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Machine Learning · head to head

ClearML vs Deepgram

ClearML logo

ClearML

Machine Learning

Open-source MLOps platform for experiment tracking and orchestration

From
Free
Free plan
Yes
Full reviewWebsite
Deepgram logo

Deepgram

AI

Voice AI API platform for speech-to-text, text-to-speech, and voice agents

From
Free
Free plan
Yes
Full reviewWebsite

The short version

  • Each has a real cost: ClearML broad scope means more to learn and more to run than a focused tracking tool; Deepgram pricing is entirely usage-based, so total cost can be harder to predict than flat subscription tools.
  • They diverge on capability: ClearML covers Experiment tracking, Deepgram covers Flux speech-to-text.
  • Prices and features above were last checked on 29 August 2026.

Where they differ

Only the attributes on which ClearML and Deepgram actually diverge.

Attributes where ClearML and Deepgram differ
AttributeClearMLDeepgram
Pricing modelOpen-source self-hosted, with paid hosted and enterprise tiersusage-based
PlatformsLinux, macOS, Windows, Docker, Kubernetesweb, api
CategoryMachine LearningAI

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in ClearML

  • Experiment tracking
  • Remote execution
  • Data versioning
  • Pipelines

Only in Deepgram

  • Flux speech-to-text
  • Flux text-to-speech
  • Voice Agent API
  • Real-time and batch processing
  • Self-hosted deployment
  • Audio intelligence

What people use each for

The jobs each tool is most often brought in to do.

ClearML

  • Tracking experiments across a team so results are reproduciblenot Deepgram
  • Moving training from laptops to shared GPU hardware without repackagingnot Deepgram
  • Versioning datasets alongside the experiments that consumed themnot Deepgram

Deepgram

  • Building real-time voice agents for customer supportnot ClearML
  • Transcribing recorded audio at scale via batch STTnot ClearML
  • Adding conversational text-to-speech to voice applicationsnot ClearML
  • Self-hosting speech models for data residency requirementsnot ClearML

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

ClearML

  • Broad scope means more to learn and more to run than a focused tracking tool
  • Self-hosting the server is real infrastructure — database, file storage and web server
  • Documentation quality is uneven across the newer parts of the platform
  • Smaller community than the most popular tracking tools, so fewer worked examples exist

Deepgram

  • Pricing is entirely usage-based, so total cost can be harder to predict than flat subscription tools.
  • The Growth plan requires a minimum $4K/year commitment to unlock discounted rates.
  • Enterprise features and custom SLAs require a direct sales conversation rather than self-serve signup.
  • Some promotional per-minute rates are time-limited, meaning long-term pricing may differ from current promotional rates.

Pricing, plan by plan

ClearML

Free
  • Open sourceFree
    • Experiment tracking
    • Pipelines
    • Self-hosted server

Deepgram

Free
  • Pay As You Go$undefined/mo
    • $200 free credit to start
    • No minimums or expiration
    • No credit card required to start
  • Growth$undefined/mo
    • Save up to 20% with annual pre-paid credits
    • Minimum $4K/year commitment
    • Credits applied against actual usage
  • Enterprise$undefined/mo
    • Custom pricing for large-scale deployments
    • Dedicated support and contracts

Which should you pick?

Choose ClearML if

  • You need experiment tracking.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, Docker, Kubernetes.
  • You also want remote execution.
ClearML review

Choose Deepgram if

  • You need flux speech-to-text.
  • You want to start without paying.
  • You work on web, api.
  • You also want flux text-to-speech.
Deepgram review

Questions people ask

Is ClearML or Deepgram better?
Neither clearly leads. ClearML starts at Free and Deepgram at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, ClearML or Deepgram?
ClearML starts at Free and Deepgram at Free.
Does ClearML or Deepgram run on more platforms?
ClearML runs on Linux, macOS, Windows, Docker, Kubernetes. Deepgram runs on web, api.
Can I use ClearML for free?
Both have a free tier, so you can try either at no cost before committing.
What is ClearML best used for?
ClearML is most often used for tracking experiments across a team so results are reproducible, moving training from laptops to shared gpu hardware without repackaging, versioning datasets alongside the experiments that consumed them. Of those, tracking experiments across a team so results are reproducible and moving training from laptops to shared gpu hardware without repackaging are not what Deepgram is typically brought in for.
What can ClearML do that Deepgram cannot?
ClearML covers Experiment tracking, Remote execution, Data versioning, Pipelines. Deepgram covers Flux speech-to-text, Flux text-to-speech, Voice Agent API, Real-time and batch processing.

Answered from the vendors’ own pages

ClearML: Is ClearML free?

The open-source version is free and self-hostable. Hosted and enterprise tiers are paid.

Deepgram: What does Deepgram cost?

Deepgram uses usage-based pricing starting with $200 in free credit, pay-as-you-go rates per minute or per character, a Growth plan with annual pre-paid credits requiring a $4K/year minimum, and custom Enterprise pricing.

Source
ClearML: How much code does tracking require?

Very little — adding a couple of lines to an existing training script captures parameters, metrics and environment automatically.

Deepgram: Is there a free plan, and what are its limits?

New users get $200 of free credit with no credit card required, which can be applied to speech-to-text, text-to-speech, or voice agent usage before any payment is needed.

Source
ClearML: Does ClearML replace MLflow?

It covers MLflow’s tracking and adds orchestration, remote execution and data versioning. Whether that breadth is an advantage or extra weight depends on whether you need the rest.

Deepgram: How is usage metered?

Usage is metered per minute of audio for speech-to-text and voice agent calls, and per 1,000 characters for text-to-speech, with add-ons like redaction and entity detection billed separately per minute.

Source
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