RTX 5060 Ti 16GB Load Test Guide

Before opening a RTX 5060 Ti 16GB deployment on our hosting to production traffic, run a sustained load test. A short benchmark shows peak; a load test shows what breaks under hours of real pressure.

Contents

• Goals
• Tool choice
• Scenario
• What to watch

Goals

• Find the concurrency level where p99 latency crosses your SLA
• Verify thermal stability over 2+ hours
• Confirm no memory leak over sustained runs
• Validate graceful degradation under overload

Tool

For LLM load testing, use vllm-benchmark or llmperf. Simple example with the ShareGPT dataset:

pip install llmperf
export OPENAI_API_BASE="http://localhost:8000/v1"
export OPENAI_API_KEY="n/a"

python -m llmperf.token_benchmark_ray \
  --model your-model \
  --num-concurrent-requests 16 \
  --num-completed-requests 500 \
  --metadata '{"name":"5060 Ti 16GB Load Test"}'

Scenario

Ramp test:

• 15 min at batch 4
• 30 min at batch 8
• 45 min at batch 16
• 30 min at batch 24
• 15 min at batch 32

Total: ~2 hours. Log tokens/sec, p50/p95/p99 TTFT, p50/p95/p99 decode latency, error rate per phase.

Watch

In parallel on the server:

nvidia-smi dmon -s u,m,p,t -c 7200 > load-test-gpu.csv

Records utilisation, memory, power, and temperature every second. After the test:

• VRAM used should stabilise, not grow (see memory leak detection)
• Temperature should stay under 80°C core, 90°C memory
• No thermal throttling events
• Consistent performance across ramp phases

If any fail, address before going live. Typical fixes: reduce max_num_seqs, enable chunked prefill, or step up GPU tier.