AI Infrastructure
Without Idle GPU Costs
Run inference, build knowledge bases from your documents, and access frontier models — all through one API. Pay only when you use it. No GPUs to rent, no idle hours to cover.
AI Developers
One API for hosted & frontier models.
- Hosted Qwen3, BGE-M3, FLUX + partner models
- Build chatbots from your PDFs — free RAG
- Pay per token, no idle GPU costs
- 🎁$1.00 free credit on signup. No credit card required.
Run a Node
Power the network. Earn per token served.
- Distributed inference, no central GPU farm
- Python CLI worker — one command start
- Earnings paid per token your GPU generates
Provider onboarding is invite-only right now. Email us your GPU specs to join the waitlist.
chirantan@lexoratechnologies.com →Open-weight models,
live on the network.
Drop-in OpenAI-compatible IDs. Live models are available now at beta pricing — pipeline models are deploying soon.
Qwen3 8B
Qwen/Qwen3-8B
Fast reasoning model on the network. Ideal for chat, code, classification, and high-throughput integrations.
FLUX.1 schnell
black-forest-labs/FLUX.1-schnell
Guidance-free 4-step image generation. Best speed-to-quality ratio for real-time image apps.
Llama 3.1 8B Instruct
meta-llama/Llama-3.1-8B-Instruct
Balanced performance and cost. Strong on reasoning, code, and long-context tasks.
Llama 3.1 70B Instruct
meta-llama/Llama-3.1-70B-Instruct
Flagship open-weight LLM. Near-GPT-4 quality at a fraction of the cost — routes to cluster-grade nodes.
FLUX.1 dev
black-forest-labs/FLUX.1-dev
Guidance-distilled FLUX for higher prompt adherence. 1024 px output, tunable CFG scale.
Stable Diffusion XL
stabilityai/stable-diffusion-xl-base-1.0
Industry-standard SDXL base model. Wide ecosystem of LoRAs, ControlNets, and refiners.
Up to 50% cheaper than centralized providers
Beta pricing — $0.04 / 1M tokens for 3B · $0.002 / image for FLUX schnell.
Full pricing details and model specs →
View pricing pageProduction infrastructure,
decentralized edge.
NestJS orchestrator, Redis node registry, PostgreSQL job ledger, and a Python vLLM worker — open source, self-hostable.
OpenAI-Compatible API
Drop-in replacement for the OpenAI SDK. Change one line — the base URL — and slash your inference bill in half.
Global Node Network
Jobs are routed to the best-ranked node by reputation score, available VRAM, and network latency — in real time.
50% Cost Reduction
Consumer GPUs have zero infrastructure overhead. Savings pass directly to you, visible in the live telemetry widget.
JWT-Authenticated Nodes
Worker nodes authenticate with hardware-fingerprint-bound JWTs. Reputation slashing for misbehaving providers.
Fault-Tolerant Dispatch
Node goes offline mid-generation? The orchestrator detects it in 30s, cancels the SSE stream, and re-dispatches automatically.
Earn from Idle VRAM
Run the Python CLI worker on any CUDA GPU. Get paid per token. No cloud setup, no committed capacity.
Train your chatbot
today. For free.
Upload any document. BGE-M3 embeds it. Qwen3 reads it and answers your questions with citations — no fine-tuning, no GPU bill, no waiting. It just works.
Upload your docs
PDF or plain text, up to 50 MB. Your contracts, manuals, research papers — anything with text.
BGE-M3 indexes it
State-of-the-art multilingual embeddings chunk and encode your content into a private vector store. Runs on the network — zero cost to you.
Qwen3 answers from it
Every question retrieves the exact relevant passages first. Qwen3 8B reads them and replies with cited page numbers — not guesses from training data.
Free tier included · No credit card needed to start
Every token traced
to its source GPU.
The network is radically transparent. When you use the sandbox below, you see the exact node ID, GPU model, tokens-per-second, and cost savings for your specific inference request — all streamed live.
- Node ID piped via SSE headers
- GPU model on active worker
- Live TPS from stream timing
- Cost delta vs. OpenAI GPT-4
Try it. Watch the node do the work.
This prompt runs against the real orchestrator. The telemetry panel shows which node answered and how fast it generated.
Live inference on decentralized GPUs
Tokens stream directly from a worker node
Inference routed to the best available GPU node in the Lexora network.
vs. OpenAI GPT-4
Live telemetry piped from the selected worker node via SSE headers & stream events.
Change two lines.
Cut your bill in half.
The Lexora network speaks the OpenAI protocol natively. Point your existing SDK at our endpoint, swap the key, and start saving. Zero refactoring.
Get API Key1import OpenAI from "openai";2 3const client = new OpenAI({4 baseURL: "https://api.lexora.network/v1",5 apiKey: process.env.LEXORA_API_KEY,6});7 8const stream = client.chat.completions.stream({9 model: "mistralai/Mistral-7B-Instruct-v0.2",10 messages: [{ role: "user", content: "Hello" }],11});12 13for await (const chunk of stream) {14 process.stdout.write(chunk.choices[0]?.delta?.content ?? "");15}