INSTANT LOADING
Restore model state in milliseconds with our innovative snapshot technology. No more waiting for models to initialize.
The Serverless Engine
for Ultra-Efficient AI Inference
Powered by our AI-Native OS Architecture
<2sCOLD START
90%+GPU UTILIZATION
30+MODELS/NODE
Currently piloting with leading infra teams
KEY FEATURES
HIGH EFFICIENCY
Achieve 90%+ GPU utilization by eliminating idle resources and optimizing memory usage across multiple models.
DEVELOPER FRIENDLY
Simple API with seamless integration. Deploy models with just a few lines of code and zero configuration.
HOW IT WORKS
SNAPSHOT CREATION
We capture the entire GPU memory state of your model after initialization and training.
OPTIMIZED STORAGE
The snapshots are compressed and stored efficiently in our distributed storage system.
INSTANT RESTORATION
When needed, the exact GPU memory state is instantly restored, eliminating initialization time.
# Traditional approach: 2-10+ minutes cold start
api.openai.com/v1/chat/completions# InferX approach: <2 seconds cold start
✓ Just change the endpoint - no code changes needed!api.inferx.net/v1/chat/completionsPERFORMANCE METRICS
Cold Start Comparison
Traditional30s
InferX2s
15x faster cold starts
GPU Utilization
90%InferX
InferX (90%) · Unused (10%)
DROP-IN REPLACEMENT
No code changes required. Just switch your API endpoint.
Traditional Inference
2-10+ minutes cold start
# Your existing code
curl -X POST https://api.openai.com/v1/chat/completions \
-H "Authorization: Bearer sk-..." \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-4",
"messages": [{"role": "user", "content": "Hello"}]
}'Model loading: 2-10+ minutes
Low GPU utilization
Limited models per node
InferX API
<2 seconds cold start
# Just change the endpoint
curl -X POST https://api.inferx.net/v1/chat/completions \
-H "Authorization: Bearer your-api-key" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-4",
"messages": [{"role": "user", "content": "Hello"}]
}'Instant model access: <2s
90%+ GPU utilization
30+ models per node
OpenAI-Compatible REST API
Works with your existing applications, SDKs, and tools. No code changes, no new libraries, no complex integrations.
HOW INFERX DELIVERS INSTANT INFERENCE
Our proprietary technology eliminates cold start delays completely, enabling on-demand AI inference with near-zero latency.
01
SNAPSHOT CREATION
InferX captures the full GPU memory and execution state of your model after initialization — including weights, buffers, and runtime context.
02
OPTIMIZED STORAGE
Snapshots are compressed, versioned, and stored across ultra-fast tiers in our distributed storage layer — ready for instant reuse.
03
INSTANT RESTORATION
On demand, InferX restores the exact GPU state in under 2 seconds — bypassing reloading, reinitialization, and warmup entirely.
THE MODEL SERVE PROCESS
1
Upload & Deploy
Users upload a containerized model (e.g. vLLM or custom runtime), and InferX returns a unique endpoint.
2
Submit Requests
Users send inference requests using the provided URL.
3
Intelligent Scaling
If a warm instance is available, the request is processed immediately.
4
Lightning-Fast Cold Start
If no warm instance exists, InferX cold-starts a GPU instance in under 2 seconds, ensuring minimal latency.
Want to test this flow with your own model?
Request Pilot Access →Model Serving Pipeline
KEY FEATURES
InferX delivers unprecedented performance and efficiency for AI inference workloads.
Ultra Fast Cold Start
Cold start GPU-based inference in under 2 seconds for large models (12B+).
GPU Slicing
Allocate only a fraction of a GPU (e.g., 1/3 GPU) per model to efficiently run multiple workloads in parallel.
Super High Model Density
Serve hundreds of models on a single node, maximizing hardware utilization.
80+% GPU Utilization
Based on Just-In-Time scaling and super high deployment density, achieving 80% GPU utilization.
Lambda-like AI Serving
Automatically scale AI inference workloads with on-demand execution.
Optimized Performance
Reduce latency, improve cost efficiency, and streamline AI inference at scale.
PLATFORM ARCHITECTURE
Our AI-Native OS architecture enables instant model loading and 90% GPU utilization.
ARCHITECTURE COMPONENTS
Click on components to explore how they work
Gateway
Routes inference requests to appropriate containers and manages the API interface for clients.
Scheduler
Optimizes resource allocation and determines when to warm up or scale down inference containers.
Node Agent
Manages container lifecycle and handles the snapshot restoration process on GPU nodes.
Container Runtime
Executes inference operations inside isolated containers with optimized GPU access.
Snapshot BlobStore
Stores model snapshots which contain the complete memory state of initialized models for rapid loading.
InferX Platform Architecture
Click components to learn more
KEY INNOVATIONS:
Instant Loading
Our snapshot technology eliminates model initialization time, enabling sub-2 second cold starts.
Multi-tenancy
Secure isolation between customer workloads with GPU sharing enables up to 90% GPU utilization.
Serverless Scaling
Automatic scaling based on demand with zero management overhead.
COLD START PROFILING
Snapshot cold start profiling
KEY ADVANTAGES:
- •Total cold start time of less than 5 seconds compared to 30+ seconds for traditional approaches
- •Minimal snapshot metadata size (200-400 MB) enables rapid deployment
- •Consistent sub-10ms response times after initial load
Our low-level runtime instantly captures and restores model state, enabling high-density deployment and lightning-fast model swaps.
SECURE CONTAINER RUNTIME
Multi-tenant Secure Container Runtime
InferX's secure multi-tenant architecture ensures full isolation between customer workloads while maximizing GPU utilization. We achieve this through low-level containerization and memory-level enforcement — without sacrificing performance.
1
Compute Isolation
Complete workload isolation ensures security and prevents cross-contamination between models.
2
Network Isolation: VPC (TCP/IP)
Separate virtual network environments for each customer's inference workloads.
3
GPU Isolation
NCCL library interface with NVLink (intra-node) and RDMA (inter-node) provides secure access to GPU resources without compromising performance.
This allows cloud providers and enterprises to safely run multiple LLMs on shared hardware — securely and efficiently.
FREQUENTLY ASKED QUESTIONS
Get answers to common questions about InferX's serverless AI inference platform.