GGML_VK_VISIBLE_DEVICES=0,1 ./llama-server -t 8 --context-shift -ctk q8_0 -ctv q8_0 -c 24576 -ngl 100 -m ~/Applications/chat/gguf
/Qwen3-VL-8B-Thinking-UD-Q4_K_XL.gguf --mmproj ~/Applications/chat/gguf/Qwen3-VL-8B-Thinking-mmproj-F16.gguf
ggml_vulkan: Found 2 Vulkan devices:
ggml_vulkan: 0 = AMD Radeon RX 7800 XT (RADV NAVI32) (radv) | uma: 0 | fp16: 1 | bf16: 0 | warp size: 64 | shared memory: 65536 | int dot: 1 | matrix cores: KHR_coopmat
ggml_vulkan: 1 = AMD Radeon RX 5700 XT (RADV NAVI10) (radv) | uma: 0 | fp16: 1 | bf16: 0 | warp size: 32 | shared memory: 65536 | int dot: 0 | matrix cores: none
main: n_parallel is set to auto, using n_parallel = 4 and kv_unified = true
build: 7512 (179fd82a7) with GNU 15.2.1 for Linux x86_64
system info: n_threads = 8, n_threads_batch = 8, total_threads = 16

system_info: n_threads = 8 (n_threads_batch = 8) / 16 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | AVX_VNNI = 1 | AVX2 = 1 | F16C = 1 | FMA = 1 | BMI2 = 1 | AVX512 = 1 | AVX512_VBMI = 1 | AVX512_VNNI = 1 | AVX512_BF16 = 1 | LLAMAFILE = 1 | OPENMP = 1 | REPACK = 1 | 

init: using 15 threads for HTTP server
start: binding port with default address family
main: loading model
srv    load_model: loading model '/home/daniandtheweb/Applications/chat/gguf/Qwen3-VL-8B-Thinking-UD-Q4_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 memory use with initial parameters [MiB]:
llama_params_fit_impl:   - Vulkan0 (AMD Radeon RX 7800 XT (RADV NAVI32)):  16368 total,   4416 used,  10938 surplus
llama_params_fit_impl:   - Vulkan1 (AMD Radeon RX 5700 XT (RADV NAVI10)):   8176 total,   2766 used,   5392 surplus
llama_params_fit_impl: projected to use 7182 MiB of device memory vs. 24544 MiB of free device memory
llama_params_fit_impl: will leave at least 5392 >= 1024 MiB of free memory on all devices, no changes needed
llama_params_fit: successfully fit params to free device memory
llama_params_fit: fitting params to free memory took 0.15 seconds
llama_model_load_from_file_impl: using device Vulkan0 (AMD Radeon RX 7800 XT (RADV NAVI32)) (0000:03:00.0) - 15354 MiB free
llama_model_load_from_file_impl: using device Vulkan1 (AMD Radeon RX 5700 XT (RADV NAVI10)) (0000:09:00.0) - 8158 MiB free
llama_model_loader: loaded meta data with 42 key-value pairs and 399 tensors from /home/daniandtheweb/Applications/chat/gguf/Qwen3-VL-8B-Thinking-UD-Q4_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              = qwen3vl
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                               general.name str              = Qwen3-Vl-8B-Thinking
llama_model_loader: - kv   3:                           general.finetune str              = Thinking
llama_model_loader: - kv   4:                           general.basename str              = Qwen3-Vl-8B-Thinking
llama_model_loader: - kv   5:                       general.quantized_by str              = Unsloth
llama_model_loader: - kv   6:                         general.size_label str              = 8B
llama_model_loader: - kv   7:                            general.license str              = apache-2.0
llama_model_loader: - kv   8:                           general.repo_url str              = https://huggingface.co/unsloth
llama_model_loader: - kv   9:                   general.base_model.count u32              = 1
llama_model_loader: - kv  10:                  general.base_model.0.name str              = Qwen3 VL 8B Thinking
llama_model_loader: - kv  11:          general.base_model.0.organization str              = Qwen
llama_model_loader: - kv  12:              general.base_model.0.repo_url str              = https://huggingface.co/Qwen/Qwen3-VL-...
llama_model_loader: - kv  13:                               general.tags arr[str,2]       = ["unsloth", "image-text-to-text"]
llama_model_loader: - kv  14:                        qwen3vl.block_count u32              = 36
llama_model_loader: - kv  15:                     qwen3vl.context_length u32              = 262144
llama_model_loader: - kv  16:                   qwen3vl.embedding_length u32              = 4096
llama_model_loader: - kv  17:                qwen3vl.feed_forward_length u32              = 12288
llama_model_loader: - kv  18:               qwen3vl.attention.head_count u32              = 32
llama_model_loader: - kv  19:            qwen3vl.attention.head_count_kv u32              = 8
llama_model_loader: - kv  20:                     qwen3vl.rope.freq_base f32              = 5000000.000000
llama_model_loader: - kv  21:   qwen3vl.attention.layer_norm_rms_epsilon f32              = 0.000001
llama_model_loader: - kv  22:               qwen3vl.attention.key_length u32              = 128
llama_model_loader: - kv  23:             qwen3vl.attention.value_length u32              = 128
llama_model_loader: - kv  24:            qwen3vl.rope.dimension_sections arr[i32,4]       = [24, 20, 20, 0]
llama_model_loader: - kv  25:                 qwen3vl.n_deepstack_layers u32              = 3
llama_model_loader: - kv  26:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  27:                         tokenizer.ggml.pre str              = qwen2
llama_model_loader: - kv  28:                      tokenizer.ggml.tokens arr[str,151936]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  29:                  tokenizer.ggml.token_type arr[i32,151936]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  30:                      tokenizer.ggml.merges arr[str,151387]  = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv  31:                tokenizer.ggml.eos_token_id u32              = 151645
llama_model_loader: - kv  32:            tokenizer.ggml.padding_token_id u32              = 151654
llama_model_loader: - kv  33:                tokenizer.ggml.bos_token_id u32              = 151643
llama_model_loader: - kv  34:               tokenizer.ggml.add_bos_token bool             = false
llama_model_loader: - kv  35:                    tokenizer.chat_template str              = {# Unsloth template fixes #}\n{%- set ...
llama_model_loader: - kv  36:               general.quantization_version u32              = 2
llama_model_loader: - kv  37:                          general.file_type u32              = 15
llama_model_loader: - kv  38:                      quantize.imatrix.file str              = Qwen3-VL-8B-Thinking-GGUF/imatrix_uns...
llama_model_loader: - kv  39:                   quantize.imatrix.dataset str              = unsloth_calibration_Qwen3-VL-8B-Think...
llama_model_loader: - kv  40:             quantize.imatrix.entries_count u32              = 252
llama_model_loader: - kv  41:              quantize.imatrix.chunks_count u32              = 684
llama_model_loader: - type  f32:  145 tensors
llama_model_loader: - type q4_K:  155 tensors
llama_model_loader: - type q5_K:   25 tensors
llama_model_loader: - type q6_K:   54 tensors
llama_model_loader: - type iq4_xs:   20 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q4_K - Medium
print_info: file size   = 4.77 GiB (5.00 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: no_alloc         = 0
print_info: n_ctx_train      = 262144
print_info: n_embd           = 4096
print_info: n_embd_inp       = 16384
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             = 12288
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_yarn_log_mul= 0.0000
print_info: rope_finetuned   = unknown
print_info: mrope sections   = [24, 20, 20, 0]
print_info: model type       = 8B
print_info: model params     = 8.19 B
print_info: general.name     = Qwen3-Vl-8B-Thinking
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        = 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 = true)
load_tensors: offloading output layer to GPU
load_tensors: offloading 35 repeating layers to GPU
load_tensors: offloaded 37/37 layers to GPU
load_tensors:   CPU_Mapped model buffer size =   333.84 MiB
load_tensors:      Vulkan0 model buffer size =  2805.34 MiB
load_tensors:      Vulkan1 model buffer size =  1740.57 MiB
......................................................................................
common_init_result: added <|endoftext|> logit bias = -inf
common_init_result: added <|im_end|> logit bias = -inf
common_init_result: added <|fim_pad|> logit bias = -inf
common_init_result: added <|repo_name|> logit bias = -inf
common_init_result: added <|file_sep|> logit bias = -inf
llama_context: constructing llama_context
llama_context: n_seq_max     = 4
llama_context: n_ctx         = 24576
llama_context: n_ctx_seq     = 24576
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 (24576) < n_ctx_train (262144) -- the full capacity of the model will not be utilized
llama_context: Vulkan_Host  output buffer size =     2.32 MiB
llama_kv_cache:    Vulkan0 KV buffer size =  1275.00 MiB
llama_kv_cache:    Vulkan1 KV buffer size =   561.00 MiB
llama_kv_cache: size = 1836.00 MiB ( 24576 cells,  36 layers,  4/1 seqs), K (q8_0):  918.00 MiB, V (q8_0):  918.00 MiB
llama_context: pipeline parallelism enabled (n_copies=4)
llama_context: Flash Attention was auto, set to enabled
llama_context:    Vulkan0 compute buffer size =   336.06 MiB
llama_context:    Vulkan1 compute buffer size =   432.82 MiB
llama_context: Vulkan_Host compute buffer size =   200.09 MiB
llama_context: graph nodes  = 1267
llama_context: graph splits = 3
common_init_from_params: warming up the model with an empty run - please wait ... (--no-warmup to disable)
srv  log_server_r: request: GET / 127.0.0.1 503
srv  log_server_r: request: GET / 127.0.0.1 503
srv  log_server_r: request: GET / 127.0.0.1 503
srv  log_server_r: request: GET / 127.0.0.1 503
srv  log_server_r: request: GET / 127.0.0.1 503
srv  log_server_r: request: GET / 127.0.0.1 503
clip_model_loader: model name:   Qwen3-Vl-8B-Thinking
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:         31

clip_model_loader: has vision encoder
clip_ctx: CLIP using Vulkan0 backend
load_hparams: Qwen-VL models require at minimum 1024 image tokens to function correctly on grounding tasks
load_hparams: if you encounter problems with accuracy, try adding --image-min-tokens 1024
load_hparams: more info: https://github.com/ggml-org/llama.cpp/issues/16842

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:     4096

--- 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:   4194304

load_hparams: model size:         1105.32 MiB
load_hparams: metadata size:      0.12 MiB
warmup: warmup with image size = 1472 x 1472
alloc_compute_meta:    Vulkan0 compute buffer size =   362.27 MiB
alloc_compute_meta:        CPU compute buffer size =    62.12 MiB
alloc_compute_meta: graph splits = 3, nodes = 853
warmup: flash attention is enabled
warmup: *****************************************************************
warmup: WARNING: the CLIP graph uses unsupported operators by the backend
warmup:          the performance will be suboptimal                      
warmup:          list of unsupported ops (backend=Vulkan0):
warmup:          UPSCALE: type = f32, ne = [92 92 1152 1]
warmup: flash attention is enabled
warmup: please report this on github as an issue
warmup: ref: https://github.com/ggml-org/llama.cpp/pull/16837#issuecomment-3461676118
warmup: *****************************************************************
srv    load_model: loaded multimodal model, '/home/daniandtheweb/Applications/chat/gguf/Qwen3-VL-8B-Thinking-mmproj-F16.gguf'
srv    load_model: ctx_shift is not supported by multimodal, it will be disabled
srv    load_model: initializing slots, n_slots = 4
slot   load_model: id  0 | task -1 | new slot, n_ctx = 24576
slot   load_model: id  1 | task -1 | new slot, n_ctx = 24576
slot   load_model: id  2 | task -1 | new slot, n_ctx = 24576
slot   load_model: id  3 | task -1 | new slot, n_ctx = 24576
srv    load_model: prompt cache is enabled, size limit: 8192 MiB
srv    load_model: use `--cache-ram 0` to disable the prompt cache
srv    load_model: for more info see https://github.com/ggml-org/llama.cpp/pull/16391
srv    load_model: thinking = 1
load_model: chat template, chat_template: {# Unsloth template fixes #}
{%- set image_count = namespace(value=0) %}
{%- set video_count = namespace(value=0) %}
{%- macro render_content(content, do_vision_count) %}
    {%- if content is string %}
        {{- content }}
    {%- else %}
        {%- for item in content %}
            {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
                {%- if do_vision_count %}
                    {%- set image_count.value = image_count.value + 1 %}
                {%- endif %}
                {%- if add_vision_id %}Picture {{ image_count.value }}: {% endif -%}
                <|vision_start|><|image_pad|><|vision_end|>
            {%- elif 'video' in item or item.type == 'video' %}
                {%- if do_vision_count %}
                    {%- set video_count.value = video_count.value + 1 %}
                {%- endif %}
                {%- if add_vision_id %}Video {{ video_count.value }}: {% endif -%}
                <|vision_start|><|video_pad|><|vision_end|>
            {%- elif 'text' in item %}
                {{- item.text }}
            {%- endif %}
        {%- endfor %}
    {%- endif %}
{%- endmacro %}
{%- if tools %}
    {{- '<|im_start|>system\n' }}
    {%- if messages[0].role == 'system' %}
        {{- render_content(messages[0].content, false) + '\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' + render_content(messages[0].content, false) + '<|im_end|>\n' }}
    {%- endif %}
{%- endif %}
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
{%- for message in messages[::-1] %}
    {%- set index = (messages|length - 1) - loop.index0 %}
    {%- if ns.multi_step_tool and message.role == "user" %}
        {%- set content = render_content(message.content, false) %}
        {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
            {%- set ns.multi_step_tool = false %}
            {%- set ns.last_query_index = index %}
        {%- endif %}
    {%- endif %}
{%- endfor %}
{%- for message in messages %}
    {%- set content = render_content(message.content, True) %}
    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
    {%- elif message.role == "assistant" %}
        {%- set reasoning_content = '' %}
        {%- if message.reasoning_content is string %}
            {%- set reasoning_content = message.reasoning_content %}
        {%- else %}
            {%- if '</think>' in content %}
                {# Unsloth template fixes - must change to for loop since llama.cpp will error out if not #}
                {%- set parts = content.split('</think>') %}
                {%- for part in parts %}
                    {%- if loop.index0 == 0 -%}
                        {%- set reasoning_content = part.rstrip('\n') %}
                        {%- set reasoning_content = (reasoning_content.split('<think>')|last) %}
                        {%- set reasoning_content = reasoning_content.lstrip('\n') -%}
                    {%- else -%}
                        {%- set content = part.lstrip('\n') %}
                    {%- endif %}
                {%- endfor %}
            {%- endif %}
        {%- endif %}
        {%- if loop.index0 > ns.last_query_index %}
            {%- if loop.last or (not loop.last and reasoning_content) %}
                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
            {%- else %}
                {{- '<|im_start|>' + message.role + '\n' + content }}
            {%- endif %}
        {%- else %}
            {{- '<|im_start|>' + message.role + '\n' + content }}
        {%- endif %}
        {%- if message.tool_calls %}
            {%- for tool_call in message.tool_calls %}
                {%- if (loop.first and 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' }}
        {{- content }}
        {{- '\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<think>\n' }}
{%- endif %}
{# Copyright 2025-present Unsloth. Apache 2.0 License. #}, 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
<think>
'
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: request: GET / 127.0.0.1 200
srv  log_server_r: request: GET /props 127.0.0.1 200
srv  log_server_r: request: GET /props 127.0.0.1 200
srv  log_server_r: request: GET /props 127.0.0.1 200
srv  log_server_r: request: GET /v1/models 127.0.0.1 200
srv  log_server_r: request: GET /props 127.0.0.1 200
srv  log_server_r: request: GET /props 127.0.0.1 200
srv  params_from_: Chat format: Hermes 2 Pro
slot get_availabl: id  3 | task -1 | selected slot by LRU, t_last = -1
slot launch_slot_: id  3 | 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  3 | task 0 | processing task
slot update_slots: id  3 | task 0 | new prompt, n_ctx_slot = 24576, n_keep = 0, task.n_tokens = 48
slot update_slots: id  3 | task 0 | n_tokens = 0, memory_seq_rm [0, end)
slot update_slots: id  3 | task 0 | prompt processing progress, n_tokens = 48, batch.n_tokens = 48, progress = 1.000000
slot update_slots: id  3 | task 0 | prompt done, n_tokens = 48, batch.n_tokens = 48
radv/amdgpu: The CS has been cancelled because the context is lost. This context is guilty of a hard recovery.
/home/daniandtheweb/Applications/chat/llama.cpp/build/bin/libggml-base.so.0(+0x156f6) [0x7ff7a58d46f6]
/home/daniandtheweb/Applications/chat/llama.cpp/build/bin/libggml-base.so.0(ggml_print_backtrace+0x203) [0x7ff7a58d4b33]
/home/daniandtheweb/Applications/chat/llama.cpp/build/bin/libggml-base.so.0(+0x284d9) [0x7ff7a58e74d9]
/usr/lib/libstdc++.so.6(+0xb1eba) [0x7ff7a1eb1eba]
/usr/lib/libstdc++.so.6(_ZSt10unexpectedv+0x0) [0x7ff7a1e975d9]
/usr/lib/libstdc++.so.6(+0xb2176) [0x7ff7a1eb2176]
/home/daniandtheweb/Applications/chat/llama.cpp/build/bin/libggml-vulkan.so.0(+0x8f984) [0x7ff7a228f984]
/home/daniandtheweb/Applications/chat/llama.cpp/build/bin/libggml-vulkan.so.0(+0x1b440e) [0x7ff7a23b440e]
/home/daniandtheweb/Applications/chat/llama.cpp/build/bin/libggml-vulkan.so.0(+0x1b504a) [0x7ff7a23b504a]
/home/daniandtheweb/Applications/chat/llama.cpp/build/bin/libggml-base.so.0(ggml_backend_sched_graph_compute_async+0x813) [0x7ff7a58f0583]
/home/daniandtheweb/Applications/chat/llama.cpp/build/bin/libllama.so.0(_ZN13llama_context13graph_computeEP11ggml_cgraphb+0xa0) [0x7ff7a56a4bb0]
/home/daniandtheweb/Applications/chat/llama.cpp/build/bin/libllama.so.0(_ZN13llama_context14process_ubatchERK12llama_ubatch14llm_graph_typeP22llama_memory_context_iR11ggml_status+0xf3) [0x7ff7a56a6883]
/home/daniandtheweb/Applications/chat/llama.cpp/build/bin/libllama.so.0(_ZN13llama_context6decodeERK11llama_batch+0x40f) [0x7ff7a56ac0ef]
/home/daniandtheweb/Applications/chat/llama.cpp/build/bin/libllama.so.0(llama_decode+0xe) [0x7ff7a56ad05e]
./llama-server(+0x17004e) [0x55d079ca104e]
./llama-server(+0x114971) [0x55d079c45971]
./llama-server(+0xa1346) [0x55d079bd2346]
/usr/lib/libc.so.6(+0x27635) [0x7ff7a1a27635]
/usr/lib/libc.so.6(__libc_start_main+0x89) [0x7ff7a1a276e9]
./llama-server(+0xa37f5) [0x55d079bd47f5]
terminate called after throwing an instance of 'vk::DeviceLostError'
  what():  vk::Queue::submit: ErrorDeviceLost
zsh: IOT instruction (core dumped)  GGML_VK_VISIBLE_DEVICES=0,1 ./llama-server -t 8 --context-shift -ctk q8_0 -ct