Individual skill
vastai-performance-tuning
Tune Vast.ai offer selection, startup, data feeding, GPU memory, and scaling from measured useful-work throughput. Use when jobs are slow, GPUs are underutilized, or faster offers cost more. Trigger with: "tune Vast.ai performance", "improve GPU utilization", "compare Vast.ai throughput".
skills/.curated/vastai-performance-tuning/SKILL.md
Source commit 0500b275e963c027f6b410e8c49c0446945c574e
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- Repository last updated
- Nov 12, 2026
- License
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- ai Repository topic
- automation Repository topic
- claude-code Repository topic
- devops Repository topic
- mcp Repository topic
- ai-agents Repository topic
- anthropic Repository topic
- claude-code-plugins Repository topic
- developer-tools Repository topic
- llm Repository topic
- saas Declared skill tag
- vastai Declared skill tag
- performance Declared skill tag
- gpu Declared skill tag
- benchmarking Declared skill tag
- engineering Derived category
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SKILL.mdcore · 4,106 bytesSKILL.mdcore · 4,106 bytesreferences/official-docs.mddoc · 1,352 bytes
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# Vast.ai Useful-Work Performance Tuning
## Overview
Provider benchmark fields help shortlist offers but do not replace workload measurement. Tune one bottleneck at a time and compare completed-work latency, throughput, reliability, and total cost on immutable workload bytes.
## Prerequisites
- Representative input, warm-up, sample count, correctness assertion, and target SLO
- Pinned code/image/model plus candidate GPU, VRAM, host, network, and disk profiles
- Baseline throughput, utilization, memory, startup time, and useful-work cost
## Instructions
