ggml_cuda_init: found 2 ROCm devices:
Device 0: AMD Radeon Graphics, gfx906:sramecc+:xnack- (0x906), VMM: no, Wave Size: 64
Device 1: AMD Radeon Graphics, gfx906:sramecc+:xnack- (0x906), VMM: no, Wave Size: 64
main: n_parallel is set to auto, using n_parallel = 4 and kv_unified = true
build: 8184 (319146247) with Clang 22.0.0 for Linux x86_64
system info: n_threads = 16, n_threads_batch = 16, total_threads = 16
system_info: n_threads = 16 (n_threads_batch = 16) / 16 | ROCm : NO_VMM = 1 | PEER_MAX_BATCH_SIZE = 128 | FA_ALL_QUANTS = 1 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | F16C = 1 | LLAMAFILE = 1 | OPENMP = 1 | REPACK = 1 |
Running without SSL
init: using 15 threads for HTTP server
start: binding port with default address family
main: loading model
srv load_model: loading model '/home/xxx/ssdModels/Qwen_Qwen3.5-35B-A3B-Q8_0.gguf'
llama_model_load_from_file_impl: using device ROCm0 (AMD Radeon Graphics) (0000:01:00.0) - 32732 MiB free
llama_model_load_from_file_impl: using device ROCm1 (AMD Radeon Graphics) (0000:02:00.0) - 32732 MiB free
llama_model_loader: loaded meta data with 47 key-value pairs and 733 tensors from /home/xxx/ssdModels/Qwen_Qwen3.5-35B-A3B-Q8_0.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 = qwen35moe
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.sampling.top_k i32 = 20
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 = Qwen3.5 35B A3B
llama_model_loader: - kv 6: general.basename str = Qwen3.5
llama_model_loader: - kv 7: general.size_label str = 35B-A3B
llama_model_loader: - kv 8: general.license str = apache-2.0
llama_model_loader: - kv 9: general.license.link str = https://huggingface.co/Qwen/Qwen3.5-3...
llama_model_loader: - kv 10: general.tags arr[str,1] = ["image-text-to-text"]
llama_model_loader: - kv 11: qwen35moe.block_count u32 = 40
llama_model_loader: - kv 12: qwen35moe.context_length u32 = 262144
llama_model_loader: - kv 13: qwen35moe.embedding_length u32 = 2048
llama_model_loader: - kv 14: qwen35moe.attention.head_count u32 = 16
llama_model_loader: - kv 15: qwen35moe.attention.head_count_kv u32 = 2
llama_model_loader: - kv 16: qwen35moe.rope.dimension_sections arr[i32,4] = [11, 11, 10, 0]
llama_model_loader: - kv 17: qwen35moe.rope.freq_base f32 = 10000000.000000
llama_model_loader: - kv 18: qwen35moe.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 19: qwen35moe.expert_count u32 = 256
llama_model_loader: - kv 20: qwen35moe.expert_used_count u32 = 8
llama_model_loader: - kv 21: qwen35moe.attention.key_length u32 = 256
llama_model_loader: - kv 22: qwen35moe.attention.value_length u32 = 256
llama_model_loader: - kv 23: qwen35moe.expert_feed_forward_length u32 = 512
llama_model_loader: - kv 24: qwen35moe.expert_shared_feed_forward_length u32 = 512
llama_model_loader: - kv 25: qwen35moe.ssm.conv_kernel u32 = 4
llama_model_loader: - kv 26: qwen35moe.ssm.state_size u32 = 128
llama_model_loader: - kv 27: qwen35moe.ssm.group_count u32 = 16
llama_model_loader: - kv 28: qwen35moe.ssm.time_step_rank u32 = 32
llama_model_loader: - kv 29: qwen35moe.ssm.inner_size u32 = 4096
llama_model_loader: - kv 30: qwen35moe.full_attention_interval u32 = 4
llama_model_loader: - kv 31: qwen35moe.rope.dimension_count u32 = 64
llama_model_loader: - kv 32: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 33: tokenizer.ggml.pre str = qwen35
llama_model_loader: - kv 34: tokenizer.ggml.tokens arr[str,248320] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 35: tokenizer.ggml.token_type arr[i32,248320] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 36: tokenizer.ggml.merges arr[str,247587] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 37: tokenizer.ggml.eos_token_id u32 = 248046
llama_model_loader: - kv 38: tokenizer.ggml.padding_token_id u32 = 248044
llama_model_loader: - kv 39: tokenizer.ggml.add_bos_token bool = false
llama_model_loader: - kv 40: tokenizer.chat_template str = {%- set image_count = namespace(value...
llama_model_loader: - kv 41: general.quantization_version u32 = 2
llama_model_loader: - kv 42: general.file_type u32 = 7
llama_model_loader: - kv 43: quantize.imatrix.file str = /models_out/Qwen3.5-35B-A3B-GGUF/Qwen...
llama_model_loader: - kv 44: quantize.imatrix.dataset str = /training_dir/calibration_datav5.txt
llama_model_loader: - kv 45: quantize.imatrix.entries_count u32 = 510
llama_model_loader: - kv 46: quantize.imatrix.chunks_count u32 = 802
llama_model_loader: - type f32: 301 tensors
llama_model_loader: - type q8_0: 432 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q8_0
print_info: file size = 34.36 GiB (8.52 BPW)
load: 0 unused tokens
load: printing all EOG tokens:
load: - 248044 ('<|endoftext|>')
load: - 248046 ('<|im_end|>')
load: - 248063 ('<|fim_pad|>')
load: - 248064 ('<|repo_name|>')
load: - 248065 ('<|file_sep|>')
load: special tokens cache size = 33
load: token to piece cache size = 1.7581 MB
print_info: arch = qwen35moe
print_info: vocab_only = 0
print_info: no_alloc = 0
print_info: n_ctx_train = 262144
print_info: n_embd = 2048
print_info: n_embd_inp = 2048
print_info: n_layer = 40
print_info: n_head = 16
print_info: n_head_kv = 2
print_info: n_rot = 64
print_info: n_swa = 0
print_info: is_swa_any = 0
print_info: n_embd_head_k = 256
print_info: n_embd_head_v = 256
print_info: n_gqa = 8
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 = 0
print_info: n_expert = 256
print_info: n_expert_used = 8
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 = 10000000.0
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 = [11, 11, 10, 0]
print_info: ssm_d_conv = 4
print_info: ssm_d_inner = 4096
print_info: ssm_d_state = 128
print_info: ssm_dt_rank = 32
print_info: ssm_n_group = 16
print_info: ssm_dt_b_c_rms = 0
print_info: model type = ?B
print_info: model params = 34.66 B
print_info: general.name = Qwen3.5 35B A3B
print_info: vocab type = BPE
print_info: n_vocab = 248320
print_info: n_merges = 247587
print_info: BOS token = 11 ','
print_info: EOS token = 248046 '<|im_end|>'
print_info: EOT token = 248046 '<|im_end|>'
print_info: PAD token = 248044 '<|endoftext|>'
print_info: LF token = 198 'Ċ'
print_info: FIM PRE token = 248060 '<|fim_prefix|>'
print_info: FIM SUF token = 248062 '<|fim_suffix|>'
print_info: FIM MID token = 248061 '<|fim_middle|>'
print_info: FIM PAD token = 248063 '<|fim_pad|>'
print_info: FIM REP token = 248064 '<|repo_name|>'
print_info: FIM SEP token = 248065 '<|file_sep|>'
print_info: EOG token = 248044 '<|endoftext|>'
print_info: EOG token = 248046 '<|im_end|>'
print_info: EOG token = 248063 '<|fim_pad|>'
print_info: EOG token = 248064 '<|repo_name|>'
print_info: EOG token = 248065 '<|file_sep|>'
print_info: max token length = 256
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 39 repeating layers to GPU
load_tensors: offloaded 41/41 layers to GPU
load_tensors: ROCm0 model buffer size = 17931.70 MiB
load_tensors: ROCm1 model buffer size = 16736.08 MiB
load_tensors: ROCm_Host model buffer size = 515.31 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 = 262144
llama_context: n_ctx_seq = 262144
llama_context: n_batch = 1024
llama_context: n_ubatch = 1024
llama_context: causal_attn = 1
llama_context: flash_attn = enabled
llama_context: kv_unified = true
llama_context: freq_base = 10000000.0
llama_context: freq_scale = 1
llama_context: ROCm_Host output buffer size = 3.79 MiB
llama_kv_cache: ROCm0 KV buffer size = 1360.00 MiB
llama_kv_cache: ROCm1 KV buffer size = 1360.00 MiB
llama_kv_cache: size = 2720.00 MiB (262144 cells, 10 layers, 4/1 seqs), K (q8_0): 1360.00 MiB, V (q8_0): 1360.00 MiB
llama_memory_recurrent: ROCm0 RS buffer size = 134.00 MiB
llama_memory_recurrent: ROCm1 RS buffer size = 117.25 MiB
llama_memory_recurrent: size = 251.25 MiB ( 4 cells, 40 layers, 4 seqs), R (f32): 11.25 MiB, S (f32): 240.00 MiB
llama_context: pipeline parallelism enabled
sched_reserve: reserving ...
sched_reserve: ROCm0 compute buffer size = 4840.13 MiB
sched_reserve: ROCm1 compute buffer size = 3066.14 MiB
sched_reserve: ROCm_Host compute buffer size = 4112.16 MiB
sched_reserve: graph nodes = 7599 (with bs=1024), 4389 (with bs=1)
sched_reserve: graph splits = 3
sched_reserve: reserve took 6131.89 ms, sched copies = 4
common_init_from_params: warming up the model with an empty run - please wait ... (--no-warmup to disable)
srv load_model: initializing slots, n_slots = 4
common_speculative_is_compat: the target context does not support partial sequence removal
srv load_model: speculative decoding not supported by this context
slot load_model: id 0 | task -1 | new slot, n_ctx = 262144
slot load_model: id 1 | task -1 | new slot, n_ctx = 262144
slot load_model: id 2 | task -1 | new slot, n_ctx = 262144
slot load_model: id 3 | task -1 | new slot, n_ctx = 262144
srv load_model: prompt cache is enabled, size limit: 512 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
init: chat template, 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>
'
srv init: init: chat template, thinking = 1
main: model loaded
main: server is listening on http://0.0.0.0:8081
main: starting the main loop...
srv update_slots: all slots are idle
slot get_availabl: id 3 | task -1 | selected slot by LRU, t_last = -1
slot launch_slot_: id 3 | task -1 | sampler chain: logits -> logit-bias -> ?penalties -> ?dry -> ?top-n-sigma -> top-k -> ?typical -> ?top-p -> min-p -> ?xtc -> ?temp-ext -> adaptive-p
slot launch_slot_: id 3 | task 0 | processing task, is_child = 0
slot update_slots: id 3 | task 0 | new prompt, n_ctx_slot = 262144, n_keep = 0, task.n_tokens = 4397
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 = 1024, batch.n_tokens = 1024, progress = 0.232886
slot update_slots: id 3 | task 0 | n_tokens = 1024, memory_seq_rm [1024, end)
slot update_slots: id 3 | task 0 | prompt processing progress, n_tokens = 2048, batch.n_tokens = 1024, progress = 0.465772
slot update_slots: id 3 | task 0 | n_tokens = 2048, memory_seq_rm [2048, end)
slot update_slots: id 3 | task 0 | prompt processing progress, n_tokens = 3072, batch.n_tokens = 1024, progress = 0.698658
slot update_slots: id 3 | task 0 | n_tokens = 3072, memory_seq_rm [3072, end)
slot update_slots: id 3 | task 0 | prompt processing progress, n_tokens = 3885, batch.n_tokens = 813, progress = 0.883557
slot update_slots: id 3 | task 0 | n_tokens = 3885, memory_seq_rm [3885, end)
slot init_sampler: id 3 | task 0 | init sampler, took 1.15 ms, tokens: text = 4397, total = 4397
slot update_slots: id 3 | task 0 | created context checkpoint 1 of 8 (pos_min = 3884, pos_max = 3884, n_tokens = 3885, size = 62.813 MiB)
slot update_slots: id 3 | task 0 | prompt processing done, n_tokens = 4397, batch.n_tokens = 512
srv log_server_r: done request: POST /completion 172.18.0.5 200
srv stop: cancel task, id_task = 0
slot release: id 3 | task 0 | stop processing: n_tokens = 4869, truncated = 0
srv update_slots: all slots are idle
slot get_availabl: id 3 | task -1 | selected slot by LCP similarity, sim_best = 1.000 (> 0.100 thold), f_keep = 0.903
slot launch_slot_: id 3 | task -1 | sampler chain: logits -> logit-bias -> ?penalties -> ?dry -> ?top-n-sigma -> top-k -> ?typical -> ?top-p -> min-p -> ?xtc -> ?temp-ext -> adaptive-p
slot launch_slot_: id 3 | task 479 | processing task, is_child = 0
slot update_slots: id 3 | task 479 | new prompt, n_ctx_slot = 262144, n_keep = 0, task.n_tokens = 4397
slot update_slots: id 3 | task 479 | n_past = 4397, slot.prompt.tokens.size() = 4869, seq_id = 3, pos_min = 4868, n_swa = 1
Memory access fault by GPU node-2 (Agent handle: 0x5638e63e1b70) on address 0x7f0e69c13000. Reason: Page not present or supervisor privilege.
Failed to write segment data to pipe: Broken pipe
GPU coredump: handler exited with error (status: 1)
GPU core dump failed
Name and Version
ggml_cuda_init: found 2 ROCm devices:
Device 0: AMD Radeon Graphics, gfx906:sramecc+:xnack- (0x906), VMM: no, Wave Size: 64
Device 1: AMD Radeon Graphics, gfx906:sramecc+:xnack- (0x906), VMM: no, Wave Size: 64
version: 8184 (3191462)
built with Clang 22.0.0 for Linux x86_64
Operating systems
Linux
GGML backends
HIP
Hardware
2x AMD MI60 32GB
Models
Qwen3.5-35B-A3B Q8_0
Problem description & steps to reproduce
Using Arch Linux and have tried both ROCM 7.1 and 7.2 Qwen3.5-35B-A3B will crash with a memory access fault after one or two prompts have been processed. I've tried reinstalling rocm and rocblas, but it will still crash. Qwen 3.5 27b works fine.
./llama-server -m ~/ssdModels/Qwen_Qwen3.5-35B-A3B-Q8_0.gguf --split-mode layer --host 0.0.0.0 --port 8081 -ngl 99 -cram 512 -ctv q8_0 --fit off -fa on --no-mmap -ctk q8_0
First Bad Commit
No response
Relevant log output
Logs