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Comparison

FLAML vs agents

Verdict

Pick FLAML when fLAML is primarily Jupyter Notebook; agents is Python; pick agents when agents is primarily Python; FLAML is Jupyter Notebook.

Markdown twin · FLAML alternatives · agents alternatives

GraphCanon updated today

FLAML logo

FLAML

microsoft/FLAML

★ 4.4kpushed Jul 11, 2026
vs
agents logo

agents

wshobson/agents

★ 38kpushed Jul 8, 2026

Trust & integrity

SignalFLAMLagents
Maintenance
Very active (0d since push)
As of today · github_public_v1
Very active (2d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Personal account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
No MCP manifest
As of today · mcp_manifest
FLAML trust reportagents trust reportTrust methodology

Tagline

FLAML
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
agents
Multi-harness agentic plugin marketplace for various AI agents

Stars

FLAML
4.4k
agents
38k

Forks

FLAML
558
agents
4.0k

Open issues

FLAML
182
agents
1

Language

FLAML
Jupyter Notebook
agents
Python

Adopt for

FLAML
-
agents
The agents tool is a marketplace for plugins that enhances multiple AI agents, offering integration and management capabilities across several platforms, including Claude Code, Codex CLI, Cursor, OpenCode, GitHub Copilot

Persona

FLAML
-
agents
-

Runtime

FLAML
-
agents
-

License

FLAML
MIT
agents
MIT

Last pushed

FLAML
Jul 11, 2026
agents
Jul 8, 2026

Categories

FLAML
Developer Tools
agents
AI Agents, Developer Tools

Trust and health

Days since push

FLAML
0d
agents
2d

Open issues (now)

FLAML
182
agents
1

Owner type

FLAML
Organization
agents
User

Security scan

FLAML
No lockfile
agents
No MCP manifest

Full report

FLAML
Trust report
agents
Trust report

Choose FLAML if…

  • FLAML is primarily Jupyter Notebook; agents is Python.
  • Tags unique to FLAML: automl, data-science, hyperparam, deep-learning.
  • FLAML ships Docker support for self-hosted deployment.

When NOT to use FLAML

  • Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
GitHubDetails

Choose agents if…

  • agents is primarily Python; FLAML is Jupyter Notebook.
  • Tags unique to agents: agent-skills, workflows, agentic-ai, prompt-engineering.
  • Also covers AI Agents.
  • You are working specifically within the ecosystems of Claude Code, Codex CLI, Cursor, OpenCode, GitHub Copilot, or Gemini CLI, as it provides tailored plugins for these environments

When NOT to use agents

  • You are working solely within a niche environment that isn't one of the supported platforms (like Claude Code, Codex CLI, etc.) because it may not offer compatible plugins or extensive support
  • Your project requirements do not include interoperability between multiple AI agents and you only need to leverage functionalities from a single AI agent with a robust in-built plugin ecosystem
GitHubDetails

Explore

FLAML trust report →agents trust report →Developer Tools 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: FLAML 4.4k · agents 38k (synced Jul 11, 2026).

Common questions

What is the difference between FLAML and agents?
FLAML: A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.. agents: Multi-harness agentic plugin marketplace for various AI agents. See the comparison table for live GitHub stats and shared categories.
When should I choose FLAML over agents?
Choose FLAML over agents when FLAML is primarily Jupyter Notebook; agents is Python; Tags unique to FLAML: automl, data-science, hyperparam, deep-learning; FLAML ships Docker support for self-hosted deployment.
When should I choose agents over FLAML?
Choose agents over FLAML when agents is primarily Python; FLAML is Jupyter Notebook; Tags unique to agents: agent-skills, workflows, agentic-ai, prompt-engineering; Also covers AI Agents; You are working specifically within the ecosystems of Claude Code, Codex CLI, Cursor, OpenCode, GitHub Copilot, or Gemini CLI, as it provides tailored plugins for these environments.
When should I avoid FLAML?
Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
When should I avoid agents?
You are working solely within a niche environment that isn't one of the supported platforms (like Claude Code, Codex CLI, etc.) because it may not offer compatible plugins or extensive support Your project requirements do not include interoperability between multiple AI agents and you only need to leverage functionalities from a single AI agent with a robust in-built plugin ecosystem
Is FLAML or agents more popular on GitHub?
agents has more GitHub stars (37,779 vs 4,373). Stars measure visibility, not whether either tool fits your constraints.
Are FLAML and agents open source?
Yes - both are open-source projects on GitHub (FLAML: MIT, agents: MIT).
Where can I find alternatives to FLAML or agents?
GraphCanon lists graph-backed alternatives at FLAML alternatives and agents alternatives (FLAML markdown twin, agents 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, FLAML or agents?
FLAML: Very active. agents: Very active. 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 FLAML and agents?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: FLAML trust report; agents trust report.