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PSU and Cooling for Local LLM PCs in Delhi

Power supply and cooling for local LLM PCs in Delhi: sustained GPU load, airflow, dust, and when thermal service is needed.

By Sachin GuptaPublished 13 September 20263 min readUpdated 13 September 2026

Quick overview

Power supply and cooling for local LLM PCs in Delhi: sustained GPU load, airflow, dust, and when thermal service is needed.

AI PC cooling DelhiLLM GPU power supply

Local LLMs keep the GPU busy far longer than a typical gaming match. In Delhi heat and dust, that turns PSU and cooling from nice-to-have into uptime insurance. A machine that passes a 30-second benchmark but throttles after twenty minutes of inference will feel broken even with enough VRAM.

Quick answer

Size the PSU to the GPU vendor's required system power with headroom. Improve case intake and exhaust, clean filters quarterly, and treat high fan noise as a signal to inspect dust before you blame the model.

PSU rules

  • Use reputable brands with clear wattage ratings
  • Respect 12V rail capacity for high-end GPUs
  • Replace aging PSUs when upgrading to a much hotter card

Read why PCs need UPS if inference runs overnight during unstable power.

Cooling and airflow

Inference loads are steady. Steady loads expose weak case airflow faster than burst gaming. See how to improve case airflow.

Delhi maintenance

Dust clogs filters and GPU heatsinks. Basic cleaning can lower fan noise when dust is the culprit: Basic PC Cleaning. Persistent hotspots after cleaning may need thermal service.

Thermal paste and GPUs

Desktop GPUs use factory paste for years, but CPU repaste and blower maintenance differ. Do not assume paste fixes a GPU VRAM OOM.

How Roger N Reckon can help

Roger N Reckon offers Basic PC Cleaning, DeepClean, and CPU thermal services when dust or paste issues show up during AI workloads. Confirm scope before booking.

Practical checklist

1. Write down the model size, quant level, and target context length you need. 2. Measure current GPU VRAM, system RAM, and free NVMe space before buying parts. 3. Confirm PSU wattage against the GPU vendor's required system power. 4. Plan cooling for sustained inference, not just short benchmarks. 5. Back up data before OS or hardware changes. 6. Request a written component list, testing scope, and warranty terms for any build or upgrade. 7. Re-test with the same prompt and context after changes.

Frequently Asked Questions

Why did tokens slow down after summer started?

Thermal throttling lowers clock speeds. Check GPU temps under load.

Is a 650W PSU enough?

Only if the GPU documentation says so for your exact card. LLM load uses sustained power draw.

Should I run with case open?

Temporary debugging only; open cases worsen dust and airflow patterns.

Do LLM PCs need server fans?

Consumer cases work if configured correctly.

Can cleaning fix OOM errors?

No. Cleaning fixes heat and noise, not memory size.

Final takeaway

Treat inference like a marathon for thermals. Power and airflow are part of AI PC spec.

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