diff --git a/docker/Dockerfile.nmp-customizer-tasks b/docker/Dockerfile.nmp-customizer-tasks
index 9fc44860f7..084b7ecfe6 100644
--- a/docker/Dockerfile.nmp-customizer-tasks
+++ b/docker/Dockerfile.nmp-customizer-tasks
@@ -3,11 +3,11 @@
 #
 # Hosts file_io / model_entity (nmp.customization_common.tasks.*), model_spec
 # analysis (nmp.core.models.tasks.model_spec), and the LoRA adapter sidecar.
-# Built on NGC PyTorch 26.05 + transformers/accelerate + Nemotron wheels
+# Built on NGC PyTorch 26.07 + transformers/accelerate + Nemotron wheels
 # (mamba-ssm, causal-conv1d) + platform glue + nmp-models.
 
 ARG SMOKE_MARKER=smoke_nmp_customizer_tasks
-ARG PYTORCH_BASE=nvcr.io/nvidia/pytorch:26.05-py3
+ARG PYTORCH_BASE=nvcr.io/nvidia/pytorch:26.07-py3
 
 FROM ${PYTORCH_BASE} AS base
 
@@ -48,8 +48,8 @@ RUN --mount=type=cache,target=/root/.cache/uv \
     "transformers==${TRANSFORMERS_VERSION}" \
     "accelerate>=1.0.0"
 
-# Nemotron/Mamba CUDA wheels — compiled against NGC 26.05 torch; install --no-deps
-# after the HF stack so a PyPI torch never lands in the venv first.
+# Nemotron/Mamba CUDA wheels install --no-deps after the HF stack so a PyPI
+# torch never lands in the venv first.
 RUN --mount=from=causal-conv1d-wheel-src,target=/tmp/causal-conv1d-wheel-src,readonly \
     --mount=from=mamba-ssm-wheel-src,target=/tmp/mamba-ssm-wheel-src,readonly \
     uv pip install --python ${VIRTUAL_ENV}/bin/python --no-cache-dir --no-deps \
@@ -68,7 +68,7 @@ RUN --mount=type=cache,target=/root/.cache/uv \
     -e /app/services/core/models
 
 # Pin scanner-tracked runtime packages into /opt/venv before removing stale
-# NGC system-site copies inherited from nvcr.io/nvidia/pytorch:26.05-py3.
+# NGC system-site copies inherited from the PyTorch base.
 RUN --mount=type=cache,target=/root/.cache/uv \
     uv pip install --python ${VIRTUAL_ENV}/bin/python --no-cache \
     --overrides /app/docker/customizer/preserve_base_torch.txt \
diff --git a/docker/Dockerfile.nmp-unsloth-training b/docker/Dockerfile.nmp-unsloth-training
index f432ac6050..467f1551ca 100644
--- a/docker/Dockerfile.nmp-unsloth-training
+++ b/docker/Dockerfile.nmp-unsloth-training
@@ -28,10 +28,10 @@
 # Publish target: nmp-unsloth-training
 # Default tag:    `local` (override via BAKE_TAG at build time).
 
-# NGC PyTorch base. 26.05-py3 ships PyTorch 2.12 + CUDA 13.2 + Python 3.12 (aligned with
-# docker/automodel/Dockerfile.nmp-automodel-base). Override at build time:
+# NGC PyTorch base, aligned with docker/automodel/Dockerfile.nmp-automodel-base.
+# Override at build time:
 # --set nmp-unsloth-training.args.PYTORCH_BASE=...
-ARG PYTORCH_BASE=nvcr.io/nvidia/pytorch:26.05-py3
+ARG PYTORCH_BASE=nvcr.io/nvidia/pytorch:26.07-py3
 
 # Prebuilt CUDA-extension wheels (mamba-ssm + causal-conv1d), shared with
 # docker/automodel/Dockerfile.nmp-automodel-base. The bake `nmp-unsloth-training` target
@@ -124,7 +124,7 @@ RUN --mount=from=causal-conv1d-wheel-src,target=/tmp/causal-conv1d-wheel-src,rea
     /tmp/causal-conv1d-wheel-src/wheels/cu13.2/causal_conv1d-*cp312*.whl \
     /tmp/mamba-ssm-wheel-src/wheels/cu13.2/mamba_ssm-2.3.0-cp312*.whl
 
-# TODO: Step 1d: Flash Attention 2 — compiled from source against the NGC 26.02 torch.
+# TODO: Step 1d: Flash Attention 2 — compile from source against the active NGC torch.
 # /usr/local/cuda symlinks to an older toolkit; use /usr/local/cuda-13.1 instead.
 # Cap parallel nvcc/ninja work — default uses all CPUs and OOMs typical build hosts.
 # Put flash attention back in when we have a working wheel in a separate image.
@@ -182,7 +182,7 @@ RUN --mount=type=cache,target=/root/.cache/uv \
     "soupsieve>=2.8.4,<3" \
     "mlflow-skinny>=3.11.1,<3.12.0"
 
-# Stale NGC system site-packages (verified on nvcr.io/nvidia/pytorch:26.05-py3).
+# Stale NGC system site-packages inherited from the PyTorch base.
 RUN apt-get update && \
     DEBIAN_FRONTEND=noninteractive apt-get install -y --only-upgrade openssl libssl3t64 && \
     rm -rf /var/lib/apt/lists/*
diff --git a/docker/automodel/Dockerfile.nmp-automodel-base b/docker/automodel/Dockerfile.nmp-automodel-base
index ecb37c0ba5..5fe174b1a0 100644
--- a/docker/automodel/Dockerfile.nmp-automodel-base
+++ b/docker/automodel/Dockerfile.nmp-automodel-base
@@ -7,7 +7,7 @@
 # Pin to the tip of the Automodel release branch (origin/r0.5.0), not main.
 # Re-pin AUTOMODEL_COMMIT when cutting to a new r0.x.y.
 ARG AUTOMODEL_COMMIT=84e85792e34a240f09194a919c1e62c9d3e47938
-ARG PYTORCH_BASE=nvcr.io/nvidia/pytorch:26.05-py3
+ARG PYTORCH_BASE=nvcr.io/nvidia/pytorch:26.07-py3
 
 FROM causal-conv1d-wheel-image AS causal-conv1d-wheel-src
 FROM mamba-ssm-wheel-image AS mamba-ssm-wheel-src
@@ -121,7 +121,7 @@ COPY --from=nmp-automodel-base-builder /opt/Automodel /opt/Automodel
 # Builder pins uv 0.9.14 but does not ship it in the venv layer; PyTorch base may ship 0.10.x.
 COPY --from=ghcr.io/astral-sh/uv:0.9.14 /uv /bin/uv
 
-# Stale copies under NGC system site-packages (verified on nvcr.io/nvidia/pytorch:26.05-py3).
+# Stale copies under NGC system site-packages inherited from the PyTorch base.
 # CVE scanners read dist-packages even when --system-site-packages resolves imports from /opt/venv.
 # rm -rf (not pip uninstall) avoids corrupted dist-info RECORDs on the NGC base image.
 RUN apt-get update && \
diff --git a/docker/automodel/README.md b/docker/automodel/README.md
index 081f4bec6b..95867425bb 100644
--- a/docker/automodel/README.md
+++ b/docker/automodel/README.md
@@ -6,7 +6,7 @@ Two images for the **nmp-automodel** customization backend, plus the shared **`n
 
 | Image | Dockerfile | Role |
 |-------|------------|------|
-| `nmp-automodel-base` | `docker/automodel/Dockerfile.nmp-automodel-base` | PyTorch 26.05 + Automodel + `mamba-ssm` / `causal-conv1d` wheels |
+| `nmp-automodel-base` | `docker/automodel/Dockerfile.nmp-automodel-base` | PyTorch 26.07 + Automodel + `mamba-ssm` / `causal-conv1d` wheels |
 | `nmp-customizer-tasks` | `docker/Dockerfile.nmp-customizer-tasks` | Shared CPU tasks (`file_io`, `model_entity`, `model_spec`, LoRA sidecar) |
 | `nmp-automodel-training` | `docker/automodel/Dockerfile.nmp-automodel-training` | Training step (`nmp.automodel.tasks.training`) |
 
@@ -79,7 +79,7 @@ Override registry: `export WHEELS_REGISTRY=...` and `export IMAGE_REGISTRY=...`
 
 ## Tasks / training runtime (platform glue)
 
-**Base (`nmp-automodel-base`):** NGC PyTorch 26.05, Automodel `uv sync --locked`, pinned `transformers`/`torch`.
+**Base (`nmp-automodel-base`):** NGC PyTorch 26.07, Automodel `uv sync --locked`, pinned `transformers`/`torch`.
 
 **Automodel cherry-picks:** Platform-specific patches under `docker/automodel/cherry-picks/` are applied after `update_pyproject_pytorch.sh` and before `uv sync`. Re-pin or drop patches when upstream `r0.x.y` absorbs the same changes.
 
diff --git a/docker/base/Dockerfile.python-wheels b/docker/base/Dockerfile.python-wheels
index a38d605c58..8542b0f43d 100644
--- a/docker/base/Dockerfile.python-wheels
+++ b/docker/base/Dockerfile.python-wheels
@@ -100,8 +100,8 @@ RUN apt-get update && apt-get install -y --no-install-recommends software-proper
 
 COPY --from=ghcr.io/astral-sh/uv:0.9.14 /uv /usr/local/bin/uv
 
-# special builder for 13.2 cuda (automodel on NGC 26.05)
-FROM nvcr.io/nvidia/pytorch:26.05-py3 AS mamba-wheel-base-py312-cu13.2
+# special builder for 13.2 cuda (Automodel/Customizer on the current NGC PyTorch base)
+FROM nvcr.io/nvidia/pytorch:26.07-py3 AS mamba-wheel-base-py312-cu13.2
 
 ENV DEBIAN_FRONTEND=noninteractive