ClearML vs Sematic

ClearML

Agents

Sematic

Agents

Tagline

ClearML

End-to-end MLOps and GenAI platform with open-source experiment tracking and enterprise GPU orchestration.

Sematic

Open-source Python-first orchestrator for ML training pipelines from laptop to cloud.

Pricing

ClearML

Freemium· Community: $0 · Pro: $15 Per User/Month + Usage · Scale: Custom Quote · Enterprise: Request a Quote

Sematic

Freemium· Open-source free; managed/enterprise tier on request

Lowest paid tier

ClearML

$15 Per User/Month + Usage · Pro

captured 2026-08-10

Sematic

—

Free trial

ClearML

Yes

Sematic

Yes

API

ClearML

Yes

Sematic

Yes

Platforms

ClearML

api

Sematic

cliapi

Open source

ClearML

Yes

Sematic

Yes

Model used

ClearML

Model-agnostic

Sematic

—

Best for

ClearML

Pick ClearML if you need an open-source MLOps backbone that also handles GPU scheduling and LLM serving for an enterprise or on-prem GPU fleet.

Sematic

Pick Sematic if you want a Python-native ML pipeline orchestrator that runs the same code on a laptop and a Kubernetes cluster with artifact tracking baked in.

Not for

ClearML

Skip it if you just want lightweight experiment logging or a single-user notebook tracker - MLflow or W&B will be lower friction.

Sematic

Skip it if you need a general-purpose data orchestrator, a hosted SaaS with zero infra, or an LLM agent framework rather than ML training plumbing.

Editorial score

ClearML

8.3 / 10

Sematic

7.3 / 10

Use cases

ClearML

experiment-trackinggpu-orchestrationmlopsllm-deploymentmodel-registrydata-versioning

Sematic

ml-pipelinestraining-orchestrationexperiment-trackingkubernetes-mldag-workflows

Pros

ClearML

• Open-source core with permissive self-hosting
• Bundles tracking, orchestration, and GenAI serving in one stack
• Strong fractional-GPU and multi-tenant scheduling for shared clusters
• Vendor-neutral across clouds, on-prem, and silicon
• Active enterprise adoption in regulated industries

Sematic

• Pure Python pipeline definitions, no YAML or custom DSL
• Same code runs locally and on Kubernetes with packaged envs
• Built-in artifact tracking, lineage, and a usable dashboard
• Apache-2.0 open source with active GitHub repo
• Supports nested, dynamic, and looping DAGs

Cons

ClearML

• Pricing for enterprise tiers is opaque
• Heavier to deploy than logging-only alternatives
• UI and docs assume MLOps fluency
• GenAI App Engine is newer and less mature than the tracking core

Sematic

• Niche project compared to Prefect/Dagster/Flyte ecosystems
• Cloud execution requires a Kubernetes cluster you operate
• Not an LLM or generative AI tool, just orchestration
• Release cadence has slowed; check repo activity before adopting

Website

ClearML

clear.ml

Sematic

sematic.dev

Editorial score: rule-based, 0–10, from AI-assisted profile inputs (see /methodology) — not a user rating; “—” means unscored. “Not listed” means we have no record of it, not that it is absent. GitHub figures and prices carry the date they were checked or captured; prices are shown as published, unconverted.