Home/Compare/gpu-telemetry vs scalene

Comparison

gpu-telemetry vs scalene

Verdict

Pick gpu-telemetry if gpu-telemetry provides comprehensive GPU observability in Kubernetes and Slurm environments by tying hardware metrics to the workload causing them; pick scalene if scalene is a high-performance CPU, GPU, and memory profiler for Python that uses AI to suggest optimizations.

Markdown twin · gpu-telemetry alternatives · scalene alternatives

GraphCanon updated 2w

gpu-telemetry logo

gpu-telemetry

last9/gpu-telemetry

57pushed Aug 2, 2026
vs
scalene logo

scalene

plasma-umass/scalene

13kpushed Aug 1, 2026

Trust & integrity

Signalgpu-telemetryscalene
Maintenance
Very active (6d since push)
As of 2w · github_public_v1
Very active (2d since push)
As of 2w · github_public_v1
Provenance
Not a fork · Organization account
As of 2w · github_public_v1
Not a fork · Organization account
As of 2w · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of 1mo · osv@v1
Published findings
As of 1mo · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1

Tagline

gpu-telemetry
GPU Observability with Workload Attribution
scalene
High-performance CPU, GPU, and memory profiler for Python with AI-powered optimization

Stars

gpu-telemetry
57
scalene
13k

Forks

gpu-telemetry
7
scalene
435

Open issues

gpu-telemetry
5
scalene
151

Language

gpu-telemetry
Python
scalene
Python

Adopt for

gpu-telemetry
gpu-telemetry provides comprehensive GPU observability in Kubernetes and Slurm environments by tying hardware metrics to the workload causing them.
scalene
Scalene is a high-performance CPU, GPU, and memory profiler for Python that uses AI to suggest optimizations.

Persona

gpu-telemetry
-
scalene
-

Runtime

gpu-telemetry
-
scalene
-

License

gpu-telemetry
MIT
scalene
Apache-2.0

Last pushed

gpu-telemetry
Aug 2, 2026
scalene
Aug 1, 2026

Categories

gpu-telemetry
Evaluation & Observability
scalene
Evaluation & Observability

Trust and health

Days since push

gpu-telemetry
6d
scalene
2d

Open issues (now)

gpu-telemetry
5
scalene
151

OSV dependency advisories

gpu-telemetry
No lockfile (source not queried)
scalene
Published findings

Full report

gpu-telemetry
Trust report

Shared compatibility

  • Python · gpu-telemetry: Python runtime · scalene: Python runtime

Choose gpu-telemetry if…

  • License: gpu-telemetry is MIT, scalene is Apache-2.0.
  • Tags unique to gpu-telemetry: amd, gpu-monitoring, intel-gaudi-base-operator, kubernetes.
  • When monitoring NVIDIA, AMD, or Intel Gaudi GPUs in Kubernetes clusters.

When NOT to use gpu-telemetry

  • If your infrastructure is not based on Kubernetes or Slurm.
  • When you prefer tools that do not require per-node OTLP agents.
  • For environments without support for NVIDIA, AMD, or Intel Gaudi GPUs.

Choose scalene if…

  • License: scalene is Apache-2.0, gpu-telemetry is MIT.
  • Tags unique to scalene: cpu-profiling, gpu-programming, memory-allocation, profiler.
  • When you need precise profiling of both CPU and GPU performance in Python applications

When NOT to use scalene

  • If your project does not involve Python, as Scalene is specific to this language
  • Avoid if your system lacks necessary dependencies like Visual C++ Redistributable on Windows

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: gpu-telemetry 57 · scalene 13k (synced Aug 9, 2026).

Common questions

What is the difference between gpu-telemetry and scalene?
gpu-telemetry: GPU Observability with Workload Attribution. scalene: High-performance CPU, GPU, and memory profiler for Python with AI-powered optimization. See the comparison table for live GitHub stats and shared categories.
When should I choose gpu-telemetry over scalene?
Choose gpu-telemetry over scalene when License: gpu-telemetry is MIT, scalene is Apache-2.0; Tags unique to gpu-telemetry: amd, gpu-monitoring, intel-gaudi-base-operator, kubernetes; When monitoring NVIDIA, AMD, or Intel Gaudi GPUs in Kubernetes clusters.
When should I choose scalene over gpu-telemetry?
Choose scalene over gpu-telemetry when License: scalene is Apache-2.0, gpu-telemetry is MIT; Tags unique to scalene: cpu-profiling, gpu-programming, memory-allocation, profiler; When you need precise profiling of both CPU and GPU performance in Python applications.
When should I avoid gpu-telemetry?
If your infrastructure is not based on Kubernetes or Slurm. When you prefer tools that do not require per-node OTLP agents. For environments without support for NVIDIA, AMD, or Intel Gaudi GPUs.
When should I avoid scalene?
If your project does not involve Python, as Scalene is specific to this language Avoid if your system lacks necessary dependencies like Visual C++ Redistributable on Windows
Is gpu-telemetry or scalene more popular on GitHub?
scalene has more GitHub stars (13,485 vs 57). Stars measure visibility, not whether either tool fits your constraints.
Are gpu-telemetry and scalene open source?
Yes - both are open-source projects on GitHub (gpu-telemetry: MIT, scalene: Apache-2.0).
Where can I find alternatives to gpu-telemetry or scalene?
GraphCanon lists graph-backed alternatives at gpu-telemetry alternatives and scalene alternatives (gpu-telemetry markdown twin, scalene markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, gpu-telemetry or scalene?
gpu-telemetry: Very active. scalene: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for gpu-telemetry and scalene?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: gpu-telemetry trust report; scalene trust report.

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