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← Back to Clarifai Overview

Clarifai Pricing & Plans 2026

Complete pricing guide for Clarifai. Compare all plans, analyze costs, and find the perfect tier for your needs.

Try Clarifai Free →Compare Plans ↓

Not sure if free is enough? See our Free vs Paid comparison →
Still deciding? Read our full verdict on whether Clarifai is worth it →

🆓Free Tier Available
💎3 Paid Plans
⚡No Setup Fees

Choose Your Plan

Community

Free

mo

  • ✓Access to public models and pre-trained APIs
  • ✓Limited monthly inference operations
  • ✓Public AI Lake projects
  • ✓Community support
  • ✓OpenAI-compatible endpoint access
Start Free →

Essential

Usage-based (pay-as-you-go)

mo

  • ✓Private workspaces and projects
  • ✓Higher rate limits and inference operations
  • ✓Custom model uploads and training (Enlight)
  • ✓Scribe data labeling
  • ✓Standard support
Start Free Trial →
Most Popular

Professional

Custom (dedicated compute)

mo

  • ✓Dedicated GPU compute instances
  • ✓Armada auto-scaling inference
  • ✓Spacetime vector and metadata search
  • ✓Mesh workflow engine
  • ✓SLA-backed reliability
  • ✓Priority support
Start Free Trial →

Enterprise

Contact sales

mo

  • ✓Multi-cloud, on-premise, and air-gapped deployment
  • ✓Edge deployment via Flare
  • ✓SOC 2, FedRAMP, and ITAR support options
  • ✓99.99% reliability SLA
  • ✓Dedicated solution architect
  • ✓Custom security and compliance reviews
Contact Sales →

Pricing sourced from Clarifai · Last verified March 2026

Feature Comparison

FeaturesCommunityEssentialProfessionalEnterprise
Access to public models and pre-trained APIs✓✓✓✓
Limited monthly inference operations✓✓✓✓
Public AI Lake projects✓✓✓✓
Community support✓✓✓✓
OpenAI-compatible endpoint access✓✓✓✓
Private workspaces and projects—✓✓✓
Higher rate limits and inference operations—✓✓✓
Custom model uploads and training (Enlight)—✓✓✓
Scribe data labeling—✓✓✓
Standard support—✓✓✓
Dedicated GPU compute instances——✓✓
Armada auto-scaling inference——✓✓
Spacetime vector and metadata search——✓✓
Mesh workflow engine——✓✓
SLA-backed reliability——✓✓
Priority support——✓✓
Multi-cloud, on-premise, and air-gapped deployment———✓
Edge deployment via Flare———✓
SOC 2, FedRAMP, and ITAR support options———✓
99.99% reliability SLA———✓
Dedicated solution architect———✓
Custom security and compliance reviews———✓

Is Clarifai Worth It?

✅ Why Choose Clarifai

  • • Fastest GPU-based inference benchmarked at 410 tokens/sec on Kimi K2.5 (Artificial Analysis)
  • • OpenAI-compatible API enables drop-in migration with only base URL and key changes
  • • Armada handles 1.6M+ inference requests/sec with 99.99% reliability SLA
  • • Full lifecycle coverage: labeling (Scribe), training (Enlight), search (Spacetime), workflows (Mesh)
  • • Flexible deployment across AWS, Azure, GCP, bare-metal air-gapped, and edge devices via Flare
  • • Claimed 90%+ reduction in compute requirements versus traditional GPU deployments

⚠️ Consider This

  • • Usage-based pricing can be hard to forecast for variable enterprise workloads
  • • Steep learning curve to use Mesh, Scribe, and AI Lake together effectively
  • • Free Community tier is restrictive compared to Hugging Face's open ecosystem
  • • Broader feature surface area than pure inference providers like Together AI or Replicate, which can be overkill for single-model hosting needs
  • • Documentation depth varies across newer products like Flare and Spacetime

What Users Say About Clarifai

👍 What Users Love

  • ✓Fastest GPU-based inference benchmarked at 410 tokens/sec on Kimi K2.5 (Artificial Analysis)
  • ✓OpenAI-compatible API enables drop-in migration with only base URL and key changes
  • ✓Armada handles 1.6M+ inference requests/sec with 99.99% reliability SLA
  • ✓Full lifecycle coverage: labeling (Scribe), training (Enlight), search (Spacetime), workflows (Mesh)
  • ✓Flexible deployment across AWS, Azure, GCP, bare-metal air-gapped, and edge devices via Flare
  • ✓Claimed 90%+ reduction in compute requirements versus traditional GPU deployments

👎 Common Concerns

  • ⚠Usage-based pricing can be hard to forecast for variable enterprise workloads
  • ⚠Steep learning curve to use Mesh, Scribe, and AI Lake together effectively
  • ⚠Free Community tier is restrictive compared to Hugging Face's open ecosystem
  • ⚠Broader feature surface area than pure inference providers like Together AI or Replicate, which can be overkill for single-model hosting needs
  • ⚠Documentation depth varies across newer products like Flare and Spacetime

Pricing FAQ

How does Clarifai compare to OpenAI in terms of speed and cost?

Clarifai delivers 410 tokens per second on models like Kimi K2.5, which Artificial Analysis benchmarked as faster than any other GPU-based provider. Because the platform exposes an OpenAI-compatible API, you can migrate by changing only the base URL and API key. Cost varies by model and compute tier, but Clarifai's serverless and dedicated compute options typically beat OpenAI's per-token pricing for open-weight models, and you avoid the rate-limit ceilings common on closed APIs.

Can I deploy my own custom models on Clarifai?

Yes. Clarifai supports custom model uploads, fine-tuning of open-source foundation models, and from-scratch training through the Enlight UI. You can bring TensorFlow, PyTorch, ONNX, and Hugging Face checkpoints, then deploy them to Armada for auto-scaling inference. Custom models inherit the same OpenAI-compatible endpoint structure, so client code does not need to change between hosted and custom deployments.

What deployment options are available?

Clarifai offers four deployment surfaces: managed multi-cloud on AWS, Azure, and Google Cloud; dedicated bare-metal with air-gapped options for regulated industries; on-premise inside customer data centers; and edge deployment through the Flare runtime for devices with constrained connectivity. All four share the same control plane and AI Lake assets, so a model trained in the cloud can ship to an edge device without re-packaging.

Does Clarifai still support computer vision capabilities?

Yes. Clarifai started as a computer vision company in 2013 and still offers pre-trained models for image classification, object detection, OCR, face detection, NSFW moderation, and visual search. These are accessible through the same API as LLM endpoints, and Spacetime adds vector similarity search for image embeddings. CV remains a first-class citizen alongside LLMs and agentic workflows.

Is Clarifai suitable for regulated industries like healthcare or government?

Clarifai is positioned for regulated workloads, with SOC 2 compliance, air-gapped on-premise deployment, and a long history of US federal and DoD contracts. Sensitive data can stay inside customer infrastructure while still using the Clarifai control plane for orchestration. Buyers in HIPAA, FedRAMP, or ITAR contexts should request the specific compliance documentation relevant to their deployment, since coverage differs between managed cloud and self-hosted options.

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More about Clarifai

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AI-native cloud for inference, fine-tuning, and dedicated GPU clusters, offering 200+ open-source and frontier-class models behind an OpenAI-compatible API plus reserved H100/H200/B200 capacity.

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Hugging Face Pricing

A collaborative platform where the machine learning community builds, shares, and deploys AI models, datasets, and applications.

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Replicate Pricing

Run, fine-tune, and deploy thousands of community AI models with a single HTTP API — covering image, video, audio, language, and embedding models, billed per-second of GPU time.

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