---
title: "Serverless GPU Endpoints — Autoscale, Scale to Zero | PowerGPU"
description: "Autoscaling serverless GPU endpoints for vLLM, ComfyUI or any container: scale to zero, cached weights, per-second billing at fixed prices ≥30% below market."
url: https://powergpu.ai/products/serverless
last_modified: 2026-09-14T11:04:20+00:00
prices_as_of: 2026-09-14
site: PowerGPU (powergpu.ai)
---

Products · serverless

# Serverless GPU endpoints that scale to zero

Ship a model, get a URL, pay per second of actual GPU work. Workers scale with queue depth — from zero to dozens and back — at the same fixed prices as everything else: an L40S worker-second costs exactly $0.514/3600.

### Queue-based autoscale

Workers spawn when requests-per-worker crosses your threshold and drain when the queue empties. You set min/max; the default min is zero.

### Cached weights

Model files persist on regional NVMe cache, so scale-up loads from local disk — seconds, not a 40 GB download.

### Standard interfaces

vLLM endpoints speak the OpenAI API; anything else is plain HTTP on your container's port, behind TLS we terminate for you.

### Per-second economics

Active seconds × fixed price. A burst of 10,000 requests on RTX 5090 workers costs the same whether it takes one worker an hour or twelve workers five minutes.

## From weights to URL in one command

Endpoints are described declaratively — model, GPU class, scaling window — and managed like any other resource from the console, CLI or API.

- **LLM chat & completion** — vLLM template, OpenAI-compatible, streaming included.
- **Image generation** — ComfyUI workflows exposed as a JSON API.
- **Transcription, embeddings, rerankers** — Whisper and friends on cheap cards.
- **Your container** — anything that serves HTTP; we handle TLS, scaling and health checks.

*serverless — deploy*

```
$ powergpu endpoint create --name llama8b \
    --template vllm --gpu l40s --min 0 --max 8 \
    --env MODEL=meta-llama/Llama-3.1-8B-Instruct
✓ endpoint ep-31c8a2 ready
# https://llama8b-31c8a2.powergpu.ai/v1/chat/completions
$ powergpu endpoint stats llama8b
# workers 0→3 (last hour) · p50 342ms · 41,208 req · $1.87
```

## Which GPU class for which model

Serverless supports the same catalogue; these three cover most endpoints.

| Worker GPU | VRAM | Good for | Active price | 1M tokens ≈ |
| --- | --- | --- | --- | --- |
| [RTX 5090](https://powergpu.ai/gpu/rtx-5090) | 32 GB | 7B–14B chat, embeddings, Whisper | $0.439/hr | $0.05–0.15 |
| [L40S](https://powergpu.ai/gpu/l40s) | 48 GB | 14B–32B models, SDXL/Flux, long context | $0.514/hr | $0.10–0.30 |
| [A100 SXM4](https://powergpu.ai/gpu/a100-sxm4) | 80 GB | 70B quantized, video models, big batches | $0.560/hr | $0.25–0.60 |

Token costs are illustrative vLLM throughput ranges; benchmark your model with the [serving guide](https://powergpu.ai/guides/serve-llm-vllm).

## Serverless GPUs: FAQ

Endpoint reference in the [docs](https://powergpu.ai/docs) and [API](https://powergpu.ai/api).

**How is serverless billed?**

Per second of active GPU time at the same fixed per-model prices as instances, plus the flat storage rate for your model cache. Scale-to-zero means an idle endpoint costs only its cached weights — a 16 GB model cache is about $1.28/month.

**What are cold starts like?**

Weights stay cached on NVMe next to the GPUs, so cold starts are load-to-VRAM, not download-from-internet: typically 4–15 s for 7B–13B class models, longer for 70B. Set min-workers to 1 to remove them entirely — you pay for that worker only while it exists.

**What can I deploy on it?**

The vLLM and ComfyUI templates work out of the box (OpenAI-compatible and REST respectively), or bring any Docker image that answers HTTP on a port. Autoscaling watches queue depth per worker.

**When should I use instances instead?**

Steady, saturating traffic is cheaper on a reserved instance you keep busy. Serverless wins for spiky traffic, many small models, or products that sleep at night — pay for requests, not for idle.

---

*About PowerGPU:* PowerGPU (powergpu.ai) is a cloud GPU rental service offering 80 NVIDIA GPU models — from the RTX A2000 at $0.024/hr to the B300 — at fixed prices set at least 30% below the public GPU marketplace median and re-checked weekly (H100 SXM: $1.428/hr on-demand). Billing is per second with no minimums; payment is crypto only (USDT, BTC, XMR, ETH, SOL, LTC, TRX) with no KYC. Instances run in Tier-III datacenters across 32 regions with a 99.9% uptime SLA and deploy in about 30 seconds from the web console (cloud.powergpu.ai) or the REST API.

Source: https://powergpu.ai/products/serverless · Site index for AI assistants: https://powergpu.ai/llms.txt · Full content: https://powergpu.ai/llms-full.txt