DCS  /  Compute  /  Overview

Compute overview

Rent a GPU by the second · or earn from your own. Real-time worker + renter state.

Active instances
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Workers online
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Earned (24h)
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Active instances

InstanceGPUSourceRegionUptimeRateStatusActions
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GPU pools

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Loading 47 GPUs from RunPod + Vast.ai…
🔥
PyTorch 2.4CUDA 12.1
🆕
PyTorch 2.8CUDA 12.4
🧩
ComfyUISDXL ready
🐧
Ubuntu 22.04bare
🤖
Small LLM7B-13B
🧠
Large LLM70B+
🎨
Image genSD / Flux
🎬
3D / videorender farm

My workers · earn

WorkerTierStatusRate
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1
Install the worker$ pip install trd-worker
2
Register your machine$ trd-worker login
3
Start earning$ trd-worker start

Earnings total

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Earning tiers

Entry
RTX 3060 / 12 GB / 7B
40 cr/hr
Mid
RTX 4070 · M3 Pro
60 cr/hr
High
RTX 4090 · M3 Max
120 cr/hr
Datacenter
A100 / H100
240 cr/hr

1,000 credits ≈ $8.00 · redeem as build credits or queue a Stripe payout.

Recent receipts

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Kubernetes

Managed clusters on rented GPUs.

Kubernetes

One-click GKE / EKS / k3s clusters provisioned on rented GPUs. Coming soon — join the early access list to get notified.

Redeem credits

Convert earned credits to build credits or cash.

Redeem credits

Current balance: cr

Convert earned compute credits into build credits (instant) or queue a Stripe cash payout (settled monthly). Minimum 1,000 cr per redemption.

Recent redemptions

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Benchmarks

Publish your GPU's tier rating.

Benchmarks

Run the trd-worker benchmark suite to publish your GPU's tier rating. Tier rating sets your default earn rate.

Usage

Detailed per-instance and per-template breakdown.

Usage

Detailed per-hour / per-instance / per-template usage breakdown. Populates after your first rental.

Alerts

Email and webhook notifications.

Alerts

Email + webhook alerts for worker offline, instance crashed, balance low, payout failed. No alert channels configured.

Billing

Compute charges roll up to your main DCS account.

Billing

Compute charges roll up to your main DCS account on app.dcsai.ai.

Settings

Profile and sign-in are managed centrally.

Settings

Profile + sign-in settings are managed from the main DCS account on app.dcsai.ai.

Virtual Machines

Launch a long-running VM on the DCS GPU fleet. Cluster sizes: ×4 for consumer / pro, ×8 for HGX/SXM data-center nodes. Per-second billing.

1Pick GPU + cluster size
2Configure VM

1. Choose your use-case

All workloadsShow every GPU
🤖
Small LLM7-13B inference, RAG
🧠
Large LLM70B+ models, training
🎨
Image genSDXL, Flux, ComfyUI
🎬
3D / renderBlender, Unreal, OctaneRender
💸
CheapestDev, small jobs

2. Pick a GPU

VRAM: Cluster:
Loading GPUs from RunPod + Vast.ai…
Pick a GPU to continue

Workloads

Batch jobs, scheduled runs, and long-running agent tasks. Distinct from short-lived instances (which spin up per request) and Virtual Machines (which run continuously). Queue-based execution with auto-retry + cost cap.

Active workloads

Workload queue ships in Phase 4

Submit YAML/JSON job specs, set retry policy + cost cap, watch progress in real time. Backed by the same dispatch layer as instances but with persistence + scheduling.

View running instances →

Browse agents

641 pre-built agents across 14 categories. Verified, community, and experimental tiers. Each agent is signed + auditable.

Agent catalog

📚

Agent catalog opens in v1.1

Browse, fork, or install any of the 641 catalog agents directly inside Compute. Same source as app.dcsai.ai/agent-catalog.

Read the Agents whitepaper →

Publish an agent

Build, test, sign, and ship an agent to the DCS catalog. 70% publisher revenue share on paid agents.

Publisher onboarding

📝

Publisher flow opens in v1.1

agent.yaml validator, sample test runs, signed publish to the catalog. Stripe Connect for revenue share. Until then, use the Agent Studio.

Open Agent Studio →

Audit log

Tamper-evident record of every action: deploys, stops, payouts, settings changes. R+1 timestamp + R+2 signature.

Recent activity

🛡

Live audit log streams in Phase 4

Every billable + administrative action gets an R+1/+2 signed receipt. Exportable as audit bundle for regulators, accountants, lawyers.

View Receipts in the meantime →