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Platform

The CLIKA Platform is where a team measures models on the hardware they will actually ship on. You register your devices with the platform, point it at a model, and it runs the benchmark on each device and brings the numbers back: accuracy per test, tokens per second, time to first token, peak memory. The same platform keeps those devices under management afterwards, runs models on them as long-lived endpoints, and issues the licenses a ClikaRT runtime needs.

One deployment carries three surfaces over the same data: a web application, a command-line tool (clika-rt), and an MCP server that lets Claude drive the platform for you in plain language.

Why the Platform​

For the ML engineer. A benchmark answers a question about a model on a device, and both halves matter. Pick a model from the Hugging Face Hub or from your project's model list, pick the quality tests to run (MMLU, GSM8K, HumanEval+, IFEval, and the rest of the catalog), pick the devices, and the platform runs every model on every device and lines the results up side by side. You do not choose a runner, a container image, or a script: the platform maps each model and device pair to the job definition that is confirmed to work on that platform and architecture.

For the team that owns the devices. A device runs one agent, which dials out to the platform over a single gRPC connection and needs no inbound port. From then on the device reports health every 15 seconds, accepts benchmark jobs and long-running services, exposes a terminal and a file browser, and can be reached through a remote desktop where the platform's providers can start one. Jetsons, x86 workstations, Windows machines, Raspberry Pi class boards and Android phones join the same fleet.

For the operator running the deployment. The platform runs on your infrastructure, in your cloud or on your own hardware. An organization holds users, roles and projects; a project holds the devices, models, benchmarks and licenses of one piece of work. API keys carry a subset of their owner's permissions, so an integration gets exactly the access it needs. Every authorization decision is recorded.

For whoever ships ClikaRT. A runtime credential issued by the platform is what a ClikaRT runtime presents to prove it may run. The platform issues those credentials per project, in an online form for runtimes that can reach the network and an offline bundle for the ones that cannot, and can revoke or rotate either one.

What you get​

  • Devices. A fleet with live health, hardware inventory, tags and per-device job history. Registration is one install command; the agent does the rest.
  • Models. A model is a reference to a Hugging Face repository plus the task it performs. Registering one is metadata only, so no weights move until a run needs them.
  • Benchmarks. A benchmark run fans out over every model and device you picked, and returns one comparable result set: quality scores, throughput and latency, memory, and the per-sample inputs and outputs behind the score.
  • Jobs and services. A job is one benchmark execution on one device, with artifact push, setup, script, teardown and result collection. A service is a process the platform keeps running on a device and restarts when it dies.
  • Model serving. Run a model on your own devices as an OpenAI-compatible endpoint the platform proxies for you.
  • Artifacts. Versioned, checksummed files (datasets, weights, engine bundles, scripts) that the platform pushes to devices and deduplicates on arrival.
  • Organizations, projects and access. Members and roles at the organization, membership and resources per project, scoped API keys for integrations.
  • Licensing. The runtime credentials your ClikaRT projects issue, update and revoke, plus activation of the deployment's own platform license.
  • CLI and Claude. Every documented operation is a CLI command and an MCP tool, so the same workflow runs from a terminal, from CI, or from a conversation with Claude.

Where to go next​

  • Getting started: the five-minute mental model, then a tutorial that takes you from signing in to reading your first benchmark result.
  • Concepts: one page each for organization, project, device, model, artifact, benchmark, job, service and deployment.
  • How-to guides: job and service definition YAML, MCP setup for Claude, members and API keys, license activation, reading results.
  • CLI reference: every clika-rt command, its arguments and its flags.