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LLM Cost Calculator

Compare API Token Costs vs Self-Hosted GPU Servers

See exactly how much you could save by switching from OpenAI, Anthropic or Google API billing to a dedicated GPU server with flat monthly pricing — no per-token fees, no usage caps.

How Much Could You Save by Self-Hosting?

API token fees add up fast. If you’re running production LLM workloads — chatbots, RAG pipelines, coding assistants, batch processing — a dedicated GPU server with flat monthly pricing can be dramatically cheaper than per-token billing.

Use the calculator below to compare your current API spend against the flat cost of a GigaGPU dedicated GPU server. Select your model, enter your daily token volume, and see the real numbers — including monthly savings, annual savings, and a visual cost comparison.

Up to 95%
cheaper than API billing at production volumes
∞
Unlimited Tokens
flat monthly price, no per-token or per-request fees
Any Model
LLaMA, DeepSeek, Mistral, Qwen — full root access
⚡

LLM Cost Calculator

Monthly API Cost
—
per-token billing
GigaGPU Monthly Cost
—
flat rate, unlimited tokens
Monthly Savings
—
with self-hosting
Cost Comparison
API
GigaGPU

How the Calculator Works

We compare per-token API pricing against GigaGPU’s flat-rate dedicated GPU servers so you can see exactly where self-hosting pays for itself.

1

Choose a Model

Select the commercial API model you’re currently using or evaluating. We pull live pricing per million input/output tokens.

2

Enter Your Usage

Estimate your daily input and output tokens. Use the quick presets or type your exact volume for accurate results.

3

Pick a GPU Plan

Select a GigaGPU dedicated server. You get full root access, unlimited tokens, and flat monthly pricing with no surprises.

4

See Your Savings

The calculator shows your monthly API spend vs the flat GPU cost, plus the percentage saved and annual total savings.

API Pricing Reference

Current per-million-token pricing for popular commercial LLM APIs. All prices in USD. Self-hosted models have no per-token cost — just the flat server fee.

Model Provider Input / 1M Tokens Output / 1M Tokens
GPT-4oOpenAI$2.50$10.00
GPT-4o MiniOpenAI$0.15$0.60
o3-miniOpenAI$1.10$4.40
GPT-4.1OpenAI$2.00$8.00
GPT-4.1 miniOpenAI$0.40$1.60
GPT-4.1 nanoOpenAI$0.10$0.40
Claude Sonnet 4Anthropic$3.00$15.00
Claude Haiku 3.5Anthropic$0.80$4.00
Claude Opus 4Anthropic$15.00$75.00
Gemini 2.5 ProGoogle$1.25$5.00
Gemini 2.5 FlashGoogle$0.15$0.60

Frequently Asked Questions

Not always. For very low usage — a few hundred requests per day — API pricing can be more economical because you only pay for what you use. But once you exceed roughly a few hundred thousand tokens per day, the flat cost of a dedicated GPU server almost always works out cheaper, and the gap widens rapidly as volume increases. The calculator above will show you exactly where the breakeven sits for your workload.
Any open-source or open-weight model you like: LLaMA 3, DeepSeek, Mistral, Qwen, Phi, Gemma, and hundreds more. You get full root access and can use inference frameworks such as vLLM, Ollama, TGI, or llama.cpp. There are no vendor lock-ins and no model restrictions.
The API prices shown are based on published list rates and are updated regularly. Your actual costs may vary based on cached token discounts, batch API pricing, committed-use agreements, or prompt caching. The GigaGPU server price is exact — it’s a flat monthly fee with no hidden charges. The calculator gives you a reliable ballpark comparison; for a precise quote, contact our sales team.
The GigaGPU monthly price includes the server hardware, GPU, 128 GB RAM, NVMe storage, a 1Gbps port, and 99.9% uptime SLA. You may choose to add extra storage or bandwidth, but for most workloads the base configuration is all you need. There are no setup fees.
Absolutely. Because you have full root access, you can serve multiple models simultaneously using vLLM or Ollama. Many customers run a primary large model alongside smaller specialist models — all on the same server, all included in the flat monthly price.
It depends on the model size and your concurrency needs. An RTX 4090 can serve a quantised 70B model at roughly 20–40 tokens/second. An H100 handles much larger models at higher throughput. Check our GPU benchmark page for tokens-per-second data, or contact sales for a recommendation based on your exact requirements.

Available on all servers

  • 1Gbps Port
  • NVMe Storage
  • 128GB DDR4/DDR5
  • Any OS
  • 99.9% Uptime
  • Root/Admin Access

Our dedicated GPU servers provide full hardware resources and a dedicated GPU card, ensuring unmatched performance and privacy. Run unlimited LLM inference with zero per-token fees — one flat monthly price, no surprises.

Get in Touch

Not sure which GPU plan matches your workload? Our team can help you choose the right server based on your model sizes, throughput requirements, and budget.

Contact Sales →

Or browse the knowledgebase for setup guides on Ollama, vLLM, and more.

Stop Paying Per Token

Flat monthly pricing. Full GPU resources. UK data centre. Run any open-source model with unlimited inference.

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