Closed
Description
Name and Version
llama-server --version
load_backend: loaded RPC backend from D:\AI\app\llama.cpp\ggml-rpc.dll
ggml_vulkan: Found 1 Vulkan devices:
ggml_vulkan: 0 = AMD Radeon RX 6600M (AMD proprietary driver) | uma: 0 | fp16: 1 | warp size: 32 | shared memory: 32768 | int dot: 1 | matrix cores: none
load_backend: loaded Vulkan backend from D:\AI\app\llama.cpp\ggml-vulkan.dll
load_backend: loaded CPU backend from D:\AI\app\llama.cpp\ggml-cpu-haswell.dll
version: 5342 (0208355)
built with MSVC 19.43.34808.0 for x64
Operating systems
Windows
GGML backends
Vulkan
Hardware
AMD Ryzen 7 5800H/AMD Radeon RX 6600M
Models
https://www.modelscope.cn/models/bartowski/Qwen_Qwen2.5-VL-7B-Instruct-GGUF/Qwen_Qwen2.5-VL-7B-Instruct-Q5_K_S.gguf 和https://www.modelscope.cn/models/bartowski/Qwen_Qwen2.5-VL-7B-Instruct-GGUF/mmproj-Qwen_Qwen2.5-VL-7B-Instruct-bf16.gguf
也试过：https://www.modelscope.cn/models/ggml-org/Qwen2.5-VL-7B-Instruct-GGUF/Qwen2.5-VL-7B-Instruct-Q4_K_M.gguf 和 https://www.modelscope.cn/models/ggml-org/Qwen2.5-VL-7B-Instruct-GGUF/mmproj-Qwen2.5-VL-7B-Instruct-f16.gguf
Problem description & steps to reproduce
Qwen2.5-VL-7B-Instruct 在做图像识别时：分辨率为328409，没有问题；分辨率为1242881 时 模型会崩溃，但是如果在加载模型的参数中添加--no-mmproj-offload，可以正常工作（很慢）。Gemma-3-4B、12B都没有问题。
First Bad Commit
从llama-server可以支持多模态开始就存在该错误
Relevant log output
PS D:\AI> ./llama-swap -config config.yaml
llama-swap listening on :8080
"20.Qwen2.5-VL-7B-Instruct":
cmd: >
llama-server
--host 0.0.0.0
--port ${PORT}
--model models/Bartowski/Qwen2.5-VL-7B-Instruct-GGUF/Qwen2.5-VL-7B-Instruct-Q5_K_S.gguf
--mmproj models/Bartowski/Qwen2.5-VL-7B-Instruct-GGUF/mmproj-Qwen2.5-VL-7B-Instruct-f16.gguf
-ngl 99
proxy:
# list of model name aliases this llama.cpp instance can serve
aliases:
- Qwen2.5-VL-7B-Instruct
# `useModelName` overrides the model name in the request
# and sends a specific name to the upstream server
useModelName: "Qwen2.5-VL-7B-Instruct"
# check this path for a HTTP 200 response for the server to be ready
checkEndpoint: /health
load_backend: loaded RPC backend from D:\AI\app\llama.cpp\ggml-rpc.dll
ggml_vulkan: Found 1 Vulkan devices:
ggml_vulkan: 0 = AMD Radeon RX 6600M (AMD proprietary driver) | uma: 0 | fp16: 1 | warp size: 32 | shared memory: 32768 | int dot: 1 | matrix cores: none
load_backend: loaded Vulkan backend from D:\AI\app\llama.cpp\ggml-vulkan.dll
load_backend: loaded CPU backend from D:\AI\app\llama.cpp\ggml-cpu-haswell.dll
build: 5342 (0208355f) with MSVC 19.43.34808.0 for x64
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 | AVX2 = 1 | F16C = 1 | FMA = 1 | BMI2 = 1 | LLAMAFILE = 1 | OPENMP = 1 | AARCH64_REPACK = 1 |
main: binding port with default address family
main: HTTP server is listening, hostname: 0.0.0.0, port: 8090, http threads: 15
main: loading model
srv load_model: loading model 'models/Bartowski/Qwen2.5-VL-7B-Instruct-GGUF/Qwen2.5-VL-7B-Instruct-Q5_K_S.gguf'
llama_model_load_from_file_impl: using device Vulkan0 (AMD Radeon RX 6600M) - 8176 MiB free
llama_model_loader: loaded meta data with 31 key-value pairs and 339 tensors from models/Bartowski/Qwen2.5-VL-7B-Instruct-GGUF/Qwen2.5-VL-7B-Instruct-Q5_K_S.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 = qwen2vl
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Qwen2.5 VL 7B Instruct
llama_model_loader: - kv 3: general.finetune str = Instruct
llama_model_loader: - kv 4: general.basename str = Qwen2.5-VL
llama_model_loader: - kv 5: general.size_label str = 7B
llama_model_loader: - kv 6: qwen2vl.block_count u32 = 28
llama_model_loader: - kv 7: qwen2vl.context_length u32 = 128000
llama_model_loader: - kv 8: qwen2vl.embedding_length u32 = 3584
llama_model_loader: - kv 9: qwen2vl.feed_forward_length u32 = 18944
llama_model_loader: - kv 10: qwen2vl.attention.head_count u32 = 28
llama_model_loader: - kv 11: qwen2vl.attention.head_count_kv u32 = 4
llama_model_loader: - kv 12: qwen2vl.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 13: qwen2vl.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 14: qwen2vl.rope.dimension_sections arr[i32,4] = [16, 24, 24, 0]
llama_model_loader: - kv 15: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 16: tokenizer.ggml.pre str = qwen2
llama_model_loader: - kv 17: tokenizer.ggml.tokens arr[str,152064] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 18: tokenizer.ggml.token_type arr[i32,152064] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
srv log_server_r: request: GET /health 127.0.0.1 503
[INFO] <20.Qwen2.5-VL-7B-Instruct> Health check error on http://localhost:8090/health, status code: 503
llama_model_loader: - kv 19: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 20: tokenizer.ggml.eos_token_id u32 = 151645
llama_model_loader: - kv 21: tokenizer.ggml.padding_token_id u32 = 151643
llama_model_loader: - kv 22: tokenizer.ggml.bos_token_id u32 = 151643
llama_model_loader: - kv 23: tokenizer.ggml.add_bos_token bool = false
llama_model_loader: - kv 24: tokenizer.chat_template str = {% set image_count = namespace(value=...
llama_model_loader: - kv 25: general.quantization_version u32 = 2
llama_model_loader: - kv 26: general.file_type u32 = 16
llama_model_loader: - kv 27: quantize.imatrix.file str = /models_out/Qwen2.5-VL-7B-Instruct-GG...
llama_model_loader: - kv 28: quantize.imatrix.dataset str = /training_dir/calibration_datav3.txt
llama_model_loader: - kv 29: quantize.imatrix.entries_count i32 = 196
llama_model_loader: - kv 30: quantize.imatrix.chunks_count i32 = 128
llama_model_loader: - type f32: 141 tensors
llama_model_loader: - type q5_K: 197 tensors
llama_model_loader: - type q6_K: 1 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q5_K - Small
print_info: file size = 4.94 GiB (5.58 BPW)
load: special tokens cache size = 22
load: token to piece cache size = 0.9310 MB
print_info: arch = qwen2vl
print_info: vocab_only = 0
print_info: n_ctx_train = 128000
print_info: n_embd = 3584
print_info: n_layer = 28
print_info: n_head = 28
print_info: n_head_kv = 4
print_info: n_rot = 128
print_info: n_swa = 0
print_info: n_swa_pattern = 1
print_info: n_embd_head_k = 128
print_info: n_embd_head_v = 128
print_info: n_gqa = 7
print_info: n_embd_k_gqa = 512
print_info: n_embd_v_gqa = 512
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 = 18944
print_info: n_expert = 0
print_info: n_expert_used = 0
print_info: causal attn = 1
print_info: pooling type = -1
print_info: rope type = 8
print_info: rope scaling = linear
print_info: freq_base_train = 1000000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn = 128000
print_info: rope_finetuned = unknown
print_info: ssm_d_conv = 0
print_info: ssm_d_inner = 0
print_info: ssm_d_state = 0
print_info: ssm_dt_rank = 0
print_info: ssm_dt_b_c_rms = 0
print_info: model type = 7B
print_info: model params = 7.62 B
print_info: general.name = Qwen2.5 VL 7B Instruct
print_info: vocab type = BPE
print_info: n_vocab = 152064
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 28 repeating layers to GPU
load_tensors: offloading output layer to GPU
load_tensors: offloaded 29/29 layers to GPU
load_tensors: Vulkan0 model buffer size = 4705.94 MiB
load_tensors: CPU_Mapped model buffer size = 357.33 MiB
......................................................................................
llama_context: constructing llama_context
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 = 0
llama_context: freq_base = 1000000.0
llama_context: freq_scale = 1
llama_context: n_ctx_per_seq (4096) < n_ctx_train (128000) -- the full capacity of the model will not be utilized
llama_context: Vulkan_Host output buffer size = 0.58 MiB
llama_kv_cache_unified: kv_size = 4096, type_k = 'f16', type_v = 'f16', n_layer = 28, can_shift = 1, padding = 32
llama_kv_cache_unified: Vulkan0 KV buffer size = 224.00 MiB
llama_kv_cache_unified: KV self size = 224.00 MiB, K (f16): 112.00 MiB, V (f16): 112.00 MiB
llama_context: Vulkan0 compute buffer size = 304.00 MiB
llama_context: Vulkan_Host compute buffer size = 15.01 MiB
llama_context: graph nodes = 1042
llama_context: graph splits = 2
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)
clip_ctx: CLIP using Vulkan0 backend
clip_model_loader: model name: Qwen2.5 VL 7B Instruct
clip_model_loader: description:
clip_model_loader: GGUF version: 3
clip_model_loader: alignment: 32
clip_model_loader: n_tensors: 519
clip_model_loader: n_kv: 22
load_hparams: projector: qwen2.5vl_merger
load_hparams: n_embd: 1280
load_hparams: n_head: 16
load_hparams: n_ff: 3420
load_hparams: n_layer: 32
load_hparams: projection_dim: 3584
load_hparams: image_size: 3584
load_hparams: patch_size: 14
load_hparams: has_llava_proj: 0
load_hparams: minicpmv_version: 0
load_hparams: proj_scale_factor: 0
load_hparams: n_wa_pattern: 8
load_hparams: ffn_op: silu
load_hparams: model size: 1291.40 MiB
load_hparams: metadata size: 0.18 MiB
srv log_server_r: request: GET /health 127.0.0.1 503
[INFO] <20.Qwen2.5-VL-7B-Instruct> Health check error on http://localhost:8090/health, status code: 503
alloc_compute_meta: Vulkan0 compute buffer size = 2.77 MiB
alloc_compute_meta: CPU compute buffer size = 0.16 MiB
srv load_model: loaded multimodal model, 'models/Bartowski/Qwen2.5-VL-7B-Instruct-GGUF/mmproj-Qwen2.5-VL-7B-Instruct-f16.gguf'
srv load_model: ctx_shift is not supported by multimodal, it will be disabled
srv init: initializing slots, n_slots = 1
slot init: id 0 | task -1 | new slot n_ctx_slot = 4096
main: model loaded
main: chat template, chat_template: {% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system
You are a helpful assistant.<|im_end|>
{% endif %}<|im_start|>{{ message['role'] }}
{% if message['content'] is string %}{{ message['content'] }}<|im_end|>
{% 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 %}<|im_end|>
{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant
{% 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://0.0.0.0:8090 - starting the main loop
srv update_slots: all slots are idle
srv log_server_r: request: GET /health 127.0.0.1 200
[INFO] <20.Qwen2.5-VL-7B-Instruct> Health check passed on http://localhost:8090/health
srv log_server_r: request: GET / 127.0.0.1 200
[INFO] Request ::1 "GET /upstream/20.Qwen2.5-VL-7B-Instruct/ HTTP/1.1" 200 1290053 "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/136.0.0.0 Safari/537.36 Edg/136.0.0.0" 10.3580702s
srv log_server_r: request: GET /props 127.0.0.1 200
[INFO] Request ::1 "GET /upstream/20.Qwen2.5-VL-7B-Instruct/props HTTP/1.1" 200 2535 "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/136.0.0.0 Safari/537.36 Edg/136.0.0.0" 2.0878ms
srv params_from_: Chat format: Content-only
slot launch_slot_: id 0 | task 0 | processing task
slot update_slots: id 0 | task 0 | new prompt, n_ctx_slot = 4096, n_keep = 0, n_prompt_tokens = 24
slot update_slots: id 0 | task 0 | kv cache rm [0, end)
slot update_slots: id 0 | task 0 | prompt processing progress, n_past = 14, n_tokens = 14, progress = 0.583333
slot update_slots: id 0 | task 0 | kv cache rm [14, end)
srv process_chun: processing image...
ggml_vulkan: Device memory allocation of size 2417184000 failed.
ggml_vulkan: Requested buffer size exceeds device memory allocation limit: ErrorOutOfDeviceMemory
ggml_gallocr_reserve_n: failed to allocate Vulkan0 buffer of size 2417184000
D:\a\llama.cpp\llama.cpp\ggml\src\ggml-backend.cpp:1663: GGML_ASSERT((char *)addr + ggml_backend_buffer_get_alloc_size(buffer, tensor) <= (char *)ggml_backend_buffer_get_base(buffer) + ggml_backend_buffer_get_size(buffer)) failed
[INFO] Request ::1 "POST /upstream/20.Qwen2.5-VL-7B-Instruct/v1/chat/completions HTTP/1.1" 502 114 "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/136.0.0.0 Safari/537.36 Edg/136.0.0.0" 757.1853ms