MarsAI
The AI infrastructure
built for scale
Scalable inference APIs and enterprise GPUs — deploy large-scale models on GPU-powered APIs and bare metal compute.
PREMIUM MODELS SOURCED FROM OFFICIAL CLOUDS & VENDORS
Official channels only · no resold keys · open models self-hosted on our own GPUs
—300+ MODELS · 40+ PROVIDERS
Every major model. One endpoint
Premium commercial and open-source models, continuously added — new models need no code change. One base_url calls them all.
01·PLATFORM
One platform. The agent's entire stack
Agents need many models and elastic compute — you used to assemble it all yourself. MarsAI brings the model layer and the compute layer into one account, so you focus on the agent and we handle the foundation.
Frontier passthrough + open-source self-hosting, OpenAI-compatible — change one line of base_url.
Unified auth and billing, multi-model routing, automatic failover — all from one place.
Dedicated machines, zero virtualization overhead — for fine-tuning, self-hosting and private deployment.
REQUEST FLOW
COMPUTE SCALE
Scalable GPU clusters
Multi-region deployment capability
High-bandwidth network infrastructure
Designed for LLM training workloads
Target platform scale — capacity is built out with demand ().
We don't build models. We don't take a token spread. Just the most economical layer between you and AI.
02·MODEL API
Every leading model. One base_url reaches all
We keep adding the latest models from every major provider — new models ship, your code stays the same. OpenAI-compatible, just one line of base_url; multi-model routing and automatic failover for agent-scale calls.
From the moment you connect, requests are routed automatically
/v1/chat/completions03·GPU BARE METAL
Dedicated machines. Zero virtualization overhead
Your own GPU Bare Metal with InfiniBand. For fine-tuning your own models, self-hosting open models, and private deployment. When you need dedicated hardware, this is it.
04·WHY MarsAI
Choose MarsAI. All in one place — cheaper, steadier
Models + compute in one platform, one bill. Four reasons, each verifiable.
Models and compute in one place, one bill, no more stitching vendors.
Premium passes through at the official price; we don't take a token spread.
Up to 60% off open-source, up to 50% off GPUs () — the more you grow, the more you save.
Automatic failover, single-tenant isolation, data never used for training.
05·INTEGRATION
One line. That's the change
Your existing OpenAI SDK runs as-is. The only edit is base_url — nothing else.
from openai import OpenAI client = OpenAI( base_url="https://api.openai.com/v1",+ base_url="https://api.marsai.com/v1", # change only this line api_key="sk-marsai-****",) res = client.chat.completions.create( model="claude-opus-4-8", # same syntax for any model messages=[{"role": "user", "content": "Hello"}],)
Create an account
Email us to get set up.
— about 1 minSwap base_url
One line in your existing code; SDKs and libraries stay the same.
— about 1 minWe take it from here
Routing and failover are automatic; costs are always visible in the console.
— ops on us06·USE CASES
Your agents, in practice
Pick the model or compute that fits each job. Not sure? Start from a recommended setup.
AGENT BACKEND / TOOLS
Agent backends & tool calls
Fast, low-cost models drive multi-step reasoning and tool orchestration at high concurrency.
RAG / KNOWLEDGE
Retrieval-augmented generation (RAG)
Long-context models do Q&A and retrieval over your private docs, ready for your agents.
BATCH / INFERENCE
Batch inference & data processing
Large offline token jobs run on the open-source tier — best cost, full throughput.
SELF-HOST / PRIVATE
Fine-tuning & private deployment
Self-host or fine-tune your own models on dedicated GPUs; data never leaves your environment.
07·PROOF
Legitimate upstream. Verifiable sources
Premium is sourced only from major clouds and vendors' official APIs; open-source is self-hosted on our own GPUs. No resold keys, no unofficial channels — data safety and status kept transparent.
08·ENGINEERING
An infrastructure team that builds for scale
Who runs the platform matters as much as the specs. MarsAI is engineering-driven — the same team designs, builds and operates the infrastructure your workloads land on.
Infrastructure decisions are made by the engineers who operate it — systems designed to hold up under real load, not slideware.
Training and inference at scale drive the architecture: scheduling, failover and throughput come before everything else.
Capacity grows node by node — from a single dedicated machine to multi-node clusters, with no re-platforming on the way up.
NVLink inside the node, high-bandwidth interconnect across nodes — built so multi-GPU jobs are never starved for data.
09·COMPLIANCE
Security & compliance. The key facts in one place
How your data is used and encrypted, whether the operating entity is legitimate, how billing and audit work — everything you'd check before adopting, in one place.
- Operator
- MarsAI LIMITED — a Colorado corporation (Denver, USA)
- Data handling
- Never used for training / retention scope stated in the Privacy Policy
- Transport & key management
- All traffic encrypted with TLS / upstream keys kept confidential
- Authentication
- Passwordless sign-in via passkeys (WebAuthn / FIDO2) supported
- Audit & permissions
- Actions and usage logged / per-API-key permission and budget controls
- Commercial terms
- Billed in USD, invoices available / no minimum, no cancellation fee
- Policies
- Terms of Service / Privacy Policy published
- Pre-contract inquiries
- MarsAI000222@gmail.com
10·FAQ
Frequently asked questions
Q1Do you train your own models? Are you a reseller?
Neither. MarsAI doesn't own or train models — Premium is sourced only from major clouds (Amazon Bedrock, Google Vertex AI, Azure) and official vendor APIs, open models are self-hosted on our own GPUs, never resold keys.
Q2Are Premium models pricier than going direct?
No — official price, 0% markup. What you gain is a unified API, one bill, and automatic failover, not a markup.
Q3Why are open-source models cheaper?
Self-hosted, optimized inference. Llama / Qwen / DeepSeek run on our own GPUs, cutting out the middleman — up to 60% cheaper than comparable closed models ().
Q4How is GPU bare metal billed?
Hourly or monthly reserved. Dedicated machines, no virtualization overhead; H100 from ~$1.99/GPU-hr, cheaper monthly — see the GPU Bare Metal page.
Q5Can I use my existing OpenAI SDK code as-is?
Yes. Change one line of base_url and your existing code, SDKs, and libraries keep working — Claude, Gemini, and open models too.
Q6Is the data I send used for training?
Never used for training. Prompts and outputs are not used for training or retained; logs are limited to billing and incident handling, per the Privacy Policy.
START NOW
Need GPU compute resources?
Submit your workload requirements and we will provision infrastructure.