team / apex-local
GPU
VRAM — / — GB
CPU
Temp
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Jobs today
0
GPU hours used
0.0
0 jobs active
Queue depth
0
Success rate
%
0 failed today
GPU utilisation — live
2s interval
60s
5m
GPU util %
CPU %
GPU util
CUDA kernels active
CPU util
— cores
Temp
Throttle @ 90°C
Submit job
GPU accelerated
Job name
Docker image
Entry script + args
GPU count
Priority
Active jobs
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No jobs yet — submit one on the left.
Dev sessions
+ New
No active sessions.
Activity
Activity will appear here as jobs run.
All jobs
# Name Image Status GPU Prio Submitted Duration Actions
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Model registry
/workspace/models
Save model checkpoints to /workspace/models/<name>/
They will appear here once a scanner picks them up. (v0.2)
Team members
+ Invite
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Plan
Team Plan
Self-hosted · unlimited GPU jobs
Active dev sessions
+ New session
No active sessions.
How dev sessions work
Each session launches a fully isolated environment with browser-native VS Code, pre-connected to your shared workspace. Click to open it instantly in a new tab — no setup, no SSH, no local install required.

Use the pre-built apex/code-server:python or apex/code-server:pytorch images, or bring your own.
GPU + CPU — live
2s SSE tick
GPU util %
CPU %
Current readings
GPU util
GPU temp
GPU power
VRAM used
VRAM total
CPU util
RAM used
RAM total
Docker images
TagImage IDSize
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Tip
Apex reads images from your local image registry automatically — no manual push or sync required. Build your training image locally and it will appear here immediately. Pre-built apex/code-server:python and apex/code-server:pytorch images are available to get started quickly.
Audit log
Audit logging lands in v0.2. All API mutations will be recorded here.
Secrets
Encrypted secrets store lands in v0.2. For now, pass secrets via environment variables on the host machine.
Platform settings
Version
0.1.0
API base
Workspace path
~/apex-workspace
GPU
Config
~/.apex/config.json
logs
RUNNING