Run any agent. For seconds or for days
Publish, access, and operate workflow-specific Agents, backed by GMI's model access, same-network inference, and managed compute
One runtime, one storefront, flexible infrastructure
200+
Models available in one key
30×
Longer sessions than a 24-hour sandbox
Marketplace
Where enterprise buyers deploy
1 invoice
Runtime + models + billing
Not an agent catalog
A launchpad for Agents
Most teams do not want another directory of demos. They want an AI agent that works, and a clear path to deploy, list, and operate it in production. GMI Agentbox is where workflow-specific Agents get packaged, distributed, and monetized at scale, with unified model access, inference, and compute behind them
Access or deploy, in one platform
Access
Explore production-ready Agents, compare capabilities and runtime resources, and access the right workflow faster
Deploy
Deploy privately, validate the runtime, then publish to the Agentbox when you're ready
Use GMI your way
Some teams need compute. Some need model access through a hosted API. Others need both. GMI Agentbox supports all three adoption paths, whether you're deploying an enterprise AI agent, building a customer-facing agent product, or scaling an internal workflow
Option 01
Compute
GMI handles deployment, hosting, and runtime operations
You bring your own model layer
Option 02
Models
GMI provides model access with 200+ models on one API key
You manage your own runtime environment
Option 03
Compute + Models
GMI handles model access, compute, and operations
One unified system end-to-end
Whether you are packaging a workflow into a customer-facing Agent or scaling an internal deployment, GMI supports modular adoption, not a one-size-fits-all stack
Built for every workload · From fast tasks to always-on agents
Enterprises run agents across the full spectrum, short bursts, hours-long jobs, and workloads that never go offline, GMI Agentbox runs all three on one platform, with same-network inference behind every call
Ephemeral · seconds
Spin up and tear down in seconds, elastic capacity that scales with demand
Use cases
Coding agents, overnight batch jobs, RL training environments
Long-running · minutes to hours
Persistent state across multi-step jobs, with low-latency model calls
Use cases
Deep research, document pipelines, multi-model routing
Always-on · 24/7
Voice / real-time agents Stays online with memory and identity across every session.
Use cases
Digital workers, monitoring agents, hosted MCP gateways
From sub-second tasks to agents that never stop, one platform covers the workloads where most teams need to stitch several together
Same agent performance.
Far less infrastructure cost.
$432
10 agents · 2 vCPU · 4 GiB · 730 hrs · monthly
- GMI's own GPU cloud — no middleman margin to price in.
- Calls stay on GMI's own network. Model access and inference, one invoice.
- Isolated by default — no dedicated-cluster premium.
- Agentbox$432BaselineInference included
- Vercel Sandbox$8061.9× Agentbox+ external API
- E2B$1,2092.8× Agentbox+ external API
- Daytona$1,2092.8× Agentbox+ external API
- Modal$1,7424.0× Agentbox+ external API
Compute at provider list prices, 2 vCPU · 4 GiB per agent. Inference on Agentbox runs on GMI's own models; elsewhere it arrives as a separate API bill.
Creation, egress, and snapshot fees excluded.
Deploy first. Launch when ready
Deploy your Agent
Start with a private deployment on GMI infrastructure.
Connect models & compute
Use GMI Models, GMI Compute, or both together.
Validate and publish
Test performance, then create an Agentbox listing linked to your live deployment.
Operate after launch
Track usage, logs, spend, and operational metrics once you're live.
For builders, GMI shortens the path from working prototype to launchable product, without a separate hosting, model setup, or distribution stack.
Client cases
From external service Agents to internal enterprise automation — teams across industries are launching on GMI.
Agent Evaluation · High-Concurrency Sandboxes
50,000 concurrent sandboxes
Oqoqo evaluates agents, MCPs, SDKs, APIs, and CLIs across every model and harness its customers use. Every run needs a clean, isolated, throwaway environment, and it needs tens of thousands of them at the same time. On Agentbox, Oqoqo runs those evaluations at full concurrency with its own Docker images and memory profiles, including the heavier setups that carry MCP sidecars.
- Up to 50,000 concurrent sandboxes in a single evaluation run
- 6 to 8 GB RAM per sandbox, up to 16 GB for MCP sidecars
- Custom Docker images, ephemeral by default
- No sandbox infrastructure to build or maintain
Agentic Workspace · Secure Multi-Tenancy
~5x lower cloud cost
Morphic is an agentic workspace for project management, wiki, and workflow automation. The team behind it, SocratesLabs, runs its containerized agent and model workloads on Agentbox. Workload segregation comes built in rather than assembled, one click spins up an enterprise-ready environment, and there are no VMs or custom server setups to maintain. Morphic's own customers move between models without anyone touching infrastructure.
- ~5x lower cloud cost than the previous AWS-based setup
- One-click environment spin-up, no VM or custom server management
- Workload segregation out of the box for secure multi-tenant deployment
- Customers switch models without integration work
“We chose to move over to GMI Cloud because it became much more intuitive. We have segregation and infrastructure support done out of the box, and our cloud setup was almost five times cheaper than AWS.”
GEO / AI Search Visibility · Multi-Tenant Agents
200+ brands on one agent stack
Topify helps brands get recommended by AI search engines. It tracks mentions, citations, and competitor position across ChatGPT, Gemini, Perplexity, and Google AI Overview, then runs an agent that closes the gaps it finds: researching, drafting, publishing to the CMS, and monitoring what happens next. Every brand needs its own isolated agent runs, and all of them sit on GMI, with 100+ models behind one OpenAI-compatible API plus container hosting and deployment support.
- 200+ brands tracked across 4 AI search engines
- 100+ models through a single OpenAI-compatible API
- 2 days from setup to a deployed control plane, proxy, and admin dashboard
- Research to published content in minutes, not days
AI Harness · Persistent Memory
“There are at least 10 different providers we have been reviewing and researching, and obviously we chose GMI in the end.”
TinyHumans is solving AI memory. Today an assistant either forgets you or costs too much to remember you, and OpenHuman is their answer: a local-first memory layer plus an orchestrator for agent fleets. Steven Enamakel evaluated more than ten inference providers before choosing GMI, then launched. Two weeks later OpenHuman was the third largest AI harness in the world, behind only OpenClaw and Hermes.
- #3 AI harness worldwide, two weeks after launch
- Chose GMI after evaluating 10+ inference providers
- 5,000+ users in the first 7 days, growing 150% week over week
- One key and one bill, with no per-provider rate limits to work around
Open Source · Early Access
Day-1 Agentbox listing
NemoClaw is an open-ecosystem agent that launched into early access with a verified Agentbox listing on day one. Community users and enterprise buyers find it in the same catalog, with the trust signals an open-source agent normally has to earn on its own.
- Verified Agentbox listing from day one of early access
- Listed alongside commercial Agents, not in a separate open-source tier
- One install path for community users and enterprise evaluation
One platform. Not a patchwork of tools.
Most teams can build an Agent. Fewer can ship it. GMI connects deployment, model access, discoverability, and visibility in one product
| Capability | Self-Hosted / Stitched Stack | GMI Agentbox |
|---|---|---|
| Deployment + launch path | Manual | Included |
| Model + inference + compute | Separate setup | Included |
| Resource transparency | Manual | Included |
| Agentbox access layer | Separate system | Included |
| Usage and logs | Separate tools | Included |
| Go-live visibility | Limited | Included |
| Commercialization path | Custom build | Included |
Everything you need to go from workflow to product
Building an AI agent is the easy part. Getting it deployed, listed, and operating reliably at scale, across models, compute, and users, is where most teams slow down. GMI closes that gap with one unified platform instead of five stitched-together tools
Launch faster
From validation to packaging to listing, one path, not three separate projects
Full stack, unified
Model access, inference, and runtime compute in one place. No stack assembly required
Transparent by default
Users see pricing, availability, and runtime specs before they commit
Production-grade, not prototype
Deploy, publish, and operate, not just demo. Designed for teams that need to ship
Full visibility after launch
Usage, logs, spend, and performance, all in one dashboard once you're live
One platform. Built for any Agent, any workflow, any team
FAQ
Get quick answers to common queries in our FAQs
Your Agent is ready
Now make it launchable
Deploy, list, and operate, with the model access, inference, and compute to go from workflow to product