vllm - ✅(Solved) Fix [Bug]: pip install 0.17 fails with CXXABI_1.3.15 not found [2 pull requests, 6 comments, 4 participants]

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vllm-project/vllm#36530Fetched 2026-04-08 00:36:23
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Error Message

(vllm) [jlquinn@login5 synth]$ python -c "from vllm import LLM" INFO 03-09 18:42:41 [importing.py:44] Triton is installed but 0 active driver(s) found (expected 1). Disabling Triton to prevent runtime errors. INFO 03-09 18:42:41 [importing.py:68] Triton not installed or not compatible; certain GPU-related functions will not be available. Traceback (most recent call last): File "<string>", line 1, in <module> File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/init.py", line 70, in getattr module = import_module(module_name, package) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/importlib/init.py", line 90, in import_module return _bootstrap._gcd_import(name[level:], package, level) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/entrypoints/llm.py", line 48, in <module> from vllm.entrypoints.pooling.io_processor_factories import init_pooling_io_processors File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/entrypoints/pooling/io_processor_factories.py", line 7, in <module> from vllm.entrypoints.pooling.base.io_processor import PoolingIOProcessor File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/entrypoints/pooling/base/io_processor.py", line 16, in <module> from vllm.entrypoints.openai.engine.serving import RendererChatRequest, RendererRequest File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 24, in <module> from vllm.engine.protocol import EngineClient File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/engine/protocol.py", line 23, in <module> from vllm.v1.engine.input_processor import InputProcessor File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/v1/engine/input_processor.py", line 20, in <module> from vllm.multimodal.encoder_budget import MultiModalBudget File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/multimodal/encoder_budget.py", line 10, in <module> from vllm.v1.core.encoder_cache_manager import compute_mm_encoder_budget File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/v1/core/encoder_cache_manager.py", line 9, in <module> from vllm.v1.request import Request File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/v1/request.py", line 24, in <module> from vllm.v1.structured_output.request import StructuredOutputRequest File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/v1/structured_output/init.py", line 19, in <module> from vllm.v1.structured_output.backend_xgrammar import XgrammarBackend File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/v1/structured_output/backend_xgrammar.py", line 20, in <module> from vllm.v1.structured_output.utils import ( File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/v1/structured_output/utils.py", line 15, in <module> from diskcache import Cache File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/diskcache/init.py", line 8, in <module> from .core import ( File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/diskcache/core.py", line 14, in <module> import sqlite3 File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/sqlite3/init.py", line 57, in <module> from sqlite3.dbapi2 import * File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/sqlite3/dbapi2.py", line 27, in <module> from _sqlite3 import * ImportError: /lib64/libstdc++.so.6: version `CXXABI_1.3.15' not found (required by /proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/lib-dynload/../.././libicui18n.so.78)

Fix Action

Fix / Workaround

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

Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 46 bits physical, 57 bits virtual Byte Order: Little Endian CPU(s): 128 On-line CPU(s) list: 0-127 Vendor ID: GenuineIntel Model name: Intel(R) Xeon(R) Gold 6448Y CPU family: 6 Model: 143 Thread(s) per core: 2 Core(s) per socket: 32 Socket(s): 2 Stepping: 8 CPU(s) scaling MHz: 71% CPU max MHz: 4100.0000 CPU min MHz: 800.0000 BogoMIPS: 4200.00 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req hfi vnmi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities Virtualization: VT-x L1d cache: 3 MiB (64 instances) L1i cache: 2 MiB (64 instances) L2 cache: 128 MiB (64 instances) L3 cache: 120 MiB (2 instances) NUMA node(s): 2 NUMA node0 CPU(s): 0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58,60,62,64,66,68,70,72,74,76,78,80,82,84,86,88,90,92,94,96,98,100,102,104,106,108,110,112,114,116,118,120,122,124,126 NUMA node1 CPU(s): 1,3,5,7,9,11,13,15,17,19,21,23,25,27,29,31,33,35,37,39,41,43,45,47,49,51,53,55,57,59,61,63,65,67,69,71,73,75,77,79,81,83,85,87,89,91,93,95,97,99,101,103,105,107,109,111,113,115,117,119,121,123,125,127 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: Not affected Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected

PR fix notes

PR #62110: [docs][llm] Add C/C++ binaries incompatibility workaround

Description (problem / solution / changelog)

Description

Ray 2.55 is about to be released with vLLM 0.18.0, and there could be C/C++ libraries incompatibilities when users install ray[llm] in their conda environments. We want to make sure that the mitigation is captured in docs.

Added instructions under Ray Data LLM and Ray Serve LLM troubleshooting section:

  • Ray Data LLM
<img width="1483" height="627" alt="Screenshot 2026-03-26 at 2 11 27 PM" src="https://github.com/user-attachments/assets/b2a4b9f8-f40f-4d0e-9fc3-ca54a8aed8e3" />
  • Ray Serve LLM
<img width="1485" height="387" alt="Screenshot 2026-03-26 at 2 12 16 PM" src="https://github.com/user-attachments/assets/434d197e-e86a-4113-84c4-72525198ea83" />

Additional information

Optional: Add implementation details, API changes, usage examples, screenshots, etc.

Changed files

  • .vale/styles/config/vocabularies/Data/accept.txt (modified, +1/-0)
  • doc/source/data/working-with-llms.rst (modified, +15/-0)
  • doc/source/serve/llm/troubleshooting.md (modified, +12/-0)

PR #38649: [Bugfix] Lazy import diskcache to avoid sqlite3/libstdc++ ImportError at startup

Description (problem / solution / changelog)

Purpose

Lazy import diskcache to avoid sqlite3/libstdc++ ImportError at startup.

Move from diskcache import Cache from top-level to inside get_outlines_cache() so environments missing CXXABI_1.3.15 no longer crash on import when the outlines cache is unused.

This import chain was introduced between 0.16.0 and 0.17.0.

In vLLM 0.16.0, XgrammarBackend was imported lazily inside a method (grammar_init), so the diskcache → sqlite3 → ICU → libstdc++ chain was only triggered when actually using structured output.

In vLLM 0.17.0, XgrammarBackend is imported at the top level of init.py, meaning import vllm now eagerly loads the entire chain: init.py → backend_xgrammar.py → utils.py → diskcache → sqlite3 → _sqlite3.so → libicui18n.so.78 → libstdc++ (CXXABI_1.3.15).

Resolves https://github.com/vllm-project/vllm/issues/36530.

Test Plan

Repro script: https://github.com/ray-project/ray/blob/master/release/llm_tests/serve/test_llm_serve_correctness.py

Test Result

Prior to this PR: <img width="1002" height="351" alt="Screenshot 2026-03-20 at 4 44 45 PM" src="https://github.com/user-attachments/assets/6641c774-3e55-4020-9d49-8435a12bec7c" />

After this PR: No libstdc++ ImportError observed, and test completes successfully.


<details> <summary> Essential Elements of an Effective PR Description Checklist </summary>
  • The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
  • The test plan, such as providing test command.
  • The test results, such as pasting the results comparison before and after, or e2e results
  • (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.
  • (Optional) Release notes update. If your change is user facing, please update the release notes draft in the Google Doc.
</details>

Changed files

  • vllm/v1/structured_output/utils.py (modified, +2/-1)

Code Example

(vllm) [jlquinn@login5 synth]$ python collect_env.py
Collecting environment information...
==============================
        System Info
==============================
OS                           : Red Hat Enterprise Linux 9.5 (Plow) (x86_64)
GCC version                  : (GCC) 11.5.0 20240719 (Red Hat 11.5.0-2)
Clang version                : Could not collect
CMake version                : Could not collect
Libc version                 : glibc-2.34

==============================
       PyTorch Info
==============================
PyTorch version              : 2.10.0+cu129
Is debug build               : False
CUDA used to build PyTorch   : 12.9
ROCM used to build PyTorch   : N/A

==============================
      Python Environment
==============================
Python version               : 3.12.12 | packaged by conda-forge | (main, Jan 26 2026, 23:51:32) [GCC 14.3.0] (64-bit runtime)
Python platform              : Linux-5.14.0-503.11.1.el9_5.x86_64-x86_64-with-glibc2.34

==============================
       CUDA / GPU Info
==============================
Is CUDA available            : False
CUDA runtime version         : No CUDA
CUDA_MODULE_LOADING set to   : N/A
GPU models and configuration : No CUDA
Nvidia driver version        : No CUDA
cuDNN version                : No CUDA
HIP runtime version          : N/A
MIOpen runtime version       : N/A
Is XNNPACK available         : True

==============================
          CPU Info
==============================
Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        46 bits physical, 57 bits virtual
Byte Order:                           Little Endian
CPU(s):                               128
On-line CPU(s) list:                  0-127
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Xeon(R) Gold 6448Y
CPU family:                           6
Model:                                143
Thread(s) per core:                   2
Core(s) per socket:                   32
Socket(s):                            2
Stepping:                             8
CPU(s) scaling MHz:                   71%
CPU max MHz:                          4100.0000
CPU min MHz:                          800.0000
BogoMIPS:                             4200.00
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req hfi vnmi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities
Virtualization:                       VT-x
L1d cache:                            3 MiB (64 instances)
L1i cache:                            2 MiB (64 instances)
L2 cache:                             128 MiB (64 instances)
L3 cache:                             120 MiB (2 instances)
NUMA node(s):                         2
NUMA node0 CPU(s):                    0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58,60,62,64,66,68,70,72,74,76,78,80,82,84,86,88,90,92,94,96,98,100,102,104,106,108,110,112,114,116,118,120,122,124,126
NUMA node1 CPU(s):                    1,3,5,7,9,11,13,15,17,19,21,23,25,27,29,31,33,35,37,39,41,43,45,47,49,51,53,55,57,59,61,63,65,67,69,71,73,75,77,79,81,83,85,87,89,91,93,95,97,99,101,103,105,107,109,111,113,115,117,119,121,123,125,127
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:   Not affected
Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

==============================
Versions of relevant libraries
==============================
[pip3] flashinfer-python==0.6.4
[pip3] numpy==2.2.6
[pip3] nvidia-cublas-cu12==12.9.1.4
[pip3] nvidia-cuda-cupti-cu12==12.9.79
[pip3] nvidia-cuda-nvrtc-cu12==12.9.86
[pip3] nvidia-cuda-runtime-cu12==12.9.79
[pip3] nvidia-cudnn-cu12==9.10.2.21
[pip3] nvidia-cudnn-frontend==1.18.0
[pip3] nvidia-cufft-cu12==11.4.1.4
[pip3] nvidia-cufile-cu12==1.14.1.1
[pip3] nvidia-curand-cu12==10.3.10.19
[pip3] nvidia-cusolver-cu12==11.7.5.82
[pip3] nvidia-cusparse-cu12==12.5.10.65
[pip3] nvidia-cusparselt-cu12==0.7.1
[pip3] nvidia-cutlass-dsl==4.4.1
[pip3] nvidia-cutlass-dsl-libs-base==4.4.1
[pip3] nvidia-ml-py==13.590.48
[pip3] nvidia-nccl-cu12==2.27.5
[pip3] nvidia-nvjitlink-cu12==12.9.86
[pip3] nvidia-nvshmem-cu12==3.4.5
[pip3] nvidia-nvtx-cu12==12.9.79
[pip3] pyzmq==27.1.0
[pip3] sentence-transformers==5.2.3
[pip3] torch==2.10.0+cu129
[pip3] torch_c_dlpack_ext==0.1.5
[pip3] torchaudio==2.10.0+cu129
[pip3] torchvision==0.25.0+cu129
[pip3] transformers==4.57.6
[pip3] triton==3.6.0
[conda] flashinfer-python                           0.6.4            pypi_0                pypi
[conda] numpy                                       2.2.6            pypi_0                pypi
[conda] nvidia-cublas-cu12                          12.9.1.4         pypi_0                pypi
[conda] nvidia-cuda-cupti-cu12                      12.9.79          pypi_0                pypi
[conda] nvidia-cuda-nvrtc-cu12                      12.9.86          pypi_0                pypi
[conda] nvidia-cuda-runtime-cu12                    12.9.79          pypi_0                pypi
[conda] nvidia-cudnn-cu12                           9.10.2.21        pypi_0                pypi
[conda] nvidia-cudnn-frontend                       1.18.0           pypi_0                pypi
[conda] nvidia-cufft-cu12                           11.4.1.4         pypi_0                pypi
[conda] nvidia-cufile-cu12                          1.14.1.1         pypi_0                pypi
[conda] nvidia-curand-cu12                          10.3.10.19       pypi_0                pypi
[conda] nvidia-cusolver-cu12                        11.7.5.82        pypi_0                pypi
[conda] nvidia-cusparse-cu12                        12.5.10.65       pypi_0                pypi
[conda] nvidia-cusparselt-cu12                      0.7.1            pypi_0                pypi
[conda] nvidia-cutlass-dsl                          4.4.1            pypi_0                pypi
[conda] nvidia-cutlass-dsl-libs-base                4.4.1            pypi_0                pypi
[conda] nvidia-ml-py                                13.590.48        pypi_0                pypi
[conda] nvidia-nccl-cu12                            2.27.5           pypi_0                pypi
[conda] nvidia-nvjitlink-cu12                       12.9.86          pypi_0                pypi
[conda] nvidia-nvshmem-cu12                         3.4.5            pypi_0                pypi
[conda] nvidia-nvtx-cu12                            12.9.79          pypi_0                pypi
[conda] pyzmq                                       27.1.0           pypi_0                pypi
[conda] sentence-transformers                       5.2.3            pypi_0                pypi
[conda] torch                                       2.10.0+cu129     pypi_0                pypi
[conda] torch-c-dlpack-ext                          0.1.5            pypi_0                pypi
[conda] torchaudio                                  2.10.0+cu129     pypi_0                pypi
[conda] torchvision                                 0.25.0+cu129     pypi_0                pypi
[conda] transformers                                4.57.6           pypi_0                pypi
[conda] triton                                      3.6.0            pypi_0                pypi

==============================
         vLLM Info
==============================
ROCM Version                 : Could not collect
vLLM Version                 : 0.17.0
vLLM Build Flags:
  CUDA Archs: Not Set; ROCm: Disabled
GPU Topology:
  Could not collect

==============================
     Environment Variables
==============================
LD_LIBRARY_PATH=/opt/share/ETELSFSH/10.1/linux4.18-glibc2.28-x86_64/lib
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
TORCHINDUCTOR_CACHE_DIR=/tmp/torchinductor_jlquinn

---

(vllm) [jlquinn@login5 synth]$ python -c "from vllm import LLM"
INFO 03-09 18:42:41 [importing.py:44] Triton is installed but 0 active driver(s) found (expected 1). Disabling Triton to prevent runtime errors.
INFO 03-09 18:42:41 [importing.py:68] Triton not installed or not compatible; certain GPU-related functions will not be available.
Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/__init__.py", line 70, in __getattr__
    module = import_module(module_name, __package__)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/importlib/__init__.py", line 90, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/entrypoints/llm.py", line 48, in <module>
    from vllm.entrypoints.pooling.io_processor_factories import init_pooling_io_processors
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/entrypoints/pooling/io_processor_factories.py", line 7, in <module>
    from vllm.entrypoints.pooling.base.io_processor import PoolingIOProcessor
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/entrypoints/pooling/base/io_processor.py", line 16, in <module>
    from vllm.entrypoints.openai.engine.serving import RendererChatRequest, RendererRequest
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 24, in <module>
    from vllm.engine.protocol import EngineClient
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/engine/protocol.py", line 23, in <module>
    from vllm.v1.engine.input_processor import InputProcessor
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/v1/engine/input_processor.py", line 20, in <module>
    from vllm.multimodal.encoder_budget import MultiModalBudget
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/multimodal/encoder_budget.py", line 10, in <module>
    from vllm.v1.core.encoder_cache_manager import compute_mm_encoder_budget
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/v1/core/encoder_cache_manager.py", line 9, in <module>
    from vllm.v1.request import Request
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/v1/request.py", line 24, in <module>
    from vllm.v1.structured_output.request import StructuredOutputRequest
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/v1/structured_output/__init__.py", line 19, in <module>
    from vllm.v1.structured_output.backend_xgrammar import XgrammarBackend
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/v1/structured_output/backend_xgrammar.py", line 20, in <module>
    from vllm.v1.structured_output.utils import (
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/v1/structured_output/utils.py", line 15, in <module>
    from diskcache import Cache
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/diskcache/__init__.py", line 8, in <module>
    from .core import (
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/diskcache/core.py", line 14, in <module>
    import sqlite3
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/sqlite3/__init__.py", line 57, in <module>
    from sqlite3.dbapi2 import *
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/sqlite3/dbapi2.py", line 27, in <module>
    from _sqlite3 import *
ImportError: /lib64/libstdc++.so.6: version `CXXABI_1.3.15' not found (required by /proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/lib-dynload/../.././libicui18n.so.78)
RAW_BUFFERClick to expand / collapse

Your current environment

<details> <summary>The output of <code>python collect_env.py</code></summary>
(vllm) [jlquinn@login5 synth]$ python collect_env.py
Collecting environment information...
==============================
        System Info
==============================
OS                           : Red Hat Enterprise Linux 9.5 (Plow) (x86_64)
GCC version                  : (GCC) 11.5.0 20240719 (Red Hat 11.5.0-2)
Clang version                : Could not collect
CMake version                : Could not collect
Libc version                 : glibc-2.34

==============================
       PyTorch Info
==============================
PyTorch version              : 2.10.0+cu129
Is debug build               : False
CUDA used to build PyTorch   : 12.9
ROCM used to build PyTorch   : N/A

==============================
      Python Environment
==============================
Python version               : 3.12.12 | packaged by conda-forge | (main, Jan 26 2026, 23:51:32) [GCC 14.3.0] (64-bit runtime)
Python platform              : Linux-5.14.0-503.11.1.el9_5.x86_64-x86_64-with-glibc2.34

==============================
       CUDA / GPU Info
==============================
Is CUDA available            : False
CUDA runtime version         : No CUDA
CUDA_MODULE_LOADING set to   : N/A
GPU models and configuration : No CUDA
Nvidia driver version        : No CUDA
cuDNN version                : No CUDA
HIP runtime version          : N/A
MIOpen runtime version       : N/A
Is XNNPACK available         : True

==============================
          CPU Info
==============================
Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        46 bits physical, 57 bits virtual
Byte Order:                           Little Endian
CPU(s):                               128
On-line CPU(s) list:                  0-127
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Xeon(R) Gold 6448Y
CPU family:                           6
Model:                                143
Thread(s) per core:                   2
Core(s) per socket:                   32
Socket(s):                            2
Stepping:                             8
CPU(s) scaling MHz:                   71%
CPU max MHz:                          4100.0000
CPU min MHz:                          800.0000
BogoMIPS:                             4200.00
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req hfi vnmi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities
Virtualization:                       VT-x
L1d cache:                            3 MiB (64 instances)
L1i cache:                            2 MiB (64 instances)
L2 cache:                             128 MiB (64 instances)
L3 cache:                             120 MiB (2 instances)
NUMA node(s):                         2
NUMA node0 CPU(s):                    0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32,34,36,38,40,42,44,46,48,50,52,54,56,58,60,62,64,66,68,70,72,74,76,78,80,82,84,86,88,90,92,94,96,98,100,102,104,106,108,110,112,114,116,118,120,122,124,126
NUMA node1 CPU(s):                    1,3,5,7,9,11,13,15,17,19,21,23,25,27,29,31,33,35,37,39,41,43,45,47,49,51,53,55,57,59,61,63,65,67,69,71,73,75,77,79,81,83,85,87,89,91,93,95,97,99,101,103,105,107,109,111,113,115,117,119,121,123,125,127
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:   Not affected
Vulnerability Spec store bypass:      Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1:             Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:             Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

==============================
Versions of relevant libraries
==============================
[pip3] flashinfer-python==0.6.4
[pip3] numpy==2.2.6
[pip3] nvidia-cublas-cu12==12.9.1.4
[pip3] nvidia-cuda-cupti-cu12==12.9.79
[pip3] nvidia-cuda-nvrtc-cu12==12.9.86
[pip3] nvidia-cuda-runtime-cu12==12.9.79
[pip3] nvidia-cudnn-cu12==9.10.2.21
[pip3] nvidia-cudnn-frontend==1.18.0
[pip3] nvidia-cufft-cu12==11.4.1.4
[pip3] nvidia-cufile-cu12==1.14.1.1
[pip3] nvidia-curand-cu12==10.3.10.19
[pip3] nvidia-cusolver-cu12==11.7.5.82
[pip3] nvidia-cusparse-cu12==12.5.10.65
[pip3] nvidia-cusparselt-cu12==0.7.1
[pip3] nvidia-cutlass-dsl==4.4.1
[pip3] nvidia-cutlass-dsl-libs-base==4.4.1
[pip3] nvidia-ml-py==13.590.48
[pip3] nvidia-nccl-cu12==2.27.5
[pip3] nvidia-nvjitlink-cu12==12.9.86
[pip3] nvidia-nvshmem-cu12==3.4.5
[pip3] nvidia-nvtx-cu12==12.9.79
[pip3] pyzmq==27.1.0
[pip3] sentence-transformers==5.2.3
[pip3] torch==2.10.0+cu129
[pip3] torch_c_dlpack_ext==0.1.5
[pip3] torchaudio==2.10.0+cu129
[pip3] torchvision==0.25.0+cu129
[pip3] transformers==4.57.6
[pip3] triton==3.6.0
[conda] flashinfer-python                           0.6.4            pypi_0                pypi
[conda] numpy                                       2.2.6            pypi_0                pypi
[conda] nvidia-cublas-cu12                          12.9.1.4         pypi_0                pypi
[conda] nvidia-cuda-cupti-cu12                      12.9.79          pypi_0                pypi
[conda] nvidia-cuda-nvrtc-cu12                      12.9.86          pypi_0                pypi
[conda] nvidia-cuda-runtime-cu12                    12.9.79          pypi_0                pypi
[conda] nvidia-cudnn-cu12                           9.10.2.21        pypi_0                pypi
[conda] nvidia-cudnn-frontend                       1.18.0           pypi_0                pypi
[conda] nvidia-cufft-cu12                           11.4.1.4         pypi_0                pypi
[conda] nvidia-cufile-cu12                          1.14.1.1         pypi_0                pypi
[conda] nvidia-curand-cu12                          10.3.10.19       pypi_0                pypi
[conda] nvidia-cusolver-cu12                        11.7.5.82        pypi_0                pypi
[conda] nvidia-cusparse-cu12                        12.5.10.65       pypi_0                pypi
[conda] nvidia-cusparselt-cu12                      0.7.1            pypi_0                pypi
[conda] nvidia-cutlass-dsl                          4.4.1            pypi_0                pypi
[conda] nvidia-cutlass-dsl-libs-base                4.4.1            pypi_0                pypi
[conda] nvidia-ml-py                                13.590.48        pypi_0                pypi
[conda] nvidia-nccl-cu12                            2.27.5           pypi_0                pypi
[conda] nvidia-nvjitlink-cu12                       12.9.86          pypi_0                pypi
[conda] nvidia-nvshmem-cu12                         3.4.5            pypi_0                pypi
[conda] nvidia-nvtx-cu12                            12.9.79          pypi_0                pypi
[conda] pyzmq                                       27.1.0           pypi_0                pypi
[conda] sentence-transformers                       5.2.3            pypi_0                pypi
[conda] torch                                       2.10.0+cu129     pypi_0                pypi
[conda] torch-c-dlpack-ext                          0.1.5            pypi_0                pypi
[conda] torchaudio                                  2.10.0+cu129     pypi_0                pypi
[conda] torchvision                                 0.25.0+cu129     pypi_0                pypi
[conda] transformers                                4.57.6           pypi_0                pypi
[conda] triton                                      3.6.0            pypi_0                pypi

==============================
         vLLM Info
==============================
ROCM Version                 : Could not collect
vLLM Version                 : 0.17.0
vLLM Build Flags:
  CUDA Archs: Not Set; ROCm: Disabled
GPU Topology:
  Could not collect

==============================
     Environment Variables
==============================
LD_LIBRARY_PATH=/opt/share/ETELSFSH/10.1/linux4.18-glibc2.28-x86_64/lib
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
TORCHINDUCTOR_CACHE_DIR=/tmp/torchinductor_jlquinn
</details>

🐛 Describe the bug

VLLM 0.17.0 crashes when loading LLM module.

(vllm) [jlquinn@login5 synth]$ python -c "from vllm import LLM"
INFO 03-09 18:42:41 [importing.py:44] Triton is installed but 0 active driver(s) found (expected 1). Disabling Triton to prevent runtime errors.
INFO 03-09 18:42:41 [importing.py:68] Triton not installed or not compatible; certain GPU-related functions will not be available.
Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/__init__.py", line 70, in __getattr__
    module = import_module(module_name, __package__)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/importlib/__init__.py", line 90, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/entrypoints/llm.py", line 48, in <module>
    from vllm.entrypoints.pooling.io_processor_factories import init_pooling_io_processors
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/entrypoints/pooling/io_processor_factories.py", line 7, in <module>
    from vllm.entrypoints.pooling.base.io_processor import PoolingIOProcessor
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/entrypoints/pooling/base/io_processor.py", line 16, in <module>
    from vllm.entrypoints.openai.engine.serving import RendererChatRequest, RendererRequest
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/entrypoints/openai/engine/serving.py", line 24, in <module>
    from vllm.engine.protocol import EngineClient
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/engine/protocol.py", line 23, in <module>
    from vllm.v1.engine.input_processor import InputProcessor
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/v1/engine/input_processor.py", line 20, in <module>
    from vllm.multimodal.encoder_budget import MultiModalBudget
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/multimodal/encoder_budget.py", line 10, in <module>
    from vllm.v1.core.encoder_cache_manager import compute_mm_encoder_budget
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/v1/core/encoder_cache_manager.py", line 9, in <module>
    from vllm.v1.request import Request
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/v1/request.py", line 24, in <module>
    from vllm.v1.structured_output.request import StructuredOutputRequest
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/v1/structured_output/__init__.py", line 19, in <module>
    from vllm.v1.structured_output.backend_xgrammar import XgrammarBackend
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/v1/structured_output/backend_xgrammar.py", line 20, in <module>
    from vllm.v1.structured_output.utils import (
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/vllm/v1/structured_output/utils.py", line 15, in <module>
    from diskcache import Cache
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/diskcache/__init__.py", line 8, in <module>
    from .core import (
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/site-packages/diskcache/core.py", line 14, in <module>
    import sqlite3
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/sqlite3/__init__.py", line 57, in <module>
    from sqlite3.dbapi2 import *
  File "/proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/sqlite3/dbapi2.py", line 27, in <module>
    from _sqlite3 import *
ImportError: /lib64/libstdc++.so.6: version `CXXABI_1.3.15' not found (required by /proj/dmfexp/jlquinn/sw/miniforge3/envs/vllm/lib/python3.12/lib-dynload/../.././libicui18n.so.78)

VLLM 0.16.0 loads 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

Fix Plan

The issue is caused by a missing version of libstdc++.so.6 that is required by libicui18n.so.78. To fix this, you can try the following steps:

  • Update your system's libstdc++.so.6 to a version that includes CXXABI_1.3.15:
sudo yum update libstdc++
  • If the above step doesn't work, you can try installing the libstdc++ package from a repository that includes the required version:
sudo yum install libstdc++-7.3.1-14.el9_5
  • Alternatively, you can try setting the LD_LIBRARY_PATH environment variable to include the path to a compatible version of libstdc++.so.6:
export LD_LIBRARY_PATH=/path/to/compatible/libstdc++.so.6:$LD_LIBRARY_PATH
  • If none of the above steps work, you can try downgrading your Python version to one that is compatible with the version of libstdc++.so.6 that you have installed.

Code Changes

No code changes are required to fix this issue. The problem is caused by a mismatch between the versions of libstdc++.so.6 and libicui18n.so.78, which can be resolved by updating or installing the required libraries.

Verification

To verify that the fix worked, you can try loading the LLM module again:

python -c "from vllm import LLM"

If the module loads successfully, then the fix was successful. If you still encounter errors, you may need to try additional troubleshooting steps.

Extra Tips

  • Make sure to check the versions of your libraries and dependencies to ensure that they are compatible with each other.
  • If you are using a virtual environment, make sure to activate it before installing or updating libraries.
  • If you are still encountering issues, try checking the documentation for your specific version of VLLM and Python to see if there are any known compatibility issues or troubleshooting steps that you can try.

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