Run Your Own LLMs on Dedicated GPUs
Llama, Mistral, Mixtral, or your custom fine-tuned models. Full control, no per-token pricing, complete data privacy. OpenAI-compatible API included.
Take Control of Your LLM Infrastructure
API pricing works until it doesn\'t. Here\'s why teams switch to self-hosting.
Cost Control
High-volume API usage gets expensive fast. Per-token pricing adds up. Dedicated GPUs give you predictable monthly costs.
Data Privacy
Your data never leaves your infrastructure. Critical for healthcare, legal, finance, and anyone handling sensitive information.
No Rate Limits
No throttling, no waiting in queues, no "please try again later." Your GPUs, your capacity.
Full Customization
Fine-tuned models, custom system prompts, no content restrictions. Configure it exactly how you need.
Consistent Latency
Dedicated capacity means consistent performance. No shared infrastructure affecting your response times.
Model Freedom
Run any model you want. Llama, Mistral, Mixtral, your fine-tuned variants. Switch whenever you want.
LLM Hosting, Managed
We handle everything from deployment to monitoring.
Model Deployment
We deploy your chosen model—Llama, Mistral, Mixtral, or your custom fine-tuned version.
Serving Stack
vLLM, TGI, or Ollama configured for production. Optimized for throughput and latency.
OpenAI-Compatible API
Drop-in replacement for OpenAI's API. Minimal code changes to switch.
GPU Optimization
Quantization, batching, memory optimization. Get the most out of your hardware.
Monitoring
Token throughput, latency percentiles, GPU utilization. Know how your LLM is performing.
Scaling
Add GPUs as usage grows. We handle the infrastructure expansion.
Updates
We handle model updates and infrastructure maintenance. New model version? We deploy it.
LLM Support
Engineers who understand LLM serving, not just generic servers. We know vLLM and TGI.
Models We Deploy
Popular open-source models and your custom variants.
| Model | GPU Requirement | Use Case | Throughput |
|---|---|---|---|
| Llama 3.1 8B | L40S / A100 40GB | General purpose, chat | High throughput, fast |
| Llama 3.1 70B | 2× A100 80GB / H100 | High-quality generation | Moderate throughput |
| Mistral 7B | L40S / A100 40GB | Fast, efficient inference | Very high throughput |
| Mixtral 8x7B | 2× A100 80GB | MoE for diverse tasks | Good balance |
| CodeLlama 34B | A100 80GB / H100 | Code generation | Moderate throughput |
| Your Fine-Tuned Model | Varies by size | Your specific use case | Depends on architecture |
Self-Hosted vs. API Pricing
The math changes at volume. Example with Llama 70B-class model.
| Self-Hosted (Dedicated H100) | API Pricing (Per-Token) | |
|---|---|---|
| Monthly fixed cost | ~$3,000-8,000 | Variable |
| 1M tokens/day cost | Included | ~$3,000-6,000/mo |
| 5M tokens/day cost | Included | ~$15,000-30,000/mo |
| Data privacy | Complete control | Data goes to provider |
| Rate limits | None | Provider limits apply |
| Custom fine-tuning | Full control | Limited options |
* Actual costs vary by model, configuration, and usage pattern. We help you calculate the real numbers for your specific case.
Who Self-Hosts LLMs
Replacing API Costs
Companies spending $10K+/month on OpenAI or Anthropic APIs often save significantly with self-hosted open models. The math changes at volume.
Data-Sensitive Industries
Healthcare, legal, and financial organizations that need data to never leave their infrastructure. Compliance requirements met by design.
Predictable Budgets
Teams that need fixed monthly costs instead of variable per-token pricing. Budget for compute like any other infrastructure.
Custom Applications
Products with specific needs: custom system prompts, domain-tuned models, no content moderation overhead, unique use cases.
From Conversation to Production LLM
Choose Your Model
Pick from popular open models or bring your fine-tuned version. We help you select the right GPU.
We Deploy
We set up vLLM/TGI, configure the model, optimize for your expected load, set up monitoring.
Get API Access
You receive an OpenAI-compatible API endpoint. Point your application at it and start using.
We Manage
Ongoing monitoring, updates, and support. If you need to scale or switch models, we handle it.
Common Questions
Which models can you deploy?
Any model that runs on NVIDIA GPUs—Llama variants, Mistral, Mixtral, Phi, CodeLlama, and custom fine-tuned models. If you can run it locally, we can deploy it at scale.
Is it really cheaper than APIs?
At high volume, usually yes. The breakeven depends on your usage pattern. At 1M+ tokens/day, self-hosting typically saves money. At lower volumes, APIs might be more cost-effective. We can help you do the math.
How does the OpenAI-compatible API work?
vLLM and TGI both offer OpenAI-compatible endpoints. Your existing code that calls OpenAI just needs the base URL changed. Most integrations work with minimal modifications.
What if I need to switch models?
We deploy new models on request. Want to try Llama 3.1 instead of Llama 2? We swap it out. Your fine-tuned version is ready? We deploy it.
Can you help with fine-tuning too?
Yes. Our AI Model Training service covers fine-tuning. Train your model, then we deploy it for inference.
What about model updates and maintenance?
We handle infrastructure updates, security patches, and model deployments. When a new model version comes out that you want, we coordinate the upgrade with minimal downtime.
Explore More
Let\'s Get Your LLM Running
Tell us about your model, expected usage, and requirements. We\'ll help you figure out if self-hosting makes sense—and set it up if it does.