Repository: gpustack/gpustack

Issue #1221: Failed to run Qwen2.5-0.5B-GGUF with error computeFunction must not be nil
Created: 2025-02-16T03:34:57Z
硬件：MacBook Pro Apple M2 Max
模型：Qwen/Qwen2.5-0.5B-Instruct-GGUF
量化：f16
后端：llama-box
python: 3.10.16 gpustack: 0.5.1 cmd: gpustack start 
日志如下：

2025-02-16T11:27:55+08:00 - gpustack.worker.downloaders - INFO - Retriving file lock
Downloading Model to directory: test/cache/model_scope/Qwen/Qwen2.5-0.5B-Instruct-GGUF
2025-02-16T11:27:56+08:00 - gpustack.worker.backends.llama_box - INFO - Starting llama-box server
0.00.001.686 I
0.00.001.695 I arguments  : /Users/robin/anaconda3/envs/gpustack/lib/python3.10/site-packages/gpustack/third_party/bin/llama-box/llama-box --host 0.0.0.0 --embeddings --gpu-layers 25 --parallel 4 --ctx-size 8192 --port 40072 --model test/cache/model_scope/Qwen/Qwen2___5-0___5B-Instruct-GGUF/qwen2.5-0.5b-instruct-fp16.gguf --alias qwen2.5 --no-mmap --no-warmup
0.00.001.696 I version    : v0.0.117 (315b735)
0.00.001.696 I compiler   : Apple clang version 15.0.0 (clang-1500.1.0.2.5)
0.00.001.696 I target     : arm64-apple-darwin23.6.0
0.00.001.697 I vendor     : llama.cpp 27d135c9 (4598), stable-diffusion.cpp 102953d (203)
0.00.002.153 I system_info: n_threads = 8 (n_threads_batch = 8) / 12 | Metal : EMBED_LIBRARY = 1 | BF16 = 1 | CPU : NEON = 1 | ARM_FMA = 1 | FP16_VA = 1 | DOTPROD = 1 | LLAMAFILE = 1 | ACCELERATE = 1 | AARCH64_REPACK = 1 |
0.00.002.155 I
0.00.002.482 I srv                      main: listening, hostname = 0.0.0.0, port = 40072, n_threads = 6 + 2
0.00.003.761 I srv                      main: loading model
0.00.003.766 I srv                load_model: loading model 'test/cache/model_scope/Qwen/Qwen2___5-0___5B-Instruct-GGUF/qwen2.5-0.5b-instruct-fp16.gguf'
0.00.056.451 I llama_model_load_from_file_impl: using device Metal (Apple M2 Max) - 21845 MiB free
0.00.085.445 I llama_model_loader: loaded meta data with 26 key-value pairs and 291 tensors from test/cache/model_scope/Qwen/Qwen2___5-0___5B-Instruct-GGUF/qwen2.5-0.5b-instruct-fp16.gguf (version GGUF V3 (latest))
0.00.085.451 I llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
0.00.085.453 I llama_model_loader: - kv   0:                       general.architecture str              = qwen2
0.00.085.453 I llama_model_loader: - kv   1:                               general.type str              = model
0.00.085.454 I llama_model_loader: - kv   2:                               general.name str              = qwen2.5-0.5b-instruct
0.00.085.454 I llama_model_loader: - kv   3:                            general.version str              = v0.1
0.00.085.455 I llama_model_loader: - kv   4:                           general.finetune str              = qwen2.5-0.5b-instruct
0.00.085.455 I llama_model_loader: - kv   5:                         general.size_label str              = 630M
0.00.085.456 I llama_model_loader: - kv   6:                          qwen2.block_count u32              = 24
0.00.085.457 I llama_model_loader: - kv   7:                       qwen2.context_length u32              = 8192
0.00.085.457 I llama_model_loader: - kv   8:                     qwen2.embedding_length u32              = 896
0.00.085.458 I llama_model_loader: - kv   9:                  qwen2.feed_forward_length u32              = 4864
0.00.085.458 I llama_model_loader: - kv  10:                 qwen2.attention.head_count u32              = 14
0.00.085.458 I llama_model_loader: - kv  11:              qwen2.attention.head_count_kv u32              = 2
0.00.085.460 I llama_model_loader: - kv  12:                       qwen2.rope.freq_base f32              = 1000000.000000
0.00.085.461 I llama_model_loader: - kv  13:     qwen2.attention.layer_norm_rms_epsilon f32              = 0.000001
0.00.085.461 I llama_model_loader: - kv  14:                          general.file_type u32              = 1
0.00.085.461 I llama_model_loader: - kv  15:                       tokenizer.ggml.model str              = gpt2
0.00.085.461 I llama_model_loader: - kv  16:                         tokenizer.ggml.pre str              = qwen2
0.00.100.828 I llama_model_loader: - kv  17:                      tokenizer.ggml.tokens arr[str,151936]  = ["!", """, "#", "$", "%", "&", "'", ...
0.00.104.888 I llama_model_loader: - kv  18:                  tokenizer.ggml.token_type arr[i32,151936]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
0.00.120.296 I llama_model_loader: - kv  19:                      tokenizer.ggml.merges arr[str,151387]  = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
0.00.120.298 I llama_model_loader: - kv  20:                tokenizer.ggml.eos_token_id u32              = 151645
0.00.120.299 I llama_model_loader: - kv  21:            tokenizer.ggml.padding_token_id u32              = 151643
0.00.120.299 I llama_model_loader: - kv  22:                tokenizer.ggml.bos_token_id u32              = 151643
0.00.120.300 I llama_model_loader: - kv  23:               tokenizer.ggml.add_bos_token bool             = false
0.00.120.302 I llama_model_loader: - kv  24:                    tokenizer.chat_template str              = {%- if tools %}\n    {{- '
...
0.00.120.303 I llama_model_loader: - kv  25:               general.quantization_version u32              = 2
0.00.120.303 I llama_model_loader: - type  f32:  121 tensors
0.00.120.304 I llama_model_loader: - type  f16:  170 tensors
0.00.120.305 I print_info: file format = GGUF V3 (latest)
0.00.120.310 I print_info: file type   = F16
0.00.120.311 I print_info: file size   = 1.17 GiB (16.00 BPW)
0.00.155.963 I load: special tokens cache size = 22
0.00.182.786 I load: token to piece cache size = 0.9310 MB
0.00.182.794 I print_info: arch             = qwen2
0.00.182.795 I print_info: vocab_only       = 0
0.00.182.795 I print_info: n_ctx_train      = 8192
0.00.182.797 I print_info: n_embd           = 896
0.00.182.798 I print_info: n_layer          = 24
0.00.182.804 I print_info: n_head           = 14
0.00.182.806 I print_info: n_head_kv        = 2
0.00.182.806 I print_info: n_rot            = 64
0.00.182.806 I print_info: n_swa            = 0
0.00.182.806 I print_info: n_embd_head_k    = 64
0.00.182.807 I print_info: n_embd_head_v    = 64
0.00.182.808 I print_info: n_gqa            = 7
0.00.182.809 I print_info: n_embd_k_gqa     = 128
0.00.182.810 I print_info: n_embd_v_gqa     = 128
0.00.182.811 I print_info: f_norm_eps       = 0.0e+00
0.00.182.811 I print_info: f_norm_rms_eps   = 1.0e-06
0.00.182.811 I print_info: f_clamp_kqv      = 0.0e+00
0.00.182.811 I print_info: f_max_alibi_bias = 0.0e+00
0.00.182.812 I print_info: f_logit_scale    = 0.0e+00
0.00.182.813 I print_info: n_ff             = 4864
0.00.182.813 I print_info: n_expert         = 0
0.00.182.813 I print_info: n_expert_used    = 0
0.00.182.814 I print_info: causal attn      = 1
0.00.182.814 I print_info: pooling type     = 0
0.00.182.814 I print_info: rope type        = 2
0.00.182.814 I print_info: rope scaling     = linear
0.00.182.815 I print_info: freq_base_train  = 1000000.0
0.00.182.815 I print_info: freq_scale_train = 1
0.00.182.815 I print_info: n_ctx_orig_yarn  = 8192
0.00.182.816 I print_info: rope_finetuned   = unknown
0.00.182.816 I print_info: ssm_d_conv       = 0
0.00.182.816 I print_info: ssm_d_inner      = 0
0.00.182.816 I print_info: ssm_d_state      = 0
0.00.182.817 I print_info: ssm_dt_rank      = 0
0.00.182.817 I print_info: ssm_dt_b_c_rms   = 0
0.00.182.817 I print_info: model type       = 1B
0.00.182.818 I print_info: model params     = 630.17 M
0.00.182.818 I print_info: general.name     = qwen2.5-0.5b-instruct
0.00.182.819 I print_info: vocab type       = BPE
0.00.182.819 I print_info: n_vocab          = 151936
0.00.182.819 I print_info: n_merges         = 151387
0.00.182.820 I print_info: BOS token        = 151643 '
'
0.00.182.820 I print_info: EOS token        = 151645 '
'
0.00.182.820 I print_info: EOT token        = 151645 '
'
0.00.182.820 I print_info: PAD token        = 151643 '
'
0.00.182.820 I print_info: LF token         = 198 'Ċ'
0.00.182.821 I print_info: FIM PRE token    = 151659 '
'
0.00.182.823 I print_info: FIM SUF token    = 151661 '
'
0.00.182.823 I print_info: FIM MID token    = 151660 '
'
0.00.182.823 I print_info: FIM PAD token    = 151662 '
'
0.00.182.823 I print_info: FIM REP token    = 151663 '
'
0.00.182.824 I print_info: FIM SEP token    = 151664 '
'
0.00.182.824 I print_info: EOG token        = 151643 '
'
0.00.182.824 I print_info: EOG token        = 151645 '
'
0.00.182.824 I print_info: EOG token        = 151662 '
'
0.00.182.825 I print_info: EOG token        = 151663 '
'
0.00.182.826 I print_info: EOG token        = 151664 '
'
0.00.182.826 I print_info: max token length = 256
0.00.186.816 I load_tensors: offloading 24 repeating layers to GPU
0.00.186.819 I load_tensors: offloading output layer to GPU
0.00.186.820 I load_tensors: offloaded 25/25 layers to GPU
0.00.186.821 I load_tensors:        Metal model buffer size =   942.43 MiB
0.00.186.821 I load_tensors:          CPU model buffer size =   259.66 MiB
0.00.471.272 I llama_init_from_model: n_seq_max     = 4
0.00.471.275 I llama_init_from_model: n_ctx         = 8192
0.00.471.276 I llama_init_from_model: n_ctx_per_seq = 2048
0.00.471.276 I llama_init_from_model: n_batch       = 2048
0.00.471.276 I llama_init_from_model: n_ubatch      = 512
0.00.471.276 I llama_init_from_model: flash_attn    = 0
0.00.471.277 I llama_init_from_model: freq_base     = 1000000.0
0.00.471.277 I llama_init_from_model: freq_scale    = 1
0.00.471.278 W llama_init_from_model: n_ctx_per_seq (2048) < n_ctx_train (8192) -- the full capacity of the model will not be utilized
0.00.471.279 I ggml_metal_init: allocating
0.00.471.309 I ggml_metal_init: found device: Apple M2 Max
0.00.471.315 I ggml_metal_init: picking default device: Apple M2 Max
0.00.471.937 I ggml_metal_init: using embedded metal library
0.00.474.525 I ggml_metal_init: GPU name:   Apple M2 Max
0.00.474.527 I ggml_metal_init: GPU family: MTLGPUFamilyApple8  (1008)
0.00.474.528 I ggml_metal_init: GPU family: MTLGPUFamilyCommon3 (3003)
0.00.474.528 I ggml_metal_init: GPU family: MTLGPUFamilyMetal3  (5001)
0.00.474.529 I ggml_metal_init: simdgroup reduction   = true
0.00.474.529 I ggml_metal_init: simdgroup matrix mul. = true
0.00.474.529 I ggml_metal_init: has residency sets    = false
0.00.474.529 I ggml_metal_init: has bfloat            = true
0.00.474.529 I ggml_metal_init: use bfloat            = true
0.00.474.530 I ggml_metal_init: hasUnifiedMemory      = true
0.00.474.535 I ggml_metal_init: recommendedMaxWorkingSetSize  = 22906.50 MB
-[MTLComputePipelineDescriptorInternal setComputeFunction:withType:]:692: failed assertion `computeFunction must not be nil.'

Duplicate issue #1220: Failed to run Qwen2.5-0.5B-GGUF with error computeFunction must not be nil.
Created: 2025-02-16T03:34:28Z
Failed to run qwen2.5-0.5b-FP16 with GGUF on M2Max with error below
2025-02-16T11:27:55+08:00 - gpustack.worker.downloaders - INFO - Retriving file lock
Downloading Model to directory: test/cache/model_scope/Qwen/Qwen2.5-0.5B-Instruct-GGUF
2025-02-16T11:27:56+08:00 - gpustack.worker.backends.llama_box - INFO - Starting llama-box server
0.00.001.686 I 
0.00.001.695 I arguments  : /Users/robin/anaconda3/envs/gpustack/lib/python3.10/site-packages/gpustack/third_party/bin/llama-box/llama-box --host 0.0.0.0 --embeddings --gpu-layers 25 --parallel 4 --ctx-size 8192 --port 40072 --model test/cache/model_scope/Qwen/Qwen2___5-0___5B-Instruct-GGUF/qwen2.5-0.5b-instruct-fp16.gguf --alias qwen2.5 --no-mmap --no-warmup
0.00.001.696 I version    : v0.0.117 (315b735)
0.00.001.696 I compiler   : Apple clang version 15.0.0 (clang-1500.1.0.2.5)
0.00.001.696 I target     : arm64-apple-darwin23.6.0
0.00.001.697 I vendor     : llama.cpp 27d135c9 (4598), stable-diffusion.cpp 102953d (203)
0.00.002.153 I system_info: n_threads = 8 (n_threads_batch = 8) / 12 | Metal : EMBED_LIBRARY = 1 | BF16 = 1 | CPU : NEON = 1 | ARM_FMA = 1 | FP16_VA = 1 | DOTPROD = 1 | LLAMAFILE = 1 | ACCELERATE = 1 | AARCH64_REPACK = 1 | 
0.00.002.155 I 
0.00.002.482 I srv                      main: listening, hostname = 0.0.0.0, port = 40072, n_threads = 6 + 2
0.00.003.761 I srv                      main: loading model
0.00.003.766 I srv                load_model: loading model 'test/cache/model_scope/Qwen/Qwen2___5-0___5B-Instruct-GGUF/qwen2.5-0.5b-instruct-fp16.gguf'
0.00.056.451 I llama_model_load_from_file_impl: using device Metal (Apple M2 Max) - 21845 MiB free
0.00.085.445 I llama_model_loader: loaded meta data with 26 key-value pairs and 291 tensors from test/cache/model_scope/Qwen/Qwen2___5-0___5B-Instruct-GGUF/qwen2.5-0.5b-instruct-fp16.gguf (version GGUF V3 (latest))
0.00.085.451 I llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
0.00.085.453 I llama_model_loader: - kv   0:                       general.architecture str              = qwen2
0.00.085.453 I llama_model_loader: - kv   1:                               general.type str              = model
0.00.085.454 I llama_model_loader: - kv   2:                               general.name str              = qwen2.5-0.5b-instruct
0.00.085.454 I llama_model_loader: - kv   3:                            general.version str              = v0.1
0.00.085.455 I llama_model_loader: - kv   4:                           general.finetune str              = qwen2.5-0.5b-instruct
0.00.085.455 I llama_model_loader: - kv   5:                         general.size_label str              = 630M
0.00.085.456 I llama_model_loader: - kv   6:                          qwen2.block_count u32              = 24
0.00.085.457 I llama_model_loader: - kv   7:                       qwen2.context_length u32              = 8192
0.00.085.457 I llama_model_loader: - kv   8:                     qwen2.embedding_length u32              = 896
0.00.085.458 I llama_model_loader: - kv   9:                  qwen2.feed_forward_length u32              = 4864
0.00.085.458 I llama_model_loader: - kv  10:                 qwen2.attention.head_count u32              = 14
0.00.085.458 I llama_model_loader: - kv  11:              qwen2.attention.head_count_kv u32              = 2
0.00.085.460 I llama_model_loader: - kv  12:                       qwen2.rope.freq_base f32              = 1000000.000000
0.00.085.461 I llama_model_loader: - kv  13:     qwen2.attention.layer_norm_rms_epsilon f32              = 0.000001
0.00.085.461 I llama_model_loader: - kv  14:                          general.file_type u32              = 1
0.00.085.461 I llama_model_loader: - kv  15:                       tokenizer.ggml.model str              = gpt2
0.00.085.461 I llama_model_loader: - kv  16:                         tokenizer.ggml.pre str              = qwen2
0.00.100.828 I llama_model_loader: - kv  17:                      tokenizer.ggml.tokens arr[str,151936]  = ["!", "\"", "#", "$", "%", "&", "'", ...
0.00.104.888 I llama_model_loader: - kv  18:                  tokenizer.ggml.token_type arr[i32,151936]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
0.00.120.296 I llama_model_loader: - kv  19:                      tokenizer.ggml.merges arr[str,151387]  = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
0.00.120.298 I llama_model_loader: - kv  20:                tokenizer.ggml.eos_token_id u32              = 151645
0.00.120.299 I llama_model_loader: - kv  21:            tokenizer.ggml.padding_token_id u32              = 151643
0.00.120.299 I llama_model_loader: - kv  22:                tokenizer.ggml.bos_token_id u32              = 151643
0.00.120.300 I llama_model_loader: - kv  23:               tokenizer.ggml.add_bos_token bool             = false
0.00.120.302 I llama_model_loader: - kv  24:                    tokenizer.chat_template str              = {%- if tools %}\n    {{- '
...
0.00.120.303 I llama_model_loader: - kv  25:               general.quantization_version u32              = 2
0.00.120.303 I llama_model_loader: - type  f32:  121 tensors
0.00.120.304 I llama_model_loader: - type  f16:  170 tensors
0.00.120.305 I print_info: file format = GGUF V3 (latest)
0.00.120.310 I print_info: file type   = F16
0.00.120.311 I print_info: file size   = 1.17 GiB (16.00 BPW) 
0.00.155.963 I load: special tokens cache size = 22
0.00.182.786 I load: token to piece cache size = 0.9310 MB
0.00.182.794 I print_info: arch             = qwen2
0.00.182.795 I print_info: vocab_only       = 0
0.00.182.795 I print_info: n_ctx_train      = 8192
0.00.182.797 I print_info: n_embd           = 896
0.00.182.798 I print_info: n_layer          = 24
0.00.182.804 I print_info: n_head           = 14
0.00.182.806 I print_info: n_head_kv        = 2
0.00.182.806 I print_info: n_rot            = 64
0.00.182.806 I print_info: n_swa            = 0
0.00.182.806 I print_info: n_embd_head_k    = 64
0.00.182.807 I print_info: n_embd_head_v    = 64
0.00.182.808 I print_info: n_gqa            = 7
0.00.182.809 I print_info: n_embd_k_gqa     = 128
0.00.182.810 I print_info: n_embd_v_gqa     = 128
0.00.182.811 I print_info: f_norm_eps       = 0.0e+00
0.00.182.811 I print_info: f_norm_rms_eps   = 1.0e-06
0.00.182.811 I print_info: f_clamp_kqv      = 0.0e+00
0.00.182.811 I print_info: f_max_alibi_bias = 0.0e+00
0.00.182.812 I print_info: f_logit_scale    = 0.0e+00
0.00.182.813 I print_info: n_ff             = 4864
0.00.182.813 I print_info: n_expert         = 0
0.00.182.813 I print_info: n_expert_used    = 0
0.00.182.814 I print_info: causal attn      = 1
0.00.182.814 I print_info: pooling type     = 0
0.00.182.814 I print_info: rope type        = 2
0.00.182.814 I print_info: rope scaling     = linear
0.00.182.815 I print_info: freq_base_train  = 1000000.0
0.00.182.815 I print_info: freq_scale_train = 1
0.00.182.815 I print_info: n_ctx_orig_yarn  = 8192
0.00.182.816 I print_info: rope_finetuned   = unknown
0.00.182.816 I print_info: ssm_d_conv       = 0
0.00.182.816 I print_info: ssm_d_inner      = 0
0.00.182.816 I print_info: ssm_d_state      = 0
0.00.182.817 I print_info: ssm_dt_rank      = 0
0.00.182.817 I print_info: ssm_dt_b_c_rms   = 0
0.00.182.817 I print_info: model type       = 1B
0.00.182.818 I print_info: model params     = 630.17 M
0.00.182.818 I print_info: general.name     = qwen2.5-0.5b-instruct
0.00.182.819 I print_info: vocab type       = BPE
0.00.182.819 I print_info: n_vocab          = 151936
0.00.182.819 I print_info: n_merges         = 151387
0.00.182.820 I print_info: BOS token        = 151643 '
'
0.00.182.820 I print_info: EOS token        = 151645 '
'
0.00.182.820 I print_info: EOT token        = 151645 '
'
0.00.182.820 I print_info: PAD token        = 151643 '
'
0.00.182.820 I print_info: LF token         = 198 'Ċ'
0.00.182.821 I print_info: FIM PRE token    = 151659 '
'
0.00.182.823 I print_info: FIM SUF token    = 151661 '
'
0.00.182.823 I print_info: FIM MID token    = 151660 '
'
0.00.182.823 I print_info: FIM PAD token    = 151662 '
'
0.00.182.823 I print_info: FIM REP token    = 151663 '
'
0.00.182.824 I print_info: FIM SEP token    = 151664 '
'
0.00.182.824 I print_info: EOG token        = 151643 '
'
0.00.182.824 I print_info: EOG token        = 151645 '
'
0.00.182.824 I print_info: EOG token        = 151662 '
'
0.00.182.825 I print_info: EOG token        = 151663 '
'
0.00.182.826 I print_info: EOG token        = 151664 '
'
0.00.182.826 I print_info: max token length = 256
0.00.186.816 I load_tensors: offloading 24 repeating layers to GPU
0.00.186.819 I load_tensors: offloading output layer to GPU
0.00.186.820 I load_tensors: offloaded 25/25 layers to GPU
0.00.186.821 I load_tensors:        Metal model buffer size =   942.43 MiB
0.00.186.821 I load_tensors:          CPU model buffer size =   259.66 MiB
0.00.471.272 I llama_init_from_model: n_seq_max     = 4
0.00.471.275 I llama_init_from_model: n_ctx         = 8192
0.00.471.276 I llama_init_from_model: n_ctx_per_seq = 2048
0.00.471.276 I llama_init_from_model: n_batch       = 2048
0.00.471.276 I llama_init_from_model: n_ubatch      = 512
0.00.471.276 I llama_init_from_model: flash_attn    = 0
0.00.471.277 I llama_init_from_model: freq_base     = 1000000.0
0.00.471.277 I llama_init_from_model: freq_scale    = 1
0.00.471.278 W llama_init_from_model: n_ctx_per_seq (2048) < n_ctx_train (8192) -- the full capacity of the model will not be utilized
0.00.471.279 I ggml_metal_init: allocating
0.00.471.309 I ggml_metal_init: found device: Apple M2 Max
0.00.471.315 I ggml_metal_init: picking default device: Apple M2 Max
0.00.471.937 I ggml_metal_init: using embedded metal library
0.00.474.525 I ggml_metal_init: GPU name:   Apple M2 Max
0.00.474.527 I ggml_metal_init: GPU family: MTLGPUFamilyApple8  (1008)
0.00.474.528 I ggml_metal_init: GPU family: MTLGPUFamilyCommon3 (3003)
0.00.474.528 I ggml_metal_init: GPU family: MTLGPUFamilyMetal3  (5001)
0.00.474.529 I ggml_metal_init: simdgroup reduction   = true
0.00.474.529 I ggml_metal_init: simdgroup matrix mul. = true
0.00.474.529 I ggml_metal_init: has residency sets    = false
0.00.474.529 I ggml_metal_init: has bfloat            = true
0.00.474.529 I ggml_metal_init: use bfloat            = true
0.00.474.530 I ggml_metal_init: hasUnifiedMemory      = true
0.00.474.535 I ggml_metal_init: recommendedMaxWorkingSetSize  = 22906.50 MB
-[MTLComputePipelineDescriptorInternal setComputeFunction:withType:]:692: failed assertion `computeFunction must not be nil.'
Environment

GPUStack version: v0.5.1
OS: Apple macOS
GPU: M2Max

Closing comment (2025-02-16T03:37:22Z): Close as duplicate of #1221