ggml_cuda_init: found 1 CUDA devices:
Device 0: NVIDIA GeForce RTX 4070, compute capability 8.9, VMM: yes
DEPRECATED: argument '--rope-scale' specified multiple times, use comma-separated values instead (only last value will be used)
build: 8148 (244641955) with GNU 11.2.0 for Linux x86_64
llama_model_load_from_file_impl: using device RPC0 (192.9.200.4:50052) (unknown id) - 11844 MiB free
llama_model_load_from_file_impl: using device CUDA0 (NVIDIA GeForce RTX 4070) (0000:01:00.0) - 11558 MiB free
llama_model_loader: loaded meta data with 40 key-value pairs and 851 tensors from /data3hd/models/Qwen3.5-27B.Q4_K_H.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 = qwen35
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 = 0.600000
llama_model_loader: - kv 5: general.name str = Qwen3.5 27B
llama_model_loader: - kv 6: general.basename str = Qwen3.5
llama_model_loader: - kv 7: general.size_label str = 27B
llama_model_loader: - kv 8: general.license str = apache-2.0
llama_model_loader: - kv 9: general.license.link str = https://huggingface.co/Qwen/Qwen3.5-2...
llama_model_loader: - kv 10: general.tags arr[str,1] = ["image-text-to-text"]
llama_model_loader: - kv 11: qwen35.block_count u32 = 64
llama_model_loader: - kv 12: qwen35.context_length u32 = 262144
llama_model_loader: - kv 13: qwen35.embedding_length u32 = 5120
llama_model_loader: - kv 14: qwen35.feed_forward_length u32 = 17408
llama_model_loader: - kv 15: qwen35.attention.head_count u32 = 24
llama_model_loader: - kv 16: qwen35.attention.head_count_kv u32 = 4
llama_model_loader: - kv 17: qwen35.rope.dimension_sections arr[i32,4] = [11, 11, 10, 0]
llama_model_loader: - kv 18: qwen35.rope.freq_base f32 = 10000000.000000
llama_model_loader: - kv 19: qwen35.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 20: qwen35.attention.key_length u32 = 256
llama_model_loader: - kv 21: qwen35.attention.value_length u32 = 256
llama_model_loader: - kv 22: qwen35.ssm.conv_kernel u32 = 4
llama_model_loader: - kv 23: qwen35.ssm.state_size u32 = 128
llama_model_loader: - kv 24: qwen35.ssm.group_count u32 = 16
llama_model_loader: - kv 25: qwen35.ssm.time_step_rank u32 = 48
llama_model_loader: - kv 26: qwen35.ssm.inner_size u32 = 6144
llama_model_loader: - kv 27: qwen35.full_attention_interval u32 = 4
llama_model_loader: - kv 28: qwen35.rope.dimension_count u32 = 64
llama_model_loader: - kv 29: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 30: tokenizer.ggml.pre str = qwen35
llama_model_loader: - kv 31: tokenizer.ggml.tokens arr[str,248320] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 32: tokenizer.ggml.token_type arr[i32,248320] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 33: tokenizer.ggml.merges arr[str,247587] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 34: tokenizer.ggml.eos_token_id u32 = 248046
llama_model_loader: - kv 35: tokenizer.ggml.padding_token_id u32 = 248044
llama_model_loader: - kv 36: tokenizer.ggml.add_bos_token bool = false
llama_model_loader: - kv 37: tokenizer.chat_template str = {%- set image_count = namespace(value...
llama_model_loader: - kv 38: general.quantization_version u32 = 2
llama_model_loader: - kv 39: general.file_type u32 = 15
llama_model_loader: - type f32: 353 tensors
llama_model_loader: - type q3_K: 118 tensors
llama_model_loader: - type q4_K: 261 tensors
llama_model_loader: - type q5_K: 79 tensors
llama_model_loader: - type q6_K: 40 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 14.85 GiB (4.74 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 = qwen35
print_info: vocab_only = 0
print_info: no_alloc = 0
print_info: n_ctx_train = 262144
print_info: n_embd = 5120
print_info: n_embd_inp = 5120
print_info: n_layer = 64
print_info: n_head = 24
print_info: n_head_kv = 4
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 = 6
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 = 17408
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 = 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 = 6144
print_info: ssm_d_state = 128
print_info: ssm_dt_rank = 48
print_info: ssm_n_group = 16
print_info: ssm_dt_b_c_rms = 0
print_info: model type = ?B
print_info: model params = 26.90 B
print_info: general.name = Qwen3.5 27B
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 = true, direct_io = false)
load_tensors: offloading output layer to GPU
load_tensors: offloading 63 repeating layers to GPU
load_tensors: offloaded 65/65 layers to GPU
load_tensors: CPU_Mapped model buffer size = 682.03 MiB
load_tensors: CUDA0 model buffer size = 7827.38 MiB
load_tensors: RPC0[192.9.200.4:50052] model buffer size = 6700.44 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 = 1
llama_context: n_ctx = 1024
llama_context: n_ctx_seq = 1024
llama_context: n_batch = 128
llama_context: n_ubatch = 128
llama_context: causal_attn = 1
llama_context: flash_attn = enabled
llama_context: kv_unified = false
llama_context: freq_base = 10000000.0
llama_context: freq_scale = 1
llama_context: yarn_log_mul = 0
llama_context: n_ctx_seq (1024) < n_ctx_train (262144) -- the full capacity of the model will not be utilized
llama_context: CUDA_Host output buffer size = 0.95 MiB
llama_kv_cache: CUDA0 KV buffer size = 32.00 MiB
llama_kv_cache: RPC0[192.9.200.4:50052] KV buffer size = 32.00 MiB
llama_kv_cache: size = 64.00 MiB ( 1024 cells, 16 layers, 1/1 seqs), K (f16): 32.00 MiB, V (f16): 32.00 MiB
llama_memory_recurrent: CUDA0 RS buffer size = 68.58 MiB
llama_memory_recurrent: RPC0[192.9.200.4:50052] RS buffer size = 81.05 MiB
llama_memory_recurrent: size = 149.62 MiB ( 1 cells, 64 layers, 1 seqs), R (f32): 5.62 MiB, S (f32): 144.00 MiB
sched_reserve: reserving ...
sched_reserve: RPC0[192.9.200.4:50052] compute buffer size = 42.12 MiB
sched_reserve: CUDA0 compute buffer size = 123.75 MiB
sched_reserve: CPU compute buffer size = 5.50 MiB
sched_reserve: graph nodes = 8409 (with bs=128), 4713 (with bs=1)
sched_reserve: graph splits = 3
sched_reserve: reserve took 134.68 ms, sched copies = 1
common_init_from_params: warming up the model with an empty run - please wait ... (--no-warmup to disable)
system_info: n_threads = 8 (n_threads_batch = 8) / 16 | CUDA : ARCHS = 800,890 | 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 |
perplexity: tokenizing the input ..
perplexity: tokenization took 149.382 ms
perplexity: calculating perplexity over 62 chunks, n_ctx=1024, batch_size=128, n_seq=1
perplexity: 2.29 seconds per pass - ETA 2.35 minutes
[1]4.1892,[2]5.7518,[3]6.3636,[4]6.7647,[5]7.3672,[6]7.4310,[7]7.2039,[8]7.4688,[9]7.5061,[10]7.2696,[11]7.1021,[12]6.4889,[13]6.1404,[14]5.9566,[15]5.7864,[16]5.6947,[17]5.7200,[18]5.8061,[19]5.8059,[20]5.9134,[21]5.9285,[22]5.9513,[23]5.8930,[24]6.0645,[25]6.1147,[26]6.1385,[27]6.2020,[28]6.2878,[29]6.2774,[30]6.2977,[31]6.3160,[32]6.3730,[33]6.4608,[34]6.4459,[35]6.4121,[36]6.4383,[37]6.4734,[38]6.4661,[39]6.4770,[40]6.3189,[41]6.3403,[42]6.3267,[43]6.3997,[44]6.3826,[45]6.3455,[46]6.3259,[47]6.3400,[48]6.3222,[49]6.3246,[50]6.3910,[51]6.3983,[52]6.3786,[53]6.3971,/usr/local/src/ai/lm/llama.cpp/ggml/src/ggml-rpc/ggml-rpc.cpp:669: Remote RPC server crashed or returned malformed response
recv failed (bytes_recv=0, size_to_recv=8)
[New LWP 14848]
[New LWP 14853]
[New LWP 14854]
[New LWP 14855]
[short2.txt](https://github.com/user-attachments/files/25547358/short2.txt)
[Thread debugging using libthread_db enabled]
Using host libthread_db library "/lib64/libthread_db.so.1".
0x00007fde7d1a83c7 in wait4 () from /lib64/libc.so.6
#0 0x00007fde7d1a83c7 in wait4 () from /lib64/libc.so.6
#1 0x00007fde7d641a0b in ggml_print_backtrace () from /usr/lib64/libggml-base.so.0
#2 0x00007fde7d641b5d in ggml_abort () from /usr/lib64/libggml-base.so.0
#3 0x00007fde7d6d79a2 in ggml_backend_rpc_buffer_get_tensor(ggml_backend_buffer*, ggml_tensor const*, void*, unsigned long, unsigned long) () from /usr/lib64/libggml-rpc.so.0
#4 0x00007fde7d6581d6 in ggml_backend_tensor_copy () from /usr/lib64/libggml-base.so.0
#5 0x00007fde7d65d026 in ggml_backend_sched_graph_compute_async () from /usr/lib64/libggml-base.so.0
#6 0x00007fde84c1e259 in llama_context::graph_compute(ggml_cgraph*, bool) () from /usr/lib64/libllama.so.0
#7 0x00007fde84c1e635 in llama_context::process_ubatch(llama_ubatch const&, llm_graph_type, llama_memory_context_i*, ggml_status&) () from /usr/lib64/libllama.so.0
#8 0x00007fde84c25e03 in llama_context::decode(llama_batch const&) () from /usr/lib64/libllama.so.0
#9 0x00007fde84c273fc in llama_decode () from /usr/lib64/libllama.so.0
#10 0x0000000000474004 in perplexity(llama_context*, common_params const&, int) ()
#11 0x000000000046bd1e in main ()
[Inferior 1 (process 14847) detached]
ll.start: line 1: 14847 Aborted llama-perplexity -m /data3hd/models/Qwen3.5-27B.Q4_K_H.gguf --rpc 192.9.200.4:50052 -ts .52028543291295045085,.47971456708704954914 -fit off --mmap -ngl 99 -c 1024 -b 128 -fa on --rope-scaling yarn --rope-scale 1.00000 --yarn-orig-ctx 262144 --rope_scale 1 -f short2.txt
Name and Version
llama.cpp b8148 on host and RPC machine
Operating systems
Linux
GGML backends
CUDA
Hardware
4070
Models
https://huggingface.co/steampunque/Qwen3.5-27B-MP-GGUF/blob/main/Qwen3.5-27B.Q4_K_H.gguf
Problem description & steps to reproduce
I found the model to intermittently crash when run with RPC on my downstream server. The problem can be replicated in upstream using a short perplexity run. The perplexity will run for awhile then eventually crash, same intermittent crashes I saw in my downstream server. My downstream server or perplexity will not crash if running locally without RPC.
llama-perplexity -m /data3hd/models/Qwen3.5-27B.Q4_K_H.gguf --rpc 192.9.200.4:50052 -ts .52028543291295045085,.47971456708704954914 -fit off --mmap -ngl 99 -c 1024 -b 128 -fa on --rope-scaling yarn --rope-scale 1.00000 --yarn-orig-ctx 262144 --rope_scale 1 -f short2.txt
short2.txt:
https://huggingface.co/steampunque/Qwen3.5-27B-MP-GGUF/blob/main/short2.txt
First Bad Commit
NA, new model
Relevant log output
Logs