Python · MPL-2.0
dstackai/dstack
A unified orchestration layer for heterogeneous AI compute. It standardizes how to manage compute and run training and inference on GPU clouds, Kubernetes, VMs, or bare-metal clusters.
★ 2.3k
Stars
272 forks · 68 open issues
+1.3/day
Growth · measured
Stars counted between two of our own snapshots roughly a week apart. The repository page gives the exact span.
35.9
Momentum / 100
see the breakdown below
4y ago
Created
last push 2d ago
Star history
How this score was built
| Component | Weight | Earned | Why |
|---|---|---|---|
| Velocity | 55 | 6.9 | +1.3/day, log-scaled against a 750/day ceiling |
| Acceleration | 15 | 4.3 | last week ran 1.29× the monthly pace |
| Freshness | 15 | 15.0 | last push 2d ago; decays to zero at 180 days |
| Scale | 15 | 9.7 | 2.3k stars, log-scaled against 150k — stops a 3-star repo topping the board |
| Momentum | 100 | 35.9 | sum of the above |
Detail
| Topics | agent-skillsagentic-orchestrationamdcloudcontainersdockerfine-tuninggpuinferencek8skubernetesllmsmachine-learningnvidiaorchestrationpythonslurmtraining |
| Matched on | LLM & Inference (fine-tuning) |
| Short window | +9 stars over 7 days = 1.3/day |
| Long window | +26 stars over 26 days = 1.0/day |
| Lifetime average | 1.30 stars/day over 1,766 days |
| First seen here | 2026-10-11 |
| Last read | 2d ago |