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Comparison

TinyZero vs autogen

Verdict

Pick TinyZero if tinyZero is a scaled-down version of the R1-Zero architecture from DeepSeek, focusing on minimal setup with essential components; pick autogen if autoGen is a Python-based framework for developing and managing agentic AI systems. It includes the AutoGen Studio for no-code GUI setup, integrating with various models.

Markdown twin · TinyZero alternatives · autogen alternatives

GraphCanon updated today

TinyZero logo

TinyZero

Jiayi-Pan/TinyZero

★ 13kpushed Feb 27, 2026
vs
autogen logo

autogen

microsoft/autogen

★ 60kpushed Apr 15, 2026

Trust & integrity

SignalTinyZeroautogen
Maintenance
Slowing (134d since push)
As of today · github_public_v1
Steady (87d since push)
As of today · github_public_v1
Provenance
Not a fork · Personal account
As of today · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
No criticals
As of today · osv@v1
No lockfile
As of today · none
TinyZero trust reportautogen trust reportTrust methodology

Tagline

TinyZero
Minimal reproduction of DeepSeek R1-Zero
autogen
A programming framework for agentic AI

Stars

TinyZero
13k
autogen
60k

Forks

TinyZero
1.6k
autogen
9.0k

Open issues

TinyZero
82
autogen
945

Language

TinyZero
Python
autogen
Python

Adopt for

TinyZero
TinyZero is a scaled-down version of the R1-Zero architecture from DeepSeek, focusing on minimal setup with essential components.
autogen
AutoGen is a Python-based framework for developing and managing agentic AI systems. It includes the AutoGen Studio for no-code GUI setup, integrating with various models.

Persona

TinyZero
-
autogen
-

Runtime

TinyZero
-
autogen
-

License

TinyZero
TinyZero is licensed under Apache-2.0, allowing for broad usage with attribution requirements.
autogen
CC-BY-4.0

Last pushed

TinyZero
Feb 27, 2026
autogen
Apr 15, 2026

Categories

TinyZero
LLM Frameworks
autogen
AI Agents, LLM Frameworks

Trust and health

Maintenance

TinyZero
Slowing (36%)
autogen
Steady (60%)

Days since push

TinyZero
134d
autogen
87d

Open issues (now)

TinyZero
82
autogen
945

Owner type

TinyZero
User
autogen
Organization

Security scan

TinyZero
No criticals
autogen
No lockfile

Full report

TinyZero
Trust report
autogen
Trust report

Shared compatibility

  • Python · TinyZero: Python runtime · autogen: Python runtime

Choose TinyZero if…

  • License: TinyZero is Apache-2.0, autogen is CC-BY-4.0.
  • Pricing: The framework itself is free and can be used without charge;.
  • Requirements: Min 4 GB RAM; Specific Python environment setup (Python 3.9) and dependency installation steps are outlined in the README..
  • Tags unique to TinyZero: ray, deepseek, vllm, r1-zero.
  • When you need a streamlined implementation of the R1-Zero architecture without unnecessary complexity.

When NOT to use TinyZero

  • If your project demands extensive customization options not available in this minimal version.
  • When working with environments where specific versions of PyTorch older than 2.4.0 are required, as TinyZero mandates the use of PyTorch 2.4.0 or allows vLLM to manage its installation.
GitHubDetails

Choose autogen if…

  • License: autogen is CC-BY-4.0, TinyZero is Apache-2.0.
  • Requirements: Min 4 GB RAM; AutoGen requires Python 3.10 or later.; Ensure security when connecting to MCP servers due to the potential for local command execution and sensitive information exposure..
  • Tags unique to autogen: llm-framework, autogen, agents, ai.
  • Also covers AI Agents.
  • You need a framework that supports integration with multiple AI models via OpenAI's chat completion client.

When NOT to use autogen

  • If you require tools supporting multiple programming languages beyond Python, as AutoGen is strictly a Python-based framework.
  • When deploying in environments where connecting to external servers (like those used by MCP) could pose security risks or is prohibited.
  • You need solutions which do not involve additional installations for server components such as `playwright/mcp`, as AutoGen requires this setup for certain functionalities.
GitHubDetails

Explore

TinyZero trust report →autogen trust report →LLM Frameworks category →AI Agents category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: TinyZero 13k · autogen 60k (synced Jul 12, 2026).

Common questions

What is the difference between TinyZero and autogen?
TinyZero: Minimal reproduction of DeepSeek R1-Zero. autogen: A programming framework for agentic AI. See the comparison table for live GitHub stats and shared categories.
When should I choose TinyZero over autogen?
Choose TinyZero over autogen when License: TinyZero is Apache-2.0, autogen is CC-BY-4.0; Pricing: The framework itself is free and can be used without charge;; Requirements: Min 4 GB RAM; Specific Python environment setup (Python 3.9) and dependency installation steps are outlined in the README.; Tags unique to TinyZero: ray, deepseek, vllm, r1-zero; When you need a streamlined implementation of the R1-Zero architecture without unnecessary complexity.
When should I choose autogen over TinyZero?
Choose autogen over TinyZero when License: autogen is CC-BY-4.0, TinyZero is Apache-2.0; Requirements: Min 4 GB RAM; AutoGen requires Python 3.10 or later.; Ensure security when connecting to MCP servers due to the potential for local command execution and sensitive information exposure.; Tags unique to autogen: llm-framework, autogen, agents, ai; Also covers AI Agents; You need a framework that supports integration with multiple AI models via OpenAI's chat completion client.
When should I avoid TinyZero?
If your project demands extensive customization options not available in this minimal version. When working with environments where specific versions of PyTorch older than 2.4.0 are required, as TinyZero mandates the use of PyTorch 2.4.0 or allows vLLM to manage its installation.
When should I avoid autogen?
If you require tools supporting multiple programming languages beyond Python, as AutoGen is strictly a Python-based framework. When deploying in environments where connecting to external servers (like those used by MCP) could pose security risks or is prohibited. You need solutions which do not involve additional installations for server components such as playwright/mcp, as AutoGen requires this setup for certain functionalities.
Is TinyZero or autogen more popular on GitHub?
autogen has more GitHub stars (59,658 vs 13,192). Stars measure visibility, not whether either tool fits your constraints.
Are TinyZero and autogen open source?
Yes - both are open-source projects on GitHub (TinyZero: Apache-2.0, autogen: CC-BY-4.0).
Where can I find alternatives to TinyZero or autogen?
GraphCanon lists graph-backed alternatives at TinyZero alternatives and autogen alternatives (TinyZero markdown twin, autogen markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, TinyZero or autogen?
TinyZero: Slowing. autogen: Steady. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for TinyZero and autogen?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: TinyZero trust report; autogen trust report.