Serverless GPU environment version 6 (Preview)

Important

This feature is in Public Preview.

This page outlines the system environment information for Serverless GPU environment version 6. This compute offering is part of AI Runtime, which is designed for modern AI and deep learning workloads.

Serverless GPU environment 6 is built on top of serverless environment 6 (CPU). See what's new in serverless environment 6 (CPU). It includes the following environment:

To ensure compatibility for the application, Serverless GPU workloads use a versioned API, known as the environment version, which remains compatible with newer server versions.

You can select a base environment that includes this environment version using the Environment side panel in your serverless notebooks. See Interactive (Notebooks).

New features and improvements

In version 6, the CUDA libraries are upgraded to NVIDIA CUDA 13, and the accompanying dependencies are upgraded to match, including MLflow and the Serverless GPU Python API. The common machine learning and AI libraries in the Databricks AI environment are updated for compatibility with the new CUDA version, along with the addition of several newly popular libraries.

CUDA 13 and PyTorch 2.11

Databricks AI environment

Version 6 upgrades the Databricks AI environment to the NVIDIA CUDA 13 toolkit and runtime stack. PyTorch is updated to torch 2.11.0 (built for CUDA 13.0, +cu130) with torchvision 0.26.0, and the bundled NVIDIA libraries (cuBLAS, cuDNN, NCCL, cuFFT, cuSPARSE, and related runtime components) are upgraded to their CUDA 13 builds.

Updated deep learning and LLM libraries

Databricks AI environment

Key machine learning libraries are upgraded in the Databricks AI environment, including:

  • transformers 5.8.1
  • vllm 0.24.0
  • ray 2.56.0
  • langchain 1.3.11
  • sentence-transformers 5.5.1
  • openai 2.37.0
  • scikit-learn 1.7.2
  • scipy 1.16.3
  • trl 0.24.0

Serverless GPU Python API

The Serverless GPU Python API 0.5.24 is included in this environment. For the full history of Serverless GPU Python API changes, see the version 5 release notes.

Packages added to Databricks AI environment

The following notable packages have been added to the Databricks AI environment in version 6:

  • langgraph 1.2.8 (with langgraph-checkpoint, langgraph-prebuilt, and langgraph-sdk)
  • langchain-classic 1.0.8
  • lightning 2.5.5
  • polars 1.42.1
  • ultralytics 8.4.90
  • flash_attn_3 3.0.0 and flash-attn-4 4.0.0b18
  • flashinfer-cubin 0.6.12
  • liger_kernel 0.8.1
  • fastsafetensors 0.3.2
  • tilelang 0.1.9
  • xgboost-cu13 3.2.0 (CUDA 13 build, replacing xgboost)
  • tabfm 1.0.1

In addition, the CUDA 13 toolkit and runtime libraries (for example, cuda-toolkit 13.0.2, nvidia-cudnn-cu13, nvidia-nccl-cu13, and related nvidia-* packages) are added as part of the CUDA 13 upgrade.

Packages removed from Databricks AI environment

The following notable packages have been removed from the Databricks AI environment in version 6:

  • unsloth (and unsloth_zoo)
  • xformers
  • diffusers
  • bitsandbytes
  • torchao
  • litellm
  • langchain-openai
  • cupy-cuda12x
  • mosaicml-streaming
  • gguf
  • seaborn
  • xgboost (replaced by xgboost-cu13) and xgboost-ray

The CUDA 12 runtime libraries (the nvidia-*-cu12 packages) are removed as part of the CUDA 13 upgrade. The JupyterLab and notebook development stack (for example, jupyterlab, notebook, nbconvert, nbclient, nbformat) and the Python LSP developer tooling (python-lsp-server, python-lsp-jsonrpc, rope, yapf) are also no longer bundled in the Databricks AI environment.

Packages not included in base environment

The following packages are not included in the base environment but remain available in the Databricks AI environment:

  • flash_attn
  • torch
  • torchvision
  • scikit-learn
  • scipy

Based on customer feedback requesting control over PyTorch versioning, torch is not included in the base environment for version 6. This allows you to install the version that best fits your workload. To use a Databricks-tested version, run %pip install torch==2.11.0 in a notebook cell or install torch==2.11.0 using the Dependencies section of the Environment side panel.

System environment

  • Operating System: Ubuntu 24.04 LTS
  • Python: 3.12.3
  • Databricks Connect: 19.0.0
  • NVIDIA CUDA Toolkit: 13.0

Installed Python libraries

Standard environment

To reproduce serverless GPU environment 6 in your local Python virtual environment, download the requirements-env-gpu-6.txt file and run pip install -r requirements-env-gpu-6.txt. This command installs all of the libraries from serverless environment 6.

Library Version Library Version Library Version
annotated-doc 0.0.4 annotated-types 0.7.0 anyio 4.10.0
arro3-core 0.8.0 asttokens 3.0.0 astunparse 1.6.3
azure-core 1.41.0 azure-identity 1.25.3 azure-mgmt-core 1.6.0
azure-mgmt-web 10.1.0 azure-storage-blob 12.29.0 azure-storage-file-datalake 12.24.0
black 25.9.0 blinker 1.7.0 boto3 1.40.46
botocore 1.40.46 cachetools 5.5.1 certifi 2025.11.12
cffi 2.0.0 charset-normalizer 3.4.4 click 8.2.1
cloudpickle 3.1.1 comm 0.2.3 contourpy 1.3.3
cryptography 46.0.3 cycler 0.11.0 databricks-agents 1.11.0
databricks-connect 19.0.0 databricks-sdk 0.122.0 databricks.serverless_gpu 0.5.24
dataclasses-json 0.6.7 dbus-python 1.3.2 debugpy 1.8.16
decorator 5.2.1 deltalake 1.5.1 Deprecated 1.3.1
distlib 0.4.0 executing 2.2.1 fastapi 0.136.3
filelock 3.29.0 fonttools 4.60.1 fsspec 2025.9.0
future 1.0.0 gitdb 4.0.11 GitPython 3.1.45
google-api-core 2.30.3 google-auth 2.53.0 google-cloud-core 2.6.0
google-cloud-storage 3.10.1 google-crc32c 1.8.0 google-resumable-media 2.9.0
googleapis-common-protos 1.71.0 grpcio 1.76.0 grpcio-status 1.76.0
h11 0.16.0 httplib2 0.20.4 idna 3.11
importlib_metadata 8.7.0 iniconfig 2.1.0 ipyflow-core 0.0.227
ipykernel 6.31.0 ipython 9.7.0 ipython_pygments_lexers 1.1.1
ipywidgets 8.1.7 isodate 0.7.2 jedi 0.19.2
Jinja2 3.1.6 jmespath 1.0.1 joblib 1.5.2
jupyter_client 8.6.3 jupyter_core 5.8.1 jupyterlab_widgets 3.0.15
kiwisolver 1.4.8 launchpadlib 1.11.0 lazr.restfulclient 0.14.6
lazr.uri 1.0.6 markdown-it-py 2.2.0 MarkupSafe 3.0.2
marshmallow 3.26.2 matplotlib 3.10.6 matplotlib-inline 0.2.1
mccabe 0.7.0 mdurl 0.1.2 mlflow-skinny 3.12.0
mmh3 5.2.1 msal 1.36.0 msal-extensions 1.3.1
msrest 0.7.1 mypy-extensions 1.0.0 nest-asyncio 1.6.0
nodeenv 1.10.0 numpy 2.3.4 nvidia-ml-py 13.590.44
oauthlib 3.2.2 opencv_python_headless 5.0.0.93 opentelemetry-api 1.42.1
opentelemetry-proto 1.42.1 opentelemetry-sdk 1.42.1 opentelemetry-semantic-conventions 0.63b1
packaging 25.0 pandas 2.3.3 parambench-train-comms 0.0.0
parso 0.8.5 pathspec 0.12.1 pexpect 4.9.0
pillow 12.0.0 pip 25.3 platformdirs 4.5.0
pluggy 1.5.0 prompt_toolkit 3.0.52 proto-plus 1.28.0
protobuf 6.33.5 psutil 7.0.0 ptyprocess 0.7.0
pure_eval 0.2.3 py4j 0.10.9.9 pyarrow 21.0.0
pyasn1 0.6.1 pyasn1_modules 0.4.2 pyccolo 0.0.83
pycparser 2.23 pydantic 2.13.3 pydantic_core 2.46.3
pydot 4.0.0 pyflakes 3.2.0 Pygments 2.19.2
PyGObject 3.48.2 pyiceberg 0.11.1 PyJWT 2.10.1
pyparsing 3.2.5 pyright 1.1.409 pyroaring 1.1.0
pyspark 4.3.0.dev0+databricks.connect.19.0.0 pytest 8.4.2 python-dateutil 2.9.0.post0
python-dotenv 1.2.2 pytokens 0.2.0 pytz 2025.2
PyYAML 6.0.3 pyzmq 27.1.0 regex 2025.9.1
requests 2.32.5 requests-oauthlib 2.0.0 rich 14.2.0
s3transfer 0.14.0 setuptools 80.9.0 six 1.17.0
smmap 5.0.0 sniffio 1.3.0 sqlparse 0.5.5
ssh-import-id 5.11 stack-data 0.6.3 starlette 0.52.1
strictyaml 1.7.3 tenacity 9.1.2 threadpoolctl 3.5.0
tiktoken 0.13.0 tokenize_rt 6.2.0 tomli 2.0.1
tornado 6.5.1 tqdm 4.67.1 traitlets 5.14.3
typing-inspect 0.9.0 typing-inspection 0.4.2 typing_extensions 4.15.0
tzdata 2026.2 unattended-upgrades 0.1 urllib3 2.5.0
uvicorn 0.48.0 virtualenv 20.35.4 wadllib 1.3.6
wcwidth 0.2.13 wheel 0.45.1 whenever 0.7.3
widgetsnbextension 4.0.14 wrapt 1.17.0 zipp 3.23.0
zstandard 0.25.0

AI environment

The AI environment includes all the packages from the Standard environment, as well as the following packages. This environment includes PyTorch and comprehensive machine learning libraries:

  • torch 2.11.0
  • torchvision 0.26.0
  • flash_attn 2.8.3
  • catboost 1.2.10
  • langchain 1.3.11
  • langgraph 1.2.8
  • lightgbm 4.6.0
  • lightning 2.5.5
  • openai 2.37.0
  • optuna 4.5.0
  • polars 1.42.1
  • pytorch-lightning 2.5.4
  • ray 2.56.0
  • scikit-learn 1.7.2
  • scipy 1.16.3
  • sentence-transformers 5.5.1
  • transformers 5.8.1
  • trl 0.24.0
  • ultralytics 8.4.90
  • vllm 0.24.0
  • xgboost-cu13 3.2.0

To reproduce AI environment V6 in your local Python virtual environment, download the requirements-ai-gpu-6.txt file and run pip install -r requirements-ai-gpu-6.txt. This command installs all the libraries from AI environment.

Library Version Library Version Library Version
absl-py 2.4.0 accelerate 1.13.0 aiohappyeyeballs 2.6.1
aiohttp 3.13.5 aiohttp-cors 0.8.1 aiosignal 1.4.0
alembic 1.18.5 annotated-doc 0.0.4 annotated-types 0.7.0
anthropic 0.116.0 antlr4-python3-runtime 4.9.3 anyio 4.10.0
apache-tvm-ffi 0.1.9 arro3-core 0.8.0 astor 0.8.1
asttokens 3.0.0 astunparse 1.6.3 attrs 25.4.0
audioread 3.1.0 azure-core 1.41.0 azure-identity 1.25.3
azure-mgmt-core 1.6.0 azure-mgmt-web 10.1.0 azure-storage-blob 12.29.0
azure-storage-file-datalake 12.24.0 black 25.9.0 blake3 1.0.9
blinker 1.7.0 boto3 1.40.46 botocore 1.40.46
cachetools 5.5.1 catboost 1.2.10 cbor2 6.1.3
certifi 2025.11.12 cffi 2.0.0 charset-normalizer 3.4.4
click 8.4.2 cloudpickle 3.1.1 colorful 0.5.8
colorlog 6.10.1 comm 0.2.3 compressed-tensors 0.17.0
contourpy 1.3.3 cryptography 44.0.1 cuda-bindings 13.3.1
cuda-core 1.0.1 cuda-pathfinder 1.5.6 cuda-python 13.3.1
cuda-tile 1.3.0 cuda-toolkit 13.0.2 cycler 0.11.0
databricks-agents 1.11.0 databricks-sdk 0.122.0 dataclasses-json 0.6.7
datasets 4.8.5 dbus-python 1.3.2 debugpy 1.8.16
decorator 5.2.1 deltalake 1.5.1 Deprecated 1.3.1
depyf 0.20.0 detect-installer 0.1.0 dill 0.4.0
diskcache 5.6.3 distlib 0.4.0 dm-tree 0.1.10
dnspython 2.8.0 docstring_parser 0.18.0 einops 0.8.2
email-validator 2.3.0 evaluate 0.4.6 executing 2.2.1
Farama-Notifications 0.0.6 fastapi 0.136.3 fastapi-cli 0.0.28
fastapi-cloud-cli 0.22.1 fastar 0.11.0 fastsafetensors 0.3.2
filelock 3.29.0 flash-attn-4 4.0.0b18 flash_attn 2.8.3
flash_attn_3 3.0.0 flashinfer-cubin 0.6.12 flashinfer-python 0.6.12
fonttools 4.60.1 frozenlist 1.8.0 fsspec 2025.9.0
future 1.0.0 gitdb 4.0.11 GitPython 3.1.45
google-api-core 2.30.3 google-auth 2.53.0 google-cloud-core 2.6.0
google-cloud-storage 3.10.1 google-crc32c 1.8.0 google-resumable-media 2.9.0
googleapis-common-protos 1.71.0 graphviz 0.21 greenlet 3.2.4
grpcio 1.76.0 grpcio-status 1.76.0 gymnasium 1.2.2
h11 0.16.0 hf-xet 1.5.1 hf_transfer 0.1.9
httpcore 1.0.9 httplib2 0.20.4 httptools 0.8.0
httpx 0.28.1 httpx-sse 0.4.3 huggingface_hub 1.22.0
humming-kernels 0.1.6 idna 3.11 ijson 3.5.1
importlib_metadata 8.7.0 iniconfig 2.1.0 interegular 0.3.3
ipyflow-core 0.0.227 ipykernel 6.31.0 ipython 9.7.0
ipython_pygments_lexers 1.1.1 ipywidgets 8.1.7 isodate 0.7.2
jedi 0.19.2 Jinja2 3.1.6 jiter 0.16.0
jmespath 1.0.1 joblib 1.5.2 jsonpatch 1.33
jsonpointer 3.1.1 jsonschema 4.25.0 jsonschema-specifications 2025.9.1
jupyter_client 8.6.3 jupyter_core 5.8.1 jupyterlab_widgets 3.0.15
kiwisolver 1.4.8 langchain 1.3.11 langchain-classic 1.0.8
langchain-community 0.4.2 langchain-core 1.4.7 langchain-protocol 0.0.18
langchain-text-splitters 1.1.2 langgraph 1.2.8 langgraph-checkpoint 4.1.1
langgraph-prebuilt 1.1.0 langgraph-sdk 0.4.2 langsmith 0.9.3
lark 1.2.2 launchpadlib 1.11.0 lazr.restfulclient 0.14.6
lazr.uri 1.0.6 lazy_loader 0.4 librosa 0.11.0
liger_kernel 0.8.1 lightgbm 4.6.0 lightning 2.5.5
lightning-utilities 0.15.3 llguidance 1.7.6 llvmlite 0.47.0
lm-format-enforcer 0.11.3 loguru 0.7.3 lz4 4.4.5
Mako 1.3.12 markdown-it-py 2.2.0 MarkupSafe 3.0.2
marshmallow 3.26.2 matplotlib 3.10.6 matplotlib-inline 0.2.1
mccabe 0.7.0 mcp 1.28.1 mdurl 0.1.2
mistral_common 1.11.5 ml_dtypes 0.5.4 mlflow-skinny 3.13.0
mmh3 5.2.1 model-hosting-container-standards 0.1.16 mpmath 1.3.0
msal 1.36.0 msal-extensions 1.3.1 msgpack 1.2.1
msgspec 0.21.1 msrest 0.7.1 multidict 6.7.0
multiprocess 0.70.16 mypy-extensions 1.0.0 narwhals 2.7.0
nest-asyncio 1.6.0 networkx 3.5 ninja 1.13.0
nodeenv 1.10.0 numba 0.65.0 numpy 2.3.4
nvidia-cublas 13.1.0.3 nvidia-cuda-cccl 13.3.3.4.1 nvidia-cuda-crt 13.3.73
nvidia-cuda-cupti 13.0.85 nvidia-cuda-nvcc 13.2.78 nvidia-cuda-nvrtc 13.0.88
nvidia-cuda-runtime 13.0.96 nvidia-cuda-tileiras 13.2.78 nvidia-cudnn-cu13 9.19.0.56
nvidia-cudnn-frontend 1.25.0 nvidia-cufft 12.0.0.61 nvidia-cufile 1.15.1.6
nvidia-curand 10.4.0.35 nvidia-cusolver 12.0.4.66 nvidia-cusparse 12.6.3.3
nvidia-cusparselt-cu13 0.8.0 nvidia-cutlass-dsl 4.5.2 nvidia-cutlass-dsl-libs-base 4.5.2
nvidia-cutlass-dsl-libs-cu13 4.5.2 nvidia-ml-py 13.590.44 nvidia-nccl-cu13 2.28.9
nvidia-nvjitlink 13.0.88 nvidia-nvshmem-cu13 3.4.5 nvidia-nvtx 13.0.85
nvidia-nvvm 13.2.78 oauthlib 3.2.2 omegaconf 2.3.1
openai 2.37.0 openai-harmony 0.0.8 opencensus 0.11.4
opencensus-context 0.1.3 opencv-python 5.0.0.93 opencv_python_headless 5.0.0.93
opentelemetry-api 1.42.1 opentelemetry-exporter-otlp 1.42.1 opentelemetry-exporter-otlp-proto-common 1.42.1
opentelemetry-exporter-otlp-proto-grpc 1.42.1 opentelemetry-exporter-otlp-proto-http 1.42.1 opentelemetry-exporter-prometheus 0.63b1
opentelemetry-proto 1.42.1 opentelemetry-sdk 1.42.1 opentelemetry-semantic-conventions 0.63b1
opentelemetry-semantic-conventions-ai 0.5.1 optuna 4.5.0 optuna-integration 4.5.0
orjson 3.11.9 ormsgpack 1.12.2 outlines_core 0.2.14
packaging 25.0 pandas 2.3.3 parso 0.8.5
partial-json-parser 0.2.1.1.post7 pathspec 0.12.1 patsy 1.0.1
peft 0.19.1 pexpect 4.9.0 pillow 12.0.0
pip 25.0.1 platformdirs 4.5.0 plotly 6.8.0
pluggy 1.5.0 polars 1.42.1 polars-runtime-32 1.42.1
pooch 1.9.0 prometheus-fastapi-instrumentator 8.0.2 prometheus_client 0.21.1
prompt_toolkit 3.0.52 propcache 0.3.1 proto-plus 1.28.0
protobuf 6.33.5 psutil 7.0.0 ptyprocess 0.7.0
pure_eval 0.2.3 py-cpuinfo 9.0.0 py-spy 0.4.2
pyarrow 21.0.0 pyasn1 0.6.1 pyasn1_modules 0.4.2
pybase64 1.4.3 pyccolo 0.0.83 pycountry 26.2.16
pycparser 2.23 pydantic 2.13.3 pydantic-extra-types 2.11.1
pydantic-settings 2.14.2 pydantic_core 2.46.3 pydot 4.0.0
pyelftools 0.33 pyflakes 3.2.0 Pygments 2.19.2
PyGObject 3.48.2 pyiceberg 0.11.1 PyJWT 2.10.1
pynndescent 0.6.0 pynvml 8.0.1 pyparsing 3.2.5
pyright 1.1.409 pyroaring 1.1.0 pytesseract 0.3.13
pytest 8.4.2 python-dateutil 2.9.0.post0 python-dotenv 1.2.2
python-json-logger 3.2.1 python-multipart 0.0.32 pytokens 0.2.0
pytorch-lightning 2.5.4 pytorch-ranger 0.1.1 pytz 2025.2
PyYAML 6.0.3 pyzmq 27.1.0 quack-kernels 0.5.0
ray 2.56.0 referencing 0.37.0 regex 2025.10.22
requests 2.32.5 requests-oauthlib 2.0.0 requests-toolbelt 1.0.0
rich 14.2.0 rich-toolkit 0.20.1 rignore 0.7.6
rpds-py 0.28.0 s3transfer 0.14.0 safetensors 0.8.0
scikit-learn 1.7.2 scipy 1.16.3 sentence-transformers 5.5.1
sentencepiece 0.2.1 sentry-sdk 2.64.0 setproctitle 1.3.7
setuptools 80.9.0 shap 0.51.0 shellingham 1.5.4
six 1.17.0 slicer 0.0.8 smart_open 8.0.0
smmap 5.0.0 sniffio 1.3.0 soundfile 0.13.1
soxr 1.1.0 SQLAlchemy 2.0.43 sqlparse 0.5.5
sse-starlette 3.4.5 ssh-import-id 5.11 stack-data 0.6.3
starlette 1.3.1 statsmodels 0.14.5 strictyaml 1.7.3
supervisor 4.3.0 sympy 1.14.0 tabulate 0.9.0
tenacity 9.1.2 tensorboardX 2.6.5 threadpoolctl 3.5.0
tiktoken 0.13.0 tilelang 0.1.9 tokenize_rt 6.2.0
tokenizers 0.22.1 tokenspeed-mla 0.1.2 tokenspeed-triton 3.7.10.post20260531
tomli 2.0.1 torch 2.11.0+cu130 torch-optimizer 0.3.0
torch_c_dlpack_ext 0.1.5 torchaudio 2.11.0+cu130 torchmetrics 1.9.0
torchvision 0.26.0+cu130 tornado 6.5.1 tqdm 4.67.1
traitlets 5.14.3 transformers 5.8.1 triton 3.6.0
trl 0.24.0 typer 0.26.8 typing-inspect 0.9.0
typing-inspection 0.4.2 typing_extensions 4.15.0 tzdata 2026.2
ultralytics 8.4.90 ultralytics-thop 2.0.20 umap-learn 0.5.12
unattended-upgrades 0.1 urllib3 2.5.0 uuid_utils 0.16.2
uvicorn 0.48.0 uvloop 0.22.1 virtualenv 20.35.4
vllm 0.24.0 wadllib 1.3.6 watchfiles 1.2.0
wcwidth 0.2.13 websockets 15.0.1 wheel 0.45.1
whenever 0.7.3 widgetsnbextension 4.0.14 wrapt 1.17.0
xgboost-cu13 3.2.0 xgrammar 0.2.3 xxhash 3.5.0
yarl 1.22.0 z3-solver 4.15.4.0 zipp 3.23.0
zstandard 0.25.0
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