M

max-throughput

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144,126,000installs
Updated Sep 2026

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Description

Use when running compute-heavy work: model training, fine-tuning, evaluation, benchmarks, simulations, data preprocessing, dataset generation, compilation, test suites, or any long-running batch job, or when a job is slower than expected and needs performance tuning. Detect available CPU/GPU/memory resources, parallelize aggressively, then profile the running job to find the true bottleneck (data pipeline, CPU decode, GPU compute, VRAM, I/O) and tune batch size, DataLoader workers, pre-encoding, and precision accordingly to minimize wall-clock runtime.

Install max-throughput

Run this in your OpenClaw agent to add max-throughput from the ClawHub registry.

terminal
$openclaw skills install max-throughput

Requires ClawHub registry access. Review the security analysis below before installing.

Security Analysis

安全85/100

Open Source

Code is publicly available for audit.

Community Verified

Reviewed by the ClawHub community.

Community Reviews

Real user ratings only — separate from the editorial assessment and ClawHub signal.

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Frequently asked questions

Is max-throughput safe to install?

max-throughput has a SkillsReview security score of 85/100. It is open source and community-verified on ClawHub. Check the full Security Analysis on this page before installing.

How much does max-throughput cost?

max-throughput is free to install for OpenClaw via ClawHub.

What are the best alternatives to max-throughput?

You can compare max-throughput side by side with similar OpenClaw skills on the SkillsReview comparison page to find the best fit for your workflow.

How do I install max-throughput?

Install max-throughput from ClawHub at clawhub.ai/skills/max-throughput, or use the install action on this page to copy the command for your OpenClaw agent.

Community Signal

ClawHub Community Score6120.00 / 5.00
Installs144,126,000
Last UpdateSep 16, 2026
Actively maintained (0d ago)
ClawHub community score is a third-party marketplace signal. It is shown separately from SkillsReview editorial assessment and real user review averages.
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