./llama-server \
-m ~/models/qwen3.5/Qwen3.5-27B-Q5_K_M.gguf \
-c 8000 \
--no-mmproj-offload \
--temp 1.0 \
--top-p 0.95 \
--top-k 20 \
--presence_penalty 1.5 \
--chat-template-kwargs '{"preserve_thinking": true}' \
--flash-attn on \
-ub 3072 \
-b 3072 \
-ngl 99 \
-ngld 99 \
-np 1 \
--host 0.0.0.0 \
--port 8088 \
--no-warmup \
--metrics
ggml_cuda_init: found 1 ROCm devices (Total VRAM: 32624 MiB):
Device 0: AMD Radeon AI PRO R9700, gfx1201 (0x1201), VMM: no, Wave Size: 32, VRAM: 32624 MiB
build_info: b9301-cb08642e6
system_info: n_threads = 8 (n_threads_batch = 8) / 16 | ROCm : NO_VMM = 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 |
init: using 15 threads for HTTP server
start: binding port with default address family
main: loading model
srv load_model: loading model '/home/user/models/qwen3.5/Qwen3.5-27B-Q5_K_M.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
common_params_fit_impl: getting device memory data for initial parameters:
common_memory_breakdown_print: | memory breakdown [MiB] | total free self model context compute unaccounted |
common_memory_breakdown_print: | - ROCm0 (AI PRO R9700) | 32624 = 32228 + (19508 = 17856 + 661 + 990) + -19112 |
common_memory_breakdown_print: | - Host | 905 = 833 + 0 + 72 |
common_params_fit_impl: projected to use 19508 MiB of device memory vs. 32228 MiB of free device memory
common_params_fit_impl: will leave 12719 >= 1024 MiB of free device memory, no changes needed
common_fit_params: successfully fit params to free device memory
common_fit_params: fitting params to free memory took 0.37 seconds
llama_model_load_from_file_impl: using device ROCm0 (AMD Radeon AI PRO R9700) (0000:08:00.0) - 32378 MiB free
llama_model_loader: loaded meta data with 49 key-value pairs and 851 tensors from /home/user/models/qwen3.5/Qwen3.5-27B-Q5_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 = 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 = Qwen3.5-27B
llama_model_loader: - kv 7: general.quantized_by str = Unsloth
llama_model_loader: - kv 8: general.size_label str = 27B
llama_model_loader: - kv 9: general.license str = apache-2.0
llama_model_loader: - kv 10: general.license.link str = https://huggingface.co/Qwen/Qwen3.5-2...
llama_model_loader: - kv 11: general.repo_url str = https://huggingface.co/unsloth
llama_model_loader: - kv 12: general.base_model.count u32 = 1
llama_model_loader: - kv 13: general.base_model.0.name str = Qwen3.5 27B
llama_model_loader: - kv 14: general.base_model.0.organization str = Qwen
llama_model_loader: - kv 15: general.base_model.0.repo_url str = https://huggingface.co/Qwen/Qwen3.5-27B
llama_model_loader: - kv 16: general.tags arr[str,3] = ["qwen3_5_moe", "unsloth", "image-tex...
llama_model_loader: - kv 17: qwen35.block_count u32 = 64
llama_model_loader: - kv 18: qwen35.context_length u32 = 262144
llama_model_loader: - kv 19: qwen35.embedding_length u32 = 5120
llama_model_loader: - kv 20: qwen35.feed_forward_length u32 = 17408
llama_model_loader: - kv 21: qwen35.attention.head_count u32 = 24
llama_model_loader: - kv 22: qwen35.attention.head_count_kv u32 = 4
llama_model_loader: - kv 23: qwen35.rope.dimension_sections arr[i32,4] = [11, 11, 10, 0]
llama_model_loader: - kv 24: qwen35.rope.freq_base f32 = 10000000.000000
llama_model_loader: - kv 25: qwen35.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 26: qwen35.attention.key_length u32 = 256
llama_model_loader: - kv 27: qwen35.attention.value_length u32 = 256
llama_model_loader: - kv 28: qwen35.ssm.conv_kernel u32 = 4
llama_model_loader: - kv 29: qwen35.ssm.state_size u32 = 128
llama_model_loader: - kv 30: qwen35.ssm.group_count u32 = 16
llama_model_loader: - kv 31: qwen35.ssm.time_step_rank u32 = 48
llama_model_loader: - kv 32: qwen35.ssm.inner_size u32 = 6144
llama_model_loader: - kv 33: qwen35.full_attention_interval u32 = 4
llama_model_loader: - kv 34: qwen35.rope.dimension_count u32 = 64
llama_model_loader: - kv 35: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 36: tokenizer.ggml.pre str = qwen35
llama_model_loader: - kv 37: tokenizer.ggml.tokens arr[str,248320] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 38: tokenizer.ggml.token_type arr[i32,248320] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 39: tokenizer.ggml.merges arr[str,247587] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 40: tokenizer.ggml.eos_token_id u32 = 248046
llama_model_loader: - kv 41: tokenizer.ggml.padding_token_id u32 = 248055
llama_model_loader: - kv 42: tokenizer.chat_template str = {%- set image_count = namespace(value...
llama_model_loader: - kv 43: general.quantization_version u32 = 2
llama_model_loader: - kv 44: general.file_type u32 = 17
llama_model_loader: - kv 45: quantize.imatrix.file str = Qwen3.5-27B-GGUF/imatrix_unsloth.gguf
llama_model_loader: - kv 46: quantize.imatrix.dataset str = unsloth_calibration_Qwen3.5-27B.txt
llama_model_loader: - kv 47: quantize.imatrix.entries_count u32 = 496
llama_model_loader: - kv 48: quantize.imatrix.chunks_count u32 = 80
llama_model_loader: - type f32: 353 tensors
llama_model_loader: - type q8_0: 96 tensors
llama_model_loader: - type q5_K: 263 tensors
llama_model_loader: - type q6_K: 139 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q5_K - Medium
print_info: file size = 18.25 GiB (5.83 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 = -1
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 = 27B
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 = 248055 '<|vision_pad|>'
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 = 833.59 MiB
load_tensors: ROCm0 model buffer size = 17856.52 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 = 8192
llama_context: n_ctx_seq = 8192
llama_context: n_batch = 1024
llama_context: n_ubatch = 1024
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: n_ctx_seq (8192) < n_ctx_train (262144) -- the full capacity of the model will not be utilized
llama_context: ROCm_Host output buffer size = 0.95 MiB
llama_kv_cache: ROCm0 KV buffer size = 512.00 MiB
llama_kv_cache: size = 512.00 MiB ( 8192 cells, 16 layers, 1/1 seqs), K (f16): 256.00 MiB, V (f16): 256.00 MiB
llama_kv_cache: attn_rot_k = 0, n_embd_head_k_all = 256
llama_kv_cache: attn_rot_v = 0, n_embd_head_k_all = 256
llama_memory_recurrent: ROCm0 RS buffer size = 149.62 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: resolving fused Gated Delta Net support:
sched_reserve: fused Gated Delta Net (autoregressive) enabled
sched_reserve: fused Gated Delta Net (chunked) enabled
sched_reserve: ROCm0 compute buffer size = 990.00 MiB
sched_reserve: ROCm_Host compute buffer size = 72.04 MiB
sched_reserve: graph nodes = 3657
sched_reserve: graph splits = 2
sched_reserve: reserve took 33.85 ms, sched copies = 1
srv load_model: initializing slots, n_slots = 1
Segmentation fault (core dumped)
Problem description & steps to reproduce
Latest build don't work anymore for rocm (r9700). Model load and right before server get launched i get Segmentation fault (core dumped).
Full Log and command below - click to open
Same command line was working perfectly before pulling latest master and building it.