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Tabby vs Langflow

AI Agent Comparison — side-by-side analysis

Comparison Summary

Langflow has a higher trust score (88.0 vs 84.0). Langflow leads in community adoption with 140,000 stars vs 25,000. Langflow offers more capabilities (5 vs 4). Tabby supports more protocols (2 vs 1).

Tabby

Self-hosted AI coding assistant

OSS Repo
Trust: 84.0 ★ 25.0k
Language: Rust
Author: TabbyML
View Profile Source →

Langflow

Low-code app builder for RAG and multi-agent AI

OSS Repo
Trust: 88.0 ★ 140.0k
Language: Python
Author: langflow-ai
View Profile Source →

Visual Comparison

Tabby Langflow
Trust Score 84.0 vs 88.0
Tabby
84.0
Langflow
88.0
WINNER
GitHub Stars 25,000 vs 140,000
Tabby
25,000
Langflow
140,000
WINNER
Capabilities 4 vs 5
Tabby
4
Langflow
5
WINNER
Protocols 2 vs 1
Tabby
2
WINNER
Langflow
1

Detailed Metrics

MetricTabbyLangflow
Trust Score84.088.0 WINNER
GitHub Stars25,000140,000 WINNER
TypeOSS RepoOSS Repo
LanguageRustPython
AuthorTabbyMLlangflow-ai
Capabilities45 WINNER
Protocols2 WINNER1
Installdocker run tabbyml/tabbypip install langflow

Capabilities

Shared Capabilities
None
Only in Tabby
chatcode-completionlocal-inferenceself-hosted
Only in Langflow
drag-dropmulti-agentno-coderagworkflow

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Tabby vs N8NLangflow vs N8NTabby vs AutoGPTLangflow vs AutoGPTTabby vs OllamaLangflow vs Ollama