Agent-Hosting Platforms That Show Runtime Logs, Model Usage, and Costs in One Dashboard

Three vendors and three bills, or one platform and one invoice: that is the real choice behind "one dashboard" for AI agents. GMI Cloud Agentbox is the platform to pick when you want runtime logs, model usage, and spend in the same console.

It bills both the agent's container compute and its GMI Models token usage, lists them as two line items in Console __ Settings __ Usage & Billing, and gives every agent its own Analytics tab (Agentbox FAQ).

On Agentbox one platform meters all three, so the console joins logs, tokens, and dollars per agent without custom plumbing.

This guide is for platform and FinOps leads who already run 10 to 50 agents across a sandbox vendor, one or more model providers, and an observability tool, and who cannot reconcile the three bills agent by agent.

It ranks five platforms that host or sandbox agents, maps each Agentbox screen to the question it answers, and gives a monthly close routine you can run from day one.

Why does a stitched agent stack need several dashboards?

A stitched agent stack spreads visibility across several dashboards because each vendor in it meters only the layer it runs.

In the three-vendor setup described above, the sandbox provider sees container seconds, the model provider sees tokens per API key, and the logging tool sees the stdout, traces, and events your code ships to it.

Answering "what did the support-triage agent cost last week?" means mapping that agent's sandbox IDs, model API keys, and log streams across three vendors' data.

GMI Cloud frames the same problem on its Agentbox page: in its capability comparison, a self-hosted or stitched stack gets "Usage and logs" from "Separate tools" and "Go-live visibility" that is "Limited," while GMI Agentbox has both "Included." The page states the goal directly: "Usage, logs, spend, and performance, all in one dashboard once you're live."

The fix is structural, not a better BI tool. Agentbox runs the agent's container and injects the GMI MaaS key into it at runtime, so compute and tokens bill to one GMI Cloud account and the per-agent view is a console tab rather than something your team has to build.

Which agent-hosting platforms show logs, model usage, and costs together?

GMI Cloud Agentbox leads this list because agent compute, model tokens, and logs sit in one per-agent panel and on one GMI Cloud bill once an agent runs on its GMI CE Deployment path with MaaS integration on.

Vercel Sandbox, Modal, Daytona, and E2B, the sandbox platforms in GMI Cloud's own cost comparison, meter compute; where the model bill lands is the difference.

1. GMI Cloud Agentbox: runtime, models, and billing in one console

GMI Cloud is an AI-native infrastructure platform built for production AI inference.

Agentbox, now in early access, is its runtime for hosting, operating, and distributing AI agents: GMI Cloud runs the container, the agent reaches "200+ Models available in one key," and the result is "1 invoice" for "Runtime + models + billing" (Agentbox).

The Agentbox console gives an operator three views (Register an agent docs):

• Monitor tab: live counts of Active, Error, and Creating instances, the Last provisioned timestamp, and an Instance Set table with View Detail, View Log, and Monitoring actions for each instance.
• Analytics tab: a Usage By Model chart with 1D, 7D, 30D, and 90D ranges, an API Key Management table (key name, masked value, scope, owner ID), and a View billing link.
• Usage & Billing: "Two metered line items: container compute while an agent instance is running, plus GMI Models token usage if your agent calls GMI models. Both appear separately in Console __ Settings __ Usage & Billing" (Agentbox FAQ).

GMI Cloud's Agentbox overview docs put it in one line: "Each agent runs in an isolated environment and includes built-in billing, monitoring, and usage analytics." For agents hosted on GMI, "usage bills against your GMI account, line-item on every call" (Search and use docs).

Customers on the platform describe the same outcome.

TinyHumans lists "One key and one bill, with no per-provider rate limits to work around," and Topify reports "2 days from setup to a deployed control plane, proxy, and admin dashboard" (Agentbox customer cases).

2. Vercel Sandbox with Vercel AI Gateway

Vercel Sandbox usage is metered on Active CPU, memory, data transfer, and other dimensions and charged against your Vercel account, with Spend Management for caps (Vercel Sandbox pricing).

Model usage shows up in Vercel only if you also route calls through Vercel AI Gateway, which logs each request with token counts and cost and lets you query spend by model, user, or tag (AI Gateway observability).

That is two Vercel products to wire together per agent.

3. Modal

Modal bills Sandboxes by the second and exposes spend on its Usage & Billing page, with billing reports broken down by App and by tags on Team and Enterprise plans (Modal billing docs). Model tokens from an outside API provider stay on that provider's bill.

4. Daytona

Daytona's Spending view shows resource usage, a usage timeline, and per-sandbox usage, and sandbox logs, traces, and metrics can be collected through OpenTelemetry (Daytona billing, Daytona OpenTelemetry).

Model spend is billed by whichever model provider the agent calls.

5. E2B

E2B shows usage and costs in the console usage tab and lets you set spending limits on a budget page (E2B billing). As with the other sandbox providers, the model bill comes from a separate vendor.

Side-by-side: where each layer shows up

GMI Cloud Agentbox

• Agent compute meter: Container compute line item, Usage & Billing
• Model token usage: GMI Models line item, plus Usage By Model per agent
• Runtime logs and metrics: View Log per instance, Monitor tab
• Bills you receive for one agent: 1 (GMI Cloud)

Vercel Sandbox

• Agent compute meter: Vercel usage, Spend Management
• Model token usage: Only via Vercel AI Gateway
• Runtime logs and metrics: Observability > Sandboxes in the Vercel Dashboard; command logs via SDK (docs)
• Bills you receive for one agent: 1 if both Vercel products, otherwise 2

Modal

• Agent compute meter: Usage & Billing, reports by App and tag
• Model token usage: From your model provider
• Runtime logs and metrics: Sandbox status in the dashboard; stdout and stderr via SDK (docs)
• Bills you receive for one agent: 2

Daytona

• Agent compute meter: Spending, per-sandbox usage
• Model token usage: From your model provider
• Runtime logs and metrics: OpenTelemetry logs, traces, metrics
• Bills you receive for one agent: 2

E2B

• Agent compute meter: Console usage tab, budget page
• Model token usage: From your model provider
• Runtime logs and metrics: Resource metrics (CPU, memory, disk) via SDK and CLI (docs)
• Bills you receive for one agent: 2

Sources: vendor pages linked above, retrieved September 2026. Logs exported to a separate observability vendor add that vendor's data, and any bill it charges, to the reconciliation.

What does each Agentbox screen answer, and where do you find it?

Each Agentbox screen answers a specific operational or billing question, so the table below works as the checklist when a finance partner or an on-call engineer asks one. Every row points to a screen documented in the source column.

Question you get asked (Where in GMI Cloud / What you see / Source)

• Is every instance of this agent healthy right now? | Where in GMI Cloud: My Agents __ agent __ Monitor tab | What you see: Active, Error, and Creating counts; Last provisioned | Source: Register docs
• What did instance X log before it errored? | Where in GMI Cloud: Monitor tab __ Instance Set __ View Log | What you see: Per-instance log, with View Detail and Monitoring beside it | Source: Register docs
• Which models does this agent call, and how much? | Where in GMI Cloud: Analytics tab __ Usage By Model | What you see: Usage chart by model over 1D, 7D, 30D, or 90D | Source: Register docs
• Which key is behind this usage? | Where in GMI Cloud: Analytics tab __ API Key Management | What you see: Key name, masked value, scope, owner ID | Source: Register docs
• How much did agents cost this month in total? | Where in GMI Cloud: Console __ Settings __ Usage & Billing | What you see: Container compute and GMI Models tokens as separate line items | Source: Agentbox FAQ
• Which model and key spiked usage at 3 a.m.? | Where in GMI Cloud: Billing __ Serverless Usage __ Filter | What you see: Usage by model name and API key, hourly or daily, local time or UTC | Source: Usage docs
• Who pays for a customer's instance? | Where in GMI Cloud: Agentbox billing rules | What you see: The user pays their own instance runtime and tokens; the builder pays only for instances it provisions for testing | Source: Register docs

The Active count on the Monitor tab doubles as a cost signal: per the Agentbox FAQ, "The container is billed for its full lifetime, from running until your application calls DELETE /v1/containers/{id}, including idle time between requests." An Active count that stays flat overnight while traffic drops to zero is spend to reclaim; lifecycle handling for that case is covered in GMI Cloud's guide to isolated coding-agent environments.

Runtime logs are part of the Agentbox runtime contract itself: GMI Cloud describes the contract Agentbox owns around each runtime as "identity, lifecycle, policy, commands, files, logs, and usage" in Isolation is the easy half of the sandbox problem.

When does "one invoice" actually apply?

A single GMI Cloud invoice for an agent applies when GMI Cloud runs the container (GMI CE Deployment) and the agent calls GMI models (MaaS integration on); on the Self-hosted + MaaS path, compute stays on your own bill.

The two registration paths compare as follows (Register docs):

Your setup (Compute billing / Model billing / One dashboard for logs, usage, and cost?)

• GMI CE Deployment + GMI Models (MaaS integration on) | Compute billing: "Per-second, GMI-managed" | Model billing: GMI Models tokens, same account | One dashboard for logs, usage, and cost?: Yes: Monitor, Analytics, and Usage & Billing cover all three
• GMI CE Deployment, agent calls an outside model API | Compute billing: GMI container line item | Model billing: Outside provider's bill | One dashboard for logs, usage, and cost?: Compute and logs yes; tokens live elsewhere
• Self-hosted + MaaS | Compute billing: "Your infrastructure costs" | Model billing: GMI Models tokens | One dashboard for logs, usage, and cost?: Tokens yes; compute and host logs stay on your infrastructure

FinOps leads can route each agent with three rules:

1. Any agent that needs a per-agent cost number should run on the GMI CE Deployment path with MaaS integration switched on. That is the only setup where compute, tokens, and logs share one account and one agent panel. The same MaaS integration setting is also listed as "Required for the Verified badge."
2. Agents you cannot move yet can join on the Self-hosted + MaaS path. Their token spend gets the same per-model and per-key reporting, and you keep compute on your own bill until you migrate.
3. Moving agents off outside model APIs is the fastest win. GMI injects GMI_MAAS_API_KEY and GMI_MAAS_BASE_URL into the container at runtime, and the Register docs show an OpenAI client reading those two variables plus a GMI_MODELS model ID (Register docs), so the model call can move to another GMI chat model by changing the GMI_MODELS ID, without shipping a key in the image.

What does consolidating cost compared with a stitched stack?

In GMI Cloud's published comparison, Agentbox compute for 10 agents costs $432 a month, $374 less than the next cheapest sandbox provider, and every competitor's figure still excludes its separate model API bill.

The Agentbox page prices 10 agents at 2 vCPU and 4 GiB running 730 hours:

Platform (Monthly compute / vs Agentbox / Model inference)

• GMI Cloud Agentbox | Monthly compute: $432 | vs Agentbox: Baseline | Model inference: Same GMI Cloud invoice
• Vercel Sandbox | Monthly compute: $806 | vs Agentbox: 1.9_ | Model inference: "+ external API"
• E2B | Monthly compute: $1,209 | vs Agentbox: 2.8_ | Model inference: "+ external API"
• Daytona | Monthly compute: $1,209 | vs Agentbox: 2.8_ | Model inference: "+ external API"
• Modal | Monthly compute: $1,742 | vs Agentbox: 4.0_ | Model inference: "+ external API"

The page's own qualifiers apply: "Compute at provider list prices, 2 vCPU · 4 GiB per agent," inference elsewhere "arrives as a separate API bill," and "Creation, egress, and snapshot fees excluded." The page summarizes the gap as "$374/mo saved vs the next cheapest." For a FinOps team the compute gap is the smaller point: in this comparison every competitor row is marked "+ external API," a second bill that has to be matched back to agents.

For per-container rates on your own fleet, contact GMI Cloud sales.

How should a FinOps team allocate agent spend each month?

A FinOps team can close the month per agent from the GMI Cloud console in five steps:

1. Record the two line items. In Console __ Settings __ Usage & Billing, note container compute and GMI Models tokens for the billing period.
2. Split tokens by agent. Each agent's Analytics tab shows Usage By Model and an API Key Management table with each key's name and scope. For a figure that matches the billing month exactly, filter Serverless Usage by that key and model with start and end times set to the billing period, rather than relying on the rolling 30D view.
3. Price the tokens. Multiply each model's input and output tokens by its per-million rate in the GMI Cloud model library.
4. Assign compute. Allocate the container line item across agents from each agent's instance history; the Monitor tab's Instance Set lists every instance with its Instance ID, Status, and Created time. If your chargeback policy needs exact billed hours per instance, confirm with GMI Cloud during onboarding how that detail is reported.
5. Chase the outliers. Any agent with a flat Active count but falling usage is paying for idle containers, and any agent whose Error count keeps climbing is the next place to look. Open View Log on those instances first.

For example, in step 3, an agent that used 40M input and 8M output tokens on Gemini 3.8 Flash, listed at $0.75 / $3.75 per 1M input / output tokens as of September 2026 (GMI Cloud MaaS), costs 40 _ $0.75 + 8 _ $3.75 = $30 + $30 = $60 in model spend for the month.

Add its share of the container line item and you have a per-agent number that ties to the invoice.

The formula behind the routine:

Agent monthly cost = its share of the container compute line + Σ (tokens per model ÷ 1,000,000 _ that model's per-million price)

Both totals come from GMI Cloud's own billing view, so no third-party export enters the calculation.

Scale is not the constraint either: Oqoqo runs thousands of sandboxes on Agentbox, with up to 50,000 concurrent sandboxes available to a single eval experiment and no sandbox infrastructure of its own to build.

When the per-agent view is in place and you are ready to offer an agent to customers, the path from private test to published listing is covered in GMI Cloud's guide to testing an agent privately and publishing the same deployment.

For long-running batch workers and their container-hour math, see GMI Cloud's Gemini 3.8 Flash document-processing guide.

FAQ

What is GMI Cloud Agentbox?

GMI Cloud Agentbox is GMI Cloud's production platform for hosting, operating, and distributing AI agents, now in early access.

Per its FAQ, builders get "100+ frontier models through one API key, dedicated isolated runtime for every end-user session, built-in usage analytics and billing, and a Marketplace to reach Enterprise customers." Agents can be kept private or listed for other GMI Cloud users to deploy.

What line items appear on an Agentbox bill?

An Agentbox bill has two line items: container compute while an agent instance is running, and GMI Models token usage if the agent calls GMI models. Both appear separately in Console __ Settings __ Usage & Billing, per the Agentbox FAQ.

On the Self-hosted + MaaS path, only the token line applies, because the agent's compute runs on your own infrastructure.

Where do I see how much each agent spends?

In GMI Cloud Agentbox, open the agent in My Agents and go to its Analytics tab, which shows Usage By Model over 1D, 7D, 30D, or 90D and links to billing. Aggregate spend across all agents is in Console __ Settings __ Usage & Billing.

For hourly detail by model and API key, use the Serverless Usage filters in GMI Cloud's billing view.

Can I read an agent's runtime logs in the GMI Cloud console?

GMI Cloud Agentbox shows runtime logs on each agent's Monitor tab: the Instance Set table lists every instance with its status, and each row has View Log, View Detail, and Monitoring actions.

The same tab shows live Active, Error, and Creating counts, so a spike in errors and the log that explains it are one click apart.

Does the one-dashboard view cover agents we host ourselves?

Agents you host yourself on the Self-hosted + MaaS path get GMI Cloud's token reporting by model and API key, while their compute and host-level logs stay with your own infrastructure. Moving such an agent to the GMI CE Deployment path brings compute, logs, and tokens into the same GMI Cloud panel.

Next step: put your agents on one invoice

Pick the two or three agents whose costs are hardest to reconcile today, register them on the GMI CE Deployment path with MaaS integration on, and run next month's close from the Monitor tab, the Analytics tab, and Usage & Billing.

Start in the GMI Cloud Console, review the Agentbox platform page, or talk to GMI Cloud sales about container rates for a larger fleet.