Can I use HuggingFace Agent and Agno together?

Yes, many teams use both tools together for different purposes. Use the Stack Builder section above to combine HuggingFace Agent and Agno with other tools and save your AI toolkit.

Does HuggingFace Agent or Agno have a free plan?

HuggingFace Agent is a paid tool. Agno is available for free. Always verify current pricing directly with the vendor.

HuggingFace Agent vs Agno

Comprehensive side-by-side comparison — features, pricing, performance, and more.

Updated June 2026

HuggingFace Agent

Hugging Face

Collaborate on state-of-the-art AI models, datasets, and applications with the ML community.

0.0(0)

OPEN_SOURCE

94% data quality

Agno

Agno Inc.

A new architecture for multi-agent systems that runs in your cloud.

0.0(0)

FREEMIUM

94% data quality

Trust & Reliability

HuggingFace Agent

Uptime:99.980%Status page

Users:10K-100K

Customers (per vendor):Ai2, AI at Meta, Amazon +5

GDPR

Too Close to Call

HuggingFace Agent (7.5) vs Agno (7.5) — difference of 0.0 points

AI Comparison Summary

HuggingFace Agent

7.5

avg score

Agno

7.5

avg score

Both tools score very similarly overall — the best choice depends on your specific priorities.

Based on 6 dimensions

How scores are calculated

Too close to call — it's a tie

HuggingFace Agent

Best For

Building custom AI agents for complex tasks for developers

Collaborating on machine learning projects for researchers and engineers

Deploying and scaling machine learning applications and agents

Sharing and discovering pre-trained AI models and datasets

Not Ideal For

Non-technical users seeking a no-code autonomous agent solution

Users looking for a single, pre-built, fully autonomous agent for specific tasks without development

Organizations requiring a fully managed, black-box AI agent solution without customization

Agno

Best For

Building and deploying multi-agent systems for developers

Orchestrating complex AI workflows in production environments

Ensuring data privacy and security for agentic applications

Teams needing high-performance and low-latency agent execution

Not Ideal For

Non-technical users seeking a no-code agent builder

Teams unwilling to manage their own cloud infrastructure

Simple, single-step automation tasks that don't require agentic capabilities

* Verdict is based on our algorithmic scoring of publicly available data. Learn about our methodology

HuggingFace Agent is best for

🤖Automation & Agents6.7

Agno is best for

🤖Automation & Agents8.3

Filter by your use case:

Pros & Cons

HuggingFace Agent

Pros

Extensive collection of 2M+ models and 500k+ datasets on the Hub
Comprehensive open-source libraries (Transformers, Diffusers, Datasets) for various ML tasks
Supports multiple modalities including text, image, video, audio, and 3D
Offers flexible compute options with GPU access for Spaces and Inference Endpoints
Strong community collaboration features with Git-based versioning and evaluation leaderboards
Enterprise-grade security features like SSO, audit logs, and granular access controls

Cons

Requires technical knowledge and coding skills for agent development
Advanced features and dedicated compute require paid subscriptions
Not a ready-to-use autonomous agent, but a framework for building them
Free tier has limited storage and inference credits

Agno

Pros

Runs entirely in your cloud, ensuring data privacy and control with no egress costs
Significantly faster agent instantiation and lower memory footprint than competitors
Flexible and agnostic, supporting any LLM, database, and cloud provider
Comprehensive control plane for real-time monitoring, tracing, and management
Robust human-in-the-loop capabilities for controlled agent execution
Open-source framework with a strong community and extensive documentation

Cons

Requires Python knowledge and coding skills, not suitable for no-code users
Self-hosted deployment requires user's own cloud infrastructure management
Newer framework compared to established alternatives like LangChain, potentially smaller ecosystem
Advanced features like custom SSO and dedicated support are locked behind enterprise tiers

Weighted Score — Adjust What Matters to You

Pick a profile or drag sliders — scores and radar update instantly on the right.

Quick profiles:

Ease of Use5

Output Quality5

Value for Money5

Customizability5

Support & Ecosystem5

Integration Power5

Dimension Comparison

HuggingFace Agent

7.5

/ 10

Agno

7.5

/ 10

Dimension Breakdown

Ease of Use

How easy it is to get started and use daily

HuggingFace Agent

6.0

Agno

6.0

Output Quality

Quality and accuracy of generated results

HuggingFace Agent

8.0

Agno

8.0

Value for Money

Cost vs. features and output quality

HuggingFace Agent

7.0

Agno

7.0

Customizability

Calculated

Ability to tailor to specific needs

HuggingFace Agent

8.0

Agno

9.0▲ +1.0

Support & Ecosystem

Documentation, community, and support quality

HuggingFace Agent

8.0▲ +1.0

Agno

7.0

Integration Power

Calculated

Ability to connect with other tools and workflows

HuggingFace Agent

8.0

Agno

8.0

Calculated = derived from verified integration count and API/open-source signals. AI = LLM-assessed from public website content. Methodology

Data is sourced from public information and vendor websites. It may not always be up-to-date — verify pricing and features directly with the vendor before purchasing.Report inaccuracy

Frequently Asked Questions

Which is better, HuggingFace Agent or Agno?

Both are strong options. HuggingFace Agent has a rating of 0.0/5 (0 reviews), while Agno has a rating of 0.0/5 (0 reviews). The best choice depends on your specific use case, budget, and workflow requirements.

Is HuggingFace Agent cheaper than Agno?

HuggingFace Agent starts at free (open_source model). Agno starts at free (freemium model). Use the Cost Calculator above for a detailed estimate.

What are the main differences between HuggingFace Agent and Agno?

HuggingFace Agent — "Collaborate on state-of-the-art AI models, datasets, and applications with the ML community.". Agno — "A new architecture for multi-agent systems that runs in your cloud.". Key differences include their pricing models, platform support, integrations, and technical capabilities. See the Feature Comparison table above for a complete side-by-side breakdown.

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