Comparison
GPUBox vs RunPod
Different products with different audiences. RunPod is GPU container rental — you bring a model, they rent you the hardware by the hour. It's the right answer when you need a specific model that nobody else hosts, or when you're running custom training.
GPUBox is an inference API. We host curated models on UK-domiciled hardware, you call them via the OpenAI-compatible surface and pay per token. It's the right answer when you want base_url = "https://api.gpubox.ai/v1" and to be done.
| Attribute | GPUBox | RunPod |
|---|---|---|
| Product shape | OpenAI-compatible API. You call /v1/chat/completions with a model name. We host the GPU. | GPU pod rental. You rent containers by the hour, install your own runtime, manage your own scaling. |
| Pricing model | Per-call. £1.00 per million tokens (chat), £0.005 per audio minute. No idle charges. | Per-hour pod rental. ~$0.34/hr for RTX 4090, ~$0.69/hr for RTX A6000, ~$2.69/hr for H100. Pay for the time the pod is running. |
| Hardware location | United Kingdom. Single-region by design. UK-incorporated operating company. | Global. ~30 regions across NA / EU / Asia. Customers self-select region. |
| Data sovereignty | UK-domiciled hardware, UK company, UK jurisdiction. No data leaves the UK without your action. | Region-dependent. Most regions are US-based. EU regions exist. No specific UK-sovereign offering. |
| Setup time | Change one URL in your existing OpenAI SDK code. Three lines. No infrastructure to provision. | Pick a template (vLLM, Ollama, custom) → spin up a pod → wait for warm-up → expose endpoint. Minutes per pod. |
| Model selection | Curated. Three models live: Qwen2.5-32B-Instruct (chat), Whisper-large-v3-turbo (audio), BGE-M3 embeddings (soon). | Anything you can fit in a container. Bring-your-own-model. Hundreds of community templates. |
| Cold starts | None. Models are warm. First token is sub-second on chat completions. | Yes on serverless tier. Mitigated by their FlashBoot warm-pool. Pod-tier has no cold start (you're paying for warm). |
| Idle charges | None. You pay only for tokens you generate. | Yes on pod tier. The card is yours while it's running, even if you're not making requests. |
| Scale ceiling | Single 5090 today. Capacity-planned, not auto-elastic. Email us for dedicated capacity. | Effectively unlimited. Spin up as many pods as you can pay for. |
| Custom models / fine-tuning | Not yet on the API. Roadmap (Factory product). Available manually for partnership engagements. | Yes — bring any container. Train, fine-tune, run any model you can package. |
| OpenAI SDK compatibility | Full. Python, Node, Go, curl — every official SDK works with one URL change. | Depends on the template. vLLM templates yes. Custom containers: whatever you implement. |
| Billing | GBP, VAT-compliant invoicing for UK and EU customers. | USD primarily. International billing supported. |
| Audit log | Per-call audit log retained 30 days minimum. Token-level usage in dashboard. | Pod-level usage logs. Per-request logging is your responsibility (you're running the runtime). |
Pick GPUBox if
- You want OpenAI-compatible API access in three lines of code.
- You need UK data residency for regulatory or contractual reasons.
- You want predictable per-token pricing, not per-hour pod meters.
- You want managed model serving — no template selection, no warm-up tuning.
- Curated chat / audio / embeddings models cover your use case.
Pick RunPod if
- You need a specific OSS model GPUBox doesn't host.
- You're running custom training and need raw container control.
- You need cards we don't have (H100, A100, multi-GPU pods).
- You're operating globally and want region selection per pod.
- Your traffic is bursty enough that hourly metering wins on cost.
Try the drop-in for yourself.
Email us for a same-day API key. First £20 of usage is on us.