Dify vs Modal

Side-by-side comparison of AI visibility scores, market position, and capabilities

Dify leads in AI visibility (69 vs 45)

Dify

ChallengerDeveloper Tools & Platforms

LLM Application Development

Open-source LLM app development platform with 80K+ GitHub stars and 1.4M+ deployments; raised $30M Pre-A at $180M valuation in Mar 2026; supports agentic workflows, RAG pipelines, and model management with integration for hundreds of LLMs.

AI VisibilityBeta
Overall Score
B69
Category Rank
#1 of 1
AI Consensus
76%
Trend
up
Per Platform
ChatGPT
64
Perplexity
64
Gemini
66

About

Dify is an open-source platform for building AI applications, developed by LangGenius, Inc. and founded in 2023. Headquartered in San Francisco, Dify combines Backend-as-a-Service with LLMOps to let developers quickly go from prototype to production-ready AI applications. The platform supports agentic workflows, RAG pipelines, agent capabilities, model management, and observability with integration for hundreds of LLMs.

Full profile

Modal

EmergingAI & Machine Learning

Serverless ML

Serverless GPU cloud platform for AI/ML with Python-native deployment and per-second billing; developer-favorite scaling from zero competing with Replicate and Beam for AI compute.

AI VisibilityBeta
Overall Score
C45
Category Rank
#1 of 1
AI Consensus
55%
Trend
up
Per Platform
ChatGPT
38
Perplexity
50
Gemini
53

About

Modal is a serverless cloud computing platform purpose-built for AI and machine learning workloads — providing on-demand GPU compute that scales instantly from zero with per-second billing, container management, distributed training support, and a Python-native developer experience that makes running ML workloads in the cloud feel as simple as running code locally. Founded in 2021 in New York City and backed by Redpoint Ventures and other investors, Modal has grown rapidly as AI development has accelerated demand for flexible, developer-friendly GPU infrastructure.\n\nModal's developer experience is its primary differentiator — engineers write Python functions decorated with @modal.function() and deploy them to the cloud with a single command, with Modal handling container building, GPU provisioning, auto-scaling, and execution. The platform supports training jobs that need distributed compute across multiple GPUs, model serving endpoints that scale to zero when unused (eliminating idle GPU costs), and batch inference jobs that process large datasets. The per-second billing model means developers pay only for actual compute time, not provisioned instances.\n\nIn 2025, Modal competes in the AI infrastructure market with Replicate, Beam, Banana, and major cloud providers' managed ML services (AWS SageMaker, Google Vertex AI, Azure ML) for serverless GPU compute. The market for AI-specific cloud infrastructure has grown dramatically as the number of ML engineers deploying models to production has expanded — traditional cloud providers require significant DevOps expertise to use GPU instances effectively, while Modal's Python-native approach reduces the barrier to entry. Modal has attracted a strong developer following among AI researchers and ML engineers building production AI applications. The 2025 strategy focuses on growing the developer community, adding enterprise features (dedicated GPU capacity, private networking, compliance), and expanding the hardware options available (H100 GPUs, custom accelerators).

Full profile

AI Visibility Head-to-Head

69
Overall Score
45
#1
Category Rank
#1
76
AI Consensus
55
up
Trend
up
64
ChatGPT
38
64
Perplexity
50
66
Gemini
53
70
Claude
39
73
Grok
37

Capabilities & Ecosystem

Capabilities

Only Dify
LLM Application Development
Only Modal
Serverless ML

Integrations

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