Deploy Your LLMs
in Production
Without Breaking the Bank
Run Llama 3, Mistral, or Custom Models with Docker + Auto-Scaling + Redis Caching. EU-hosted for GDPR compliance. Sub-30s cold starts. Perfect for AI developers and startups.Starting at €0.001/1K tokens - pay only for inference
Trusted by freelancers across Europe
Memory usage spike detected. Suggested: increase allocation to 512MB.
LLM Deployment Shouldn't Be This Hard
Stop fighting infrastructure. Start deploying production-ready LLMs in minutes.
Deploy Production LLMs in 3 Simple Steps
Connect Your Model
- HuggingFace Hub integration
- Custom Docker images
- Automatic dependency detection
- Quantization support (int4, int8, bfloat16)
Configure Resources
- GPU Type: T4 (budget) | A100 (performance)
- Auto-scaling rules
- Redis caching strategy (FREE)
- Environment variables
Deploy & Scale
- Auto-generated API endpoints
- Real-time monitoring dashboard
- Pay only for actual inference
- Scale to zero when idle
Deploy in 3 Lines of Code
From model to production API in minutes, not days
# Deploy Mistral-7B in 3 lines
import chitacloud as cc
model = cc.deploy_model(
model_id="mistralai/Mistral-7B-Instruct-v0.2",
gpu_type="T4",
quantization="int4",
auto_scale=True
)
# Inference
response = model.generate(
prompt="Explain quantum computing",
max_tokens=512
)
print(response.text)
# Auto-generated API endpoint: https://my-api.chitacloud.dev/v1/mistral-7b-abc123Everything You Need for Production LLMs
Performance
Model warming + predictive scaling
Scale to zero when idle
Response caching included FREE
Shared resources for small models
Privacy & Security
Your model weights stay private
GDPR compliant by default
Model data encrypted at rest
Automatic sensitive data masking
Developer Experience
Bring your own container
One-click from Hub
Prometheus + Grafana dashboards
chitac ml deploy <model>
60% Cheaper Than Alternatives
Same performance, better privacy, lower cost
| Provider | Cold Start | Cost/1K tokens | EU Hosting | Redis Cache |
|---|---|---|---|---|
| Chita Cloud | <30s | €0.001 | Yes | Included |
| Replicate | 60s+ | $0.0015 | No | Extra |
| Modal | 45s | $0.002 | No | Extra |
| AWS SageMaker | 90s+ | $0.003+ | Optional | Extra |
Perfect For Every Use Case
AI Startups
Deploy custom fine-tuned models without infrastructure headaches
Researchers
Experiment with multiple models without breaking budget
Enterprises
GDPR-compliant AI with audit logs and SLA guarantees
Indie Developers
Build AI features without AWS complexity
Technical Specifications
Supported Models
- ✓Llama 2 & 3 (all variants)
- ✓Mistral 7B/8x7B
- ✓GPT-Neo/GPT-J
- ✓Falcon
- ✓Custom fine-tuned models
GPU Options
- ✓T4 (16GB VRAM) - Budget-friendly
- ✓A100 (40GB VRAM) - High performance
- ✓A100 (80GB VRAM) - Large models
- ✓Auto-scaling based on demand
Frameworks
- ✓PyTorch
- ✓TensorFlow
- ✓Transformers (HuggingFace)
- ✓vLLM
- ✓Text Generation Inference (TGI)
Quantization
- ✓int4, int8, bfloat16
- ✓LoRA/QLoRA support
- ✓GPTQ quantization
- ✓AWQ quantization
- ✓Custom quantization configs
Frequently Asked Questions
How does pricing work?
Pay-per-inference model: €0.001/1K tokens. Free tier includes 10K tokens/month. Professional tier: 100K tokens for €24/month.
Do I need to manage infrastructure?
No! We handle GPU allocation, auto-scaling, monitoring, and maintenance. You just deploy your model and use the API.
Can I use my own fine-tuned models?
Yes! Upload from HuggingFace Hub, provide a custom Docker image, or connect your GitHub repository with model weights.
What about data privacy?
Zero-log guarantee: we never store your prompts or model outputs. All data is encrypted at rest and in transit. EU-hosted for GDPR compliance.
How fast are cold starts?
Optimized to <30s with model warming, predictive scaling, and smart caching. Most popular models are pre-loaded.
Can I scale to zero?
Yes! Models automatically shut down after 15 minutes of inactivity. You only pay for actual inference time.
Ready to Deploy Your First LLM?
Join hundreds of AI developers deploying LLMs on Chita Cloud with Redis cache included and transparent pricing.