Migrate from OpenAI to Dedicated GPU: Savings Calculator
How much can you save by moving from OpenAI (GPT-4o / GPT-4o-mini) to a dedicated GPU server?
Projected Savings
OpenAI’s per-token pricing was designed for experimentation, not production at scale. Teams spending £500/month on GPT-4o and GPT-4o-mini calls can run equivalent open-source models on a dedicated RTX 5090 for a fraction of the cost:
- £411/month (82% reduction)
- £4,932/year in total savings
Savings by Current OpenAI Spend
| Current OpenAI Spend | GigaGPU RTX 5090 Cost | Monthly Savings | Annual Savings |
|---|---|---|---|
| £100/mo | £89/mo | £11/mo | £132/yr |
| £250/mo | £89/mo | £161/mo | £1,932/yr |
| £500/mo | £89/mo | £411/mo | £4,932/yr |
| £1000/mo | £89/mo | £911/mo | £10,932/yr |
| £2500/mo | £89/mo | £2411/mo | £28,932/yr |
| £5000/mo | £89/mo | £4911/mo | £58,932/yr |
GigaGPU pricing is fixed monthly. No per-token, per-image, or per-request fees.
Why OpenAI Bills Grow Faster Than Expected
OpenAI charges per token with costs that scale linearly. Most teams underestimate their actual token consumption because prompts, system messages, and conversation history all count toward billing. Teams spending over £200/month can typically save 50-80% by migrating to equivalent open-source models on dedicated hardware. The drop-in OpenAI-compatible API format supported by vLLM and TGI means your application code barely changes — you swap the base URL and API key.
What Replaces Your OpenAI Subscription
- Dedicated hardware: A full RTX 5090 server exclusively for your workloads. No sharing, no noisy neighbours.
- Recommended alternative: LLaMA 3 70B or Mistral 7B delivers comparable quality to GPT-4o / GPT-4o-mini for most production use cases.
- Fixed pricing: £89/month regardless of how many tokens, images, or requests you process.
- Full control: SSH access, custom model deployment, fine-tuning capability, no vendor lock-in.
- Data sovereignty: Your data stays on your server. No third-party data processing or logging.
Six Steps to Leave OpenAI
- Audit current usage: Export your OpenAI usage data to understand volume, peak times, and model requirements.
- Select your GPU server: Based on your throughput needs, choose from GigaGPU dedicated plans starting at £89/month.
- Deploy your model: GigaGPU servers come with CUDA, Docker, and inference frameworks pre-installed. Deploy LLaMA 3 70B or Mistral 7B in under 15 minutes.
- Update API endpoints: Point your application to your new server. Most inference servers (vLLM, TGI) support OpenAI-compatible API formats for drop-in migration.
- Run parallel testing: Run both OpenAI and your self-hosted model in parallel for 1-2 weeks to validate quality and performance.
- Cut over: Once validated, switch fully to your dedicated server and cancel your OpenAI subscription.
Drop-In API Compatibility
GigaGPU servers support OpenAI-compatible API endpoints out of the box. If your application currently calls the OpenAI API, you typically only need to change the base URL and API key to point to your dedicated server. No application code changes required for most integrations.
Start Your Migration
Stop paying per-token to OpenAI. Get a dedicated RTX 5090 server for £89/month and keep 100% of your savings.
