vllm - 💡(How to fix) Fix [Bug]: Step 3.5 Flash MTP failed to start in v0.19.0 [2 comments, 2 participants]

Official PRs (…)
ON THIS PAGE

Recommended Tools

×6

Utilities matched from this issue’s tags and category — try them while you read without losing context.

GitHub issue graph ai analysis

Paste a GitHub issue URL. We fetch that issue, discover linked issues from bodies/comments/timeline, collect linked pull requests, and produce a structured English report.

The report is written in English Markdown for sharing and archival.

Helpful · Quick feedback

Loading…
GitHub stats
vllm-project/vllm#40000Fetched 2026-04-17 08:27:48
View on GitHub
Comments
2
Participants
2
Timeline
16
Reactions
0
Author
Assignees
Timeline (top)
mentioned ×4subscribed ×4commented ×2labeled ×2

Error Message

vllm serve stepfun-ai/Step-3.5-Flash-FP8 --tensor-parallel-size 4 --reasoning-parser step3p5 --tool-call-parser step3p5 --enable-auto-tool-choice --trust-remote-code --disable-cascade-attn --enable-expert-parallel --hf-overrides '{"num_nextn_predict_layers": 1}' --speculative-config '{"method": "step3p5_mtp", "num_speculative_tokens": 1}' ....

Error

(Worker_TP0_EP0 pid=2116241) ERROR 04-16 14:12:42 [multiproc_executor.py:857] File "/home/akk/yh/uvenv/vllm0190/lib/python3.12/site-packages/vllm/model_executor/models/step3p5.py", line 449, in init (Worker_TP0_EP0 pid=2116241) ERROR 04-16 14:12:42 [multiproc_executor.py:857] and config.layer_types[layer_idx] (Worker_TP0_EP0 pid=2116241) ERROR 04-16 14:12:42 [multiproc_executor.py:857] ~~~~~~~~~~~~~~~~~~^^^^^^^^^^^ (Worker_TP0_EP0 pid=2116241) ERROR 04-16 14:12:42 [multiproc_executor.py:857] IndexError: list index out of range

Root Cause

Specifically, in Step3.5-Flash the model config construction has a few layers that're truncated as a result of update in #38247. Because Step3.5-Flash has the MTP block stored in the config as layers > 45 so the update removed the mtp_block's layer_types from the config construction. Causing the IndexError as shown below during server startup.

Fix Action

Fix / Workaround

============================== CPU Info

Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 52 bits physical, 57 bits virtual Byte Order: Little Endian CPU(s): 192 On-line CPU(s) list: 0-191 Vendor ID: AuthenticAMD Model name: AMD EPYC 9654 96-Core Processor CPU family: 25 Model: 17 Thread(s) per core: 1 Core(s) per socket: 96 Socket(s): 2 Stepping: 1 Frequency boost: enabled CPU max MHz: 3707.8120 CPU min MHz: 1500.0000 BogoMIPS: 4792.60 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp ibrs_enhanced vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local avx512_bf16 clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin cppc arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq la57 rdpid overflow_recov succor smca fsrm flush_l1d Virtualization: AMD-V L1d cache: 6 MiB (192 instances) L1i cache: 6 MiB (192 instances) L2 cache: 192 MiB (192 instances) L3 cache: 768 MiB (24 instances) NUMA node(s): 2 NUMA node0 CPU(s): 0-95 NUMA node1 CPU(s): 96-191 Vulnerability Gather data sampling: Not affected Vulnerability Itlb multihit: Not affected Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Not affected Vulnerability Reg file data sampling: Not affected Vulnerability Retbleed: Not affected Vulnerability Spec rstack overflow: Mitigation; safe RET Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected

Code Example

Collecting environment information...
==============================
        System Info
==============================
OS                           : Ubuntu 22.04.5 LTS (x86_64)
GCC version                  : (Ubuntu 11.4.0-1ubuntu1~22.04.2) 11.4.0
Clang version                : 20.0.0git (https://github.com/RadeonOpenCompute/llvm-project roc-7.0.0 25314 f4087f6b428f0e6f575ebac8a8a724dab123d06e)
CMake version                : version 3.31.10
Libc version                 : glibc-2.35

==============================
       PyTorch Info
==============================
PyTorch version              : 2.9.1+git8907517
Is debug build               : False
CUDA used to build PyTorch   : N/A
ROCM used to build PyTorch   : 7.0.51831-a3e329ad8
XPU used to build PyTorch    : N/A

==============================
      Python Environment
==============================
Python version               : 3.12.12 (main, Oct 10 2025, 08:52:57) [GCC 11.4.0] (64-bit runtime)
Python platform              : Linux-5.15.0-116-generic-x86_64-with-glibc2.35

==============================
       CUDA / GPU Info
==============================
Is CUDA available            : True
CUDA runtime version         : Could not collect
CUDA_MODULE_LOADING set to   :
GPU models and configuration :  (gfx942:sramecc+:xnack-)
Nvidia driver version        : Could not collect
cuDNN version                : Could not collect
HIP runtime version          : 7.0.51831
MIOpen runtime version       : 3.5.0
Is XNNPACK available         : True

==============================
          CPU Info
==============================
Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        52 bits physical, 57 bits virtual
Byte Order:                           Little Endian
CPU(s):                               192
On-line CPU(s) list:                  0-191
Vendor ID:                            AuthenticAMD
Model name:                           AMD EPYC 9654 96-Core Processor
CPU family:                           25
Model:                                17
Thread(s) per core:                   1
Core(s) per socket:                   96
Socket(s):                            2
Stepping:                             1
Frequency boost:                      enabled
CPU max MHz:                          3707.8120
CPU min MHz:                          1500.0000
BogoMIPS:                             4792.60
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp ibrs_enhanced vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local avx512_bf16 clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin cppc arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq la57 rdpid overflow_recov succor smca fsrm flush_l1d
Virtualization:                       AMD-V
L1d cache:                            6 MiB (192 instances)
L1i cache:                            6 MiB (192 instances)
L2 cache:                             192 MiB (192 instances)
L3 cache:                             768 MiB (24 instances)
NUMA node(s):                         2
NUMA node0 CPU(s):                    0-95
NUMA node1 CPU(s):                    96-191
Vulnerability Gather data sampling:   Not affected
Vulnerability Itlb multihit:          Not affected
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Not affected
Vulnerability Spec rstack overflow:   Mitigation; safe RET
Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Enhanced / Automatic IBRS; IBPB conditional; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

==============================
Versions of relevant libraries
==============================
[pip3] conch-triton-kernels==1.2.1
[pip3] numpy==2.1.3
[pip3] onnx==1.19.0
[pip3] onnx-ir==0.2.0
[pip3] onnxscript==0.6.2
[pip3] onnxslim==0.1.90
[pip3] pyzmq==27.1.0
[pip3] torch==2.9.1+git8907517
[pip3] torchaudio==2.9.0+eaa9e4e
[pip3] torchvision==0.24.1+d801a34
[pip3] transformers==4.57.6
[pip3] triton==3.4.0
[pip3] triton_kernels==1.0.0
[conda] Could not collect

==============================
         vLLM Info
==============================
ROCM Version                 : 7.0.51831-a3e329ad8
vLLM Version                 : 0.18.1
vLLM Build Flags:
  CUDA Archs: Not Set; ROCm: Disabled; XPU: Disabled
GPU Topology:
  ============================ ROCm System Management Interface ============================
================================ Weight between two GPUs =================================
       GPU0         GPU1         GPU2         GPU3         GPU4         GPU5         GPU6         GPU7
GPU0   0            15           15           15           15           15           15           15
GPU1   15           0            15           15           15           15           15           15
GPU2   15           15           0            15           15           15           15           15
GPU3   15           15           15           0            15           15           15           15
GPU4   15           15           15           15           0            15           15           15
GPU5   15           15           15           15           15           0            15           15
GPU6   15           15           15           15           15           15           0            15
GPU7   15           15           15           15           15           15           15           0

================================= Hops between two GPUs ==================================
       GPU0         GPU1         GPU2         GPU3         GPU4         GPU5         GPU6         GPU7
GPU0   0            1            1            1            1            1            1            1
GPU1   1            0            1            1            1            1            1            1
GPU2   1            1            0            1            1            1            1            1
GPU3   1            1            1            0            1            1            1            1
GPU4   1            1            1            1            0            1            1            1
GPU5   1            1            1            1            1            0            1            1
GPU6   1            1            1            1            1            1            0            1
GPU7   1            1            1            1            1            1            1            0

=============================== Link Type between two GPUs ===============================
       GPU0         GPU1         GPU2         GPU3         GPU4         GPU5         GPU6         GPU7
GPU0   0            XGMI         XGMI         XGMI         XGMI         XGMI         XGMI         XGMI
GPU1   XGMI         0            XGMI         XGMI         XGMI         XGMI         XGMI         XGMI
GPU2   XGMI         XGMI         0            XGMI         XGMI         XGMI         XGMI         XGMI
GPU3   XGMI         XGMI         XGMI         0            XGMI         XGMI         XGMI         XGMI
GPU4   XGMI         XGMI         XGMI         XGMI         0            XGMI         XGMI         XGMI
GPU5   XGMI         XGMI         XGMI         XGMI         XGMI         0            XGMI         XGMI
GPU6   XGMI         XGMI         XGMI         XGMI         XGMI         XGMI         0            XGMI
GPU7   XGMI         XGMI         XGMI         XGMI         XGMI         XGMI         XGMI         0

======================================= Numa Nodes =======================================
GPU[0]          : (Topology) Numa Node: 0
GPU[0]          : (Topology) Numa Affinity: 0
GPU[1]          : (Topology) Numa Node: 0
GPU[1]          : (Topology) Numa Affinity: 0
GPU[2]          : (Topology) Numa Node: 0
GPU[2]          : (Topology) Numa Affinity: 0
GPU[3]          : (Topology) Numa Node: 0
GPU[3]          : (Topology) Numa Affinity: 0
GPU[4]          : (Topology) Numa Node: 1
GPU[4]          : (Topology) Numa Affinity: 1
GPU[5]          : (Topology) Numa Node: 1
GPU[5]          : (Topology) Numa Affinity: 1
GPU[6]          : (Topology) Numa Node: 1
GPU[6]          : (Topology) Numa Affinity: 1
GPU[7]          : (Topology) Numa Node: 1
GPU[7]          : (Topology) Numa Affinity: 1
================================== End of ROCm SMI Log ===================================

==============================
     Environment Variables
==============================
PYTORCH_ROCM_ARCH=gfx90a;gfx942;gfx950;gfx1100;gfx1101;gfx1200;gfx1201;gfx1150;gfx1151
LD_LIBRARY_PATH=/opt/rocm/lib:/usr/local/lib:
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1

---

"num_hidden_layers": 45,
        ...
        "model.layers.45.mtp_block.self_attn.g_proj",
        "model.layers.45.mtp_block.self_attn.qkv_proj",
        "model.layers.45.mtp_block.self_attn.o_proj",
        "model.layers.45.mtp_block.mlp.gate_up_proj",
        "model.layers.45.mtp_block.mlp.down_proj",
        ...

---

vllm serve stepfun-ai/Step-3.5-Flash-FP8     --tensor-parallel-size 4     --reasoning-parser step3p5     --tool-call-parser step3p5     --enable-auto-tool-choice     --trust-remote-code  --disable-cascade-attn --enable-expert-parallel --hf-overrides '{"num_nextn_predict_layers": 1}' --speculative-config '{"method": "step3p5_mtp", "num_speculative_tokens": 1}'
....
# Error
(Worker_TP0_EP0 pid=2116241) ERROR 04-16 14:12:42 [multiproc_executor.py:857]   File "/home/akk/yh/uvenv/vllm0190/lib/python3.12/site-packages/vllm/model_executor/models/step3p5.py", line 449, in __init__
(Worker_TP0_EP0 pid=2116241) ERROR 04-16 14:12:42 [multiproc_executor.py:857]     and config.layer_types[layer_idx]
(Worker_TP0_EP0 pid=2116241) ERROR 04-16 14:12:42 [multiproc_executor.py:857]         ~~~~~~~~~~~~~~~~~~^^^^^^^^^^^
(Worker_TP0_EP0 pid=2116241) ERROR 04-16 14:12:42 [multiproc_executor.py:857] IndexError: list index out of range
RAW_BUFFERClick to expand / collapse

Your current environment

<details> <summary>The output of <code>python collect_env.py</code></summary>
Collecting environment information...
==============================
        System Info
==============================
OS                           : Ubuntu 22.04.5 LTS (x86_64)
GCC version                  : (Ubuntu 11.4.0-1ubuntu1~22.04.2) 11.4.0
Clang version                : 20.0.0git (https://github.com/RadeonOpenCompute/llvm-project roc-7.0.0 25314 f4087f6b428f0e6f575ebac8a8a724dab123d06e)
CMake version                : version 3.31.10
Libc version                 : glibc-2.35

==============================
       PyTorch Info
==============================
PyTorch version              : 2.9.1+git8907517
Is debug build               : False
CUDA used to build PyTorch   : N/A
ROCM used to build PyTorch   : 7.0.51831-a3e329ad8
XPU used to build PyTorch    : N/A

==============================
      Python Environment
==============================
Python version               : 3.12.12 (main, Oct 10 2025, 08:52:57) [GCC 11.4.0] (64-bit runtime)
Python platform              : Linux-5.15.0-116-generic-x86_64-with-glibc2.35

==============================
       CUDA / GPU Info
==============================
Is CUDA available            : True
CUDA runtime version         : Could not collect
CUDA_MODULE_LOADING set to   :
GPU models and configuration :  (gfx942:sramecc+:xnack-)
Nvidia driver version        : Could not collect
cuDNN version                : Could not collect
HIP runtime version          : 7.0.51831
MIOpen runtime version       : 3.5.0
Is XNNPACK available         : True

==============================
          CPU Info
==============================
Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        52 bits physical, 57 bits virtual
Byte Order:                           Little Endian
CPU(s):                               192
On-line CPU(s) list:                  0-191
Vendor ID:                            AuthenticAMD
Model name:                           AMD EPYC 9654 96-Core Processor
CPU family:                           25
Model:                                17
Thread(s) per core:                   1
Core(s) per socket:                   96
Socket(s):                            2
Stepping:                             1
Frequency boost:                      enabled
CPU max MHz:                          3707.8120
CPU min MHz:                          1500.0000
BogoMIPS:                             4792.60
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp ibrs_enhanced vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local avx512_bf16 clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin cppc arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq la57 rdpid overflow_recov succor smca fsrm flush_l1d
Virtualization:                       AMD-V
L1d cache:                            6 MiB (192 instances)
L1i cache:                            6 MiB (192 instances)
L2 cache:                             192 MiB (192 instances)
L3 cache:                             768 MiB (24 instances)
NUMA node(s):                         2
NUMA node0 CPU(s):                    0-95
NUMA node1 CPU(s):                    96-191
Vulnerability Gather data sampling:   Not affected
Vulnerability Itlb multihit:          Not affected
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Not affected
Vulnerability Spec rstack overflow:   Mitigation; safe RET
Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Enhanced / Automatic IBRS; IBPB conditional; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

==============================
Versions of relevant libraries
==============================
[pip3] conch-triton-kernels==1.2.1
[pip3] numpy==2.1.3
[pip3] onnx==1.19.0
[pip3] onnx-ir==0.2.0
[pip3] onnxscript==0.6.2
[pip3] onnxslim==0.1.90
[pip3] pyzmq==27.1.0
[pip3] torch==2.9.1+git8907517
[pip3] torchaudio==2.9.0+eaa9e4e
[pip3] torchvision==0.24.1+d801a34
[pip3] transformers==4.57.6
[pip3] triton==3.4.0
[pip3] triton_kernels==1.0.0
[conda] Could not collect

==============================
         vLLM Info
==============================
ROCM Version                 : 7.0.51831-a3e329ad8
vLLM Version                 : 0.18.1
vLLM Build Flags:
  CUDA Archs: Not Set; ROCm: Disabled; XPU: Disabled
GPU Topology:
  ============================ ROCm System Management Interface ============================
================================ Weight between two GPUs =================================
       GPU0         GPU1         GPU2         GPU3         GPU4         GPU5         GPU6         GPU7
GPU0   0            15           15           15           15           15           15           15
GPU1   15           0            15           15           15           15           15           15
GPU2   15           15           0            15           15           15           15           15
GPU3   15           15           15           0            15           15           15           15
GPU4   15           15           15           15           0            15           15           15
GPU5   15           15           15           15           15           0            15           15
GPU6   15           15           15           15           15           15           0            15
GPU7   15           15           15           15           15           15           15           0

================================= Hops between two GPUs ==================================
       GPU0         GPU1         GPU2         GPU3         GPU4         GPU5         GPU6         GPU7
GPU0   0            1            1            1            1            1            1            1
GPU1   1            0            1            1            1            1            1            1
GPU2   1            1            0            1            1            1            1            1
GPU3   1            1            1            0            1            1            1            1
GPU4   1            1            1            1            0            1            1            1
GPU5   1            1            1            1            1            0            1            1
GPU6   1            1            1            1            1            1            0            1
GPU7   1            1            1            1            1            1            1            0

=============================== Link Type between two GPUs ===============================
       GPU0         GPU1         GPU2         GPU3         GPU4         GPU5         GPU6         GPU7
GPU0   0            XGMI         XGMI         XGMI         XGMI         XGMI         XGMI         XGMI
GPU1   XGMI         0            XGMI         XGMI         XGMI         XGMI         XGMI         XGMI
GPU2   XGMI         XGMI         0            XGMI         XGMI         XGMI         XGMI         XGMI
GPU3   XGMI         XGMI         XGMI         0            XGMI         XGMI         XGMI         XGMI
GPU4   XGMI         XGMI         XGMI         XGMI         0            XGMI         XGMI         XGMI
GPU5   XGMI         XGMI         XGMI         XGMI         XGMI         0            XGMI         XGMI
GPU6   XGMI         XGMI         XGMI         XGMI         XGMI         XGMI         0            XGMI
GPU7   XGMI         XGMI         XGMI         XGMI         XGMI         XGMI         XGMI         0

======================================= Numa Nodes =======================================
GPU[0]          : (Topology) Numa Node: 0
GPU[0]          : (Topology) Numa Affinity: 0
GPU[1]          : (Topology) Numa Node: 0
GPU[1]          : (Topology) Numa Affinity: 0
GPU[2]          : (Topology) Numa Node: 0
GPU[2]          : (Topology) Numa Affinity: 0
GPU[3]          : (Topology) Numa Node: 0
GPU[3]          : (Topology) Numa Affinity: 0
GPU[4]          : (Topology) Numa Node: 1
GPU[4]          : (Topology) Numa Affinity: 1
GPU[5]          : (Topology) Numa Node: 1
GPU[5]          : (Topology) Numa Affinity: 1
GPU[6]          : (Topology) Numa Node: 1
GPU[6]          : (Topology) Numa Affinity: 1
GPU[7]          : (Topology) Numa Node: 1
GPU[7]          : (Topology) Numa Affinity: 1
================================== End of ROCm SMI Log ===================================

==============================
     Environment Variables
==============================
PYTORCH_ROCM_ARCH=gfx90a;gfx942;gfx950;gfx1100;gfx1101;gfx1200;gfx1201;gfx1150;gfx1151
LD_LIBRARY_PATH=/opt/rocm/lib:/usr/local/lib:
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
</details>

🐛 Describe the bug

In v0.19.0 Step3.5-Flash MTP failed to start due to incorrect model config construction.

Specifically, in Step3.5-Flash the model config construction has a few layers that're truncated as a result of update in #38247. Because Step3.5-Flash has the MTP block stored in the config as layers > 45 so the update removed the mtp_block's layer_types from the config construction. Causing the IndexError as shown below during server startup.

config.json:

  "num_hidden_layers": 45,
        ...
        "model.layers.45.mtp_block.self_attn.g_proj",
        "model.layers.45.mtp_block.self_attn.qkv_proj",
        "model.layers.45.mtp_block.self_attn.o_proj",
        "model.layers.45.mtp_block.mlp.gate_up_proj",
        "model.layers.45.mtp_block.mlp.down_proj",
        ...

Startup command + error:

vllm serve stepfun-ai/Step-3.5-Flash-FP8     --tensor-parallel-size 4     --reasoning-parser step3p5     --tool-call-parser step3p5     --enable-auto-tool-choice     --trust-remote-code  --disable-cascade-attn --enable-expert-parallel --hf-overrides '{"num_nextn_predict_layers": 1}' --speculative-config '{"method": "step3p5_mtp", "num_speculative_tokens": 1}'
....
# Error
(Worker_TP0_EP0 pid=2116241) ERROR 04-16 14:12:42 [multiproc_executor.py:857]   File "/home/akk/yh/uvenv/vllm0190/lib/python3.12/site-packages/vllm/model_executor/models/step3p5.py", line 449, in __init__
(Worker_TP0_EP0 pid=2116241) ERROR 04-16 14:12:42 [multiproc_executor.py:857]     and config.layer_types[layer_idx]
(Worker_TP0_EP0 pid=2116241) ERROR 04-16 14:12:42 [multiproc_executor.py:857]         ~~~~~~~~~~~~~~~~~~^^^^^^^^^^^
(Worker_TP0_EP0 pid=2116241) ERROR 04-16 14:12:42 [multiproc_executor.py:857] IndexError: list index out of range

In v0.18.1 (before the PR), it's working fine

Before submitting a new issue...

  • Make sure you already searched for relevant issues, and asked the chatbot living at the bottom right corner of the documentation page, which can answer lots of frequently asked questions.

extent analysis

TL;DR

The most likely fix is to update the model configuration to include the missing layer types for the MTP block in the config.json file.

Guidance

  • Review the config.json file and update the num_hidden_layers value to include the layers beyond 45 that are required for the MTP block.
  • Verify that the layer_types list in the model configuration includes the necessary types for the MTP block, such as mtp_block.
  • Check the step3p5.py file, specifically line 449, to ensure that the layer_idx is within the valid range of the layer_types list.
  • Consider reverting the changes made in PR #38247 or updating the model configuration to accommodate the changes.

Example

No code snippet is provided as the issue is related to configuration and not code.

Notes

The issue seems to be specific to the Step3.5-Flash model and the changes made in PR #38247. The fix may require updating the model configuration or reverting the changes made in the PR.

Recommendation

Apply a workaround by updating the config.json file to include the missing layer types for the MTP block. This should allow the model to start without errors.

Vote matrix · Quick signals

Works
Did the solution work? Tap to confirm.
Easy Fix
Was it a quick fix?
Time Saver
Did it save you time?
Blocking
Was it severely blocking?
Common Issue
Are others likely hitting this too?
Flaky / Intermittent
Is it intermittent?
Verified / Reproducible
Can you reproduce it reliably?
Loading…

Still need to ship something?

×6

Another batch ranked right after the header list — different links, same matching logic.

Back to top recommendations

TRENDING