OpenAI Pricing Reality Check
OpenAI’s API pricing looks manageable at low volume but scales linearly. At 100M+ tokens per month, you are paying thousands for something you could run on your own dedicated GPU server at a fraction of the cost. Meta’s LLaMA 3 matches or exceeds GPT-4o on many benchmarks, and it is completely free to run on your own hardware.
Here is what OpenAI charges across their current model lineup:
| OpenAI Model | Input (per 1M) | Output (per 1M) | Blended Rate |
|---|---|---|---|
| GPT-4o | $2.50 | $10.00 | ~$5.50 |
| GPT-4o Mini | $0.15 | $0.60 | ~$0.33 |
| GPT-4 Turbo | $10.00 | $30.00 | ~$18.00 |
Compare these against self-hosting alternatives using our GPU vs API cost comparison tool.
LLaMA 3 Hosting Costs
LLaMA 3 is fully open-source with no per-token fees. Your only cost is the server hardware. Here are the recommended configurations for each model size:
| LLaMA 3 Model | GPU Setup | Monthly Cost | Throughput |
|---|---|---|---|
| LLaMA 3 8B | 1x RTX 5090 32 GB | $149/mo | ~100-130 tok/s |
| LLaMA 3 8B | 1x RTX 3090 24GB | $99/mo | ~70-90 tok/s |
| LLaMA 3 70B | 2x RTX 6000 Pro 96 GB | $599/mo | ~40-65 tok/s |
| LLaMA 3 70B | 4x RTX 6000 Pro 96 GB | $899/mo | ~80-120 tok/s |
For detailed GPU-level cost analysis, see our cost per 1M tokens: LLaMA 3 by GPU breakdown. Serving is handled through vLLM for production or Ollama for development setups.
Head-to-Head Cost Comparison
We will break this into two matchups: budget tier (LLaMA 3 8B vs GPT-4o Mini) and premium tier (LLaMA 3 70B vs GPT-4o). These are the most common comparisons teams face when deciding between OpenAI and self-hosted open-source models.
LLaMA 3 8B vs GPT-4o Mini
| Monthly Tokens | GPT-4o Mini ($0.33/1M) | LLaMA 3 8B (RTX 5090) | Winner |
|---|---|---|---|
| 1M | $0.33 | $149 | API |
| 100M | $33 | $149 | API |
| 500M | $165 | $149 | Self-hosted ($16 saved) |
| 1B | $330 | $149 | Self-hosted ($181 saved, 55%) |
| 5B | $1,650 | $149 | Self-hosted ($1,501 saved, 91%) |
| 10B | $3,300 | $149 | Self-hosted ($3,151 saved, 95%) |
GPT-4o Mini is cheap, but LLaMA 3 8B is even cheaper at scale. The break-even sits at approximately 450M tokens per month. Above that, every token is essentially free.
LLaMA 3 70B vs GPT-4o
| Monthly Tokens | GPT-4o ($5.50/1M) | LLaMA 3 70B (2x RTX 6000 Pro) | Savings |
|---|---|---|---|
| 1M | $5.50 | $599 | API wins |
| 50M | $275 | $599 | API wins |
| 100M | $550 | $599 | Roughly even |
| 150M | $825 | $599 | $226 saved (27%) |
| 500M | $2,750 | $599 | $2,151 saved (78%) |
| 1B | $5,500 | $599 | $4,901 saved (89%) |
The LLaMA 3 70B vs GPT-4o break-even hits at 109M tokens per month. At 1B tokens, you save nearly $4,900 per month, or $58,800 annually. Run the numbers for your exact workload with our LLM Cost Calculator.
Total Cost of Ownership
The raw token cost is only part of the picture. Our TCO analysis shows that self-hosting on dedicated hardware also eliminates several hidden costs:
- Rate limit workarounds – no need for queuing systems or request retries
- Compliance overhead – private hosting simplifies GDPR and data residency requirements
- Multi-model flexibility – run LLaMA, DeepSeek, Mistral, or any other model on the same hardware
- Vendor independence – no risk of sudden price hikes or API deprecation
For a comprehensive view of all API providers, read our is self-hosting LLMs cheaper than APIs deep-dive and the Claude API vs dedicated GPU comparison.
Making the Switch
Migrating from OpenAI to self-hosted LLaMA 3 is simpler than most teams expect. vLLM provides an OpenAI-compatible API endpoint, so your application code changes are minimal. Follow our self-host LLM guide for a step-by-step walkthrough.
Choose the cheapest GPU that meets your throughput requirements, and consider our RTX 3090 vs RTX 5090 comparison for budget-friendly options. For high-throughput needs, multi-GPU clusters provide linear scaling.
Run LLaMA 3 on Your Own Server
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