Currently in Private Beta

Serverless Custom Model Deployment & GPU Inference Without Cold Starts

Deploy, manage, and scale any AI model—open-source or proprietary—in a private, high-performance environment with transparent, flexible pricing.

The AI Infrastructure Challenge

High Cost & Complexity

Owning the stack means sourcing GPUs, managing storage, and operating around-the-clock capacity. Public API pricing becomes difficult to justify once private workloads ramp.

Data Security & Compliance

Sensitive prompts, weights, and outputs cannot casually transit shared endpoints. Teams need private network boundaries, access controls, and infrastructure they can reason about.

Unpredictable Performance

Large checkpoints do not behave like stateless web handlers. Image pulls, cold boot cycles, and remote storage bottlenecks introduce latency exactly where production systems feel it most.

Managed Hardware Layer for Model Serving

You ship the model. We handle the GPU nodes, storage path, and private serving layer beneath it.

No image pulls
No container warmup
No Kubernetes to manage
No VM boot cycles

Built for demanding inference workloads

Dedicated infrastructure for production-grade model serving
Private deployment environments with strong operational controls
Fast, reliable performance for teams shipping serious workloads
A simple API experience on top of managed infrastructure

From a Hugging Face Repo to Production in Minutes

Get Started

1. Setup Your Model Repository

Prepare your Hugging Face repo—no complex setup or configuration needed.

Example model: openai/gpt-oss-120b

Text Generation
120B parameters
Updated Aug 26
4.4M stars
4.17k downloads

2. Deploy to SynapsAI Cloud

Deploy your custom model hosting pipeline to SynapsAI Cloud in minutes.

3. Run Low-Latency Inference

Access your model via a private API with familiar OpenAI-style SDK integration.

from synapsai import SynapsAI

client = SynapsAI()
res = client.chat.completions.create(
    model="..."
)

4. Monitor and Iterate

Monitor LLM hosting usage and logs in real-time with complete visibility and analytics.

Unprecedented Model Load Times

Our platform achieves remarkable checkpoint loading speeds for BF16/FP16 models. As we scale, these times will improve further.

Model Framework	Load Time (Seconds)
OPT 2.7B	0.5s
LLaMA-2 7B	1.0s
OPT 6.7B	1.0s
Falcon 7B	1.1s
LLaMA-2 13B	1.9s
OPT 13B	2.0s
OPT 30B	4.5s
Falcon 40B	6.2s
LLaMA-2 70B	10.3s

*SynapsAI Cloud load times (excludes a typical ~3s allocation/warmup required prior to model loading). Lower is better. Performance continually improving as we scale.

The SynapsAI Cloud Advantage

Blazing-Fast Model Deployment

Immediate provisioning on H100/H200 clusters. Full setup handled automatically.

Flexible Billing

Choose per-token or hourly. Smart cost controls ensure predictable and optimized spending.

Rapid Model Loading

Local NVMe and persistent SSD storage deliver model loading at scale.

Cost Monitoring

Real-time dashboards show token usage, user-level billing, and project costs.

Beyond LLMs: Versatile Model Support

SynapsAI Cloud hosts a diverse array of AI capabilities, not just Large Language Models.

Text Classification
Text-to-Image
Image-to-Text
Text-to-Speech
Speech-to-Text
Text-to-Video
Video-to-Text
Text-to-Audio
Audio-to-Text

See the full list of supported pipelines

Flexible token-based billing available for LLMs.

Focus on Innovation, Not Infrastructure

SynapsAI Cloud removes the barriers to deploying private, high-value AI models at scale by combining managed infrastructure with enterprise security and predictable economics.

Get Started Today

We have a lot yet to come

We're constantly building new features and improving performance — tell us what you'd like to see next.