/llama.cpp/pull/16391
srv          init: thinking = 0
main: model loaded
main: chat template, chat_template: {%- if tools %}
    {{- '<|im_start|>system\n' }}
    {%- if messages[0].role == 'system' %}
        {%- if messages[0].content is string %}
            {{- messages[0].content }}
        {%- else %}
            {%- for content in messages[0].content %}
                {%- if 'text' in content %}
                    {{- content.text }}
                {%- endif %}
            {%- endfor %}
        {%- endif %}
        {{- '\n\n' }}
    {%- endif %}
    {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
    {%- for tool in tools %}
        {{- "\n" }}
        {{- tool | tojson }}
    {%- endfor %}
    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
{%- else %}
    {%- if messages[0].role == 'system' %}
        {{- '<|im_start|>system\n' }}
        {%- if messages[0].content is string %}
            {{- messages[0].content }}
        {%- else %}
            {%- for content in messages[0].content %}
                {%- if 'text' in content %}
                    {{- content.text }}
                {%- endif %}
            {%- endfor %}
        {%- endif %}
        {{- '<|im_end|>\n' }}
    {%- endif %}
{%- endif %}
{%- set image_count = namespace(value=0) %}
{%- set video_count = namespace(value=0) %}
{%- for message in messages %}
    {%- if message.role == "user" %}
        {{- '<|im_start|>' + message.role + '\n' }}
        {%- if message.content is string %}
            {{- message.content }}
        {%- else %}
            {%- for content in message.content %}
                {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}
                    {%- set image_count.value = image_count.value + 1 %}
                    {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}
                    <|vision_start|><|image_pad|><|vision_end|>
                {%- elif content.type == 'video' or 'video' in content %}
                    {%- set video_count.value = video_count.value + 1 %}
                    {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}
                    <|vision_start|><|video_pad|><|vision_end|>
                {%- elif 'text' in content %}
                    {{- content.text }}
                {%- endif %}
            {%- endfor %}
        {%- endif %}
        {{- '<|im_end|>\n' }}
    {%- elif message.role == "assistant" %}
        {{- '<|im_start|>' + message.role + '\n' }}
        {%- if message.content is string %}
            {{- message.content }}
        {%- else %}
            {%- for content_item in message.content %}
                {%- if 'text' in content_item %}
                    {{- content_item.text }}
                {%- endif %}
            {%- endfor %}
        {%- endif %}
        {%- if message.tool_calls %}
            {%- for tool_call in message.tool_calls %}
                {%- if (loop.first and message.content) or (not loop.first) %}
                    {{- '\n' }}
                {%- endif %}
                {%- if tool_call.function %}
                    {%- set tool_call = tool_call.function %}
                {%- endif %}
                {{- '<tool_call>\n{"name": "' }}
                {{- tool_call.name }}
                {{- '", "arguments": ' }}
                {%- if tool_call.arguments is string %}
                    {{- tool_call.arguments }}
                {%- else %}
                    {{- tool_call.arguments | tojson }}
                {%- endif %}
                {{- '}\n</tool_call>' }}
            {%- endfor %}
        {%- endif %}
        {{- '<|im_end|>\n' }}
    {%- elif message.role == "tool" %}
        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
            {{- '<|im_start|>user' }}
        {%- endif %}
        {{- '\n<tool_response>\n' }}
        {%- if message.content is string %}
            {{- message.content }}
        {%- else %}
            {%- for content in message.content %}
                {%- if content.type == 'image' or 'image' in content or 'image_url' in content %}
                    {%- set image_count.value = image_count.value + 1 %}
                    {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}
                    <|vision_start|><|image_pad|><|vision_end|>
                {%- elif content.type == 'video' or 'video' in content %}
                    {%- set video_count.value = video_count.value + 1 %}
                    {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}
                    <|vision_start|><|video_pad|><|vision_end|>
                {%- elif 'text' in content %}
                    {{- content.text }}
                {%- endif %}
            {%- endfor %}
        {%- endif %}
        {{- '\n</tool_response>' }}
        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
            {{- '<|im_end|>\n' }}
        {%- endif %}
    {%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
    {{- '<|im_start|>assistant\n' }}
{%- endif %}
, example_format: '<|im_start|>system
You are a helpful assistant<|im_end|>
<|im_start|>user
Hello<|im_end|>
<|im_start|>assistant
Hi there<|im_end|>
<|im_start|>user
How are you?<|im_end|>
<|im_start|>assistant
'
main: server is listening on http://127.0.0.1:8080 - starting the main loop
srv  update_slots: all slots are idle