Perplexity vs Modal

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

Perplexity leads in AI visibility (88 vs 45)

Perplexity

LeaderAI & Machine Learning

AI Search API

1B+ monthly queries; 240M website visits/month; AI search category leader. $9B valuation; Perplexity Pro with GPT-4o and Claude 3.7 access. Sonar API for AI-native search in agentic applications. 15M+ registered users.

AI VisibilityBeta
Overall Score
A88
Category Rank
#1 of 1
AI Consensus
58%
Trend
stable
Per Platform
ChatGPT
97
Perplexity
92
Gemini
99

About

Perplexity AI is an AI-powered answer engine that provides direct, sourced responses to user queries by searching the web in real time and synthesizing information through large language models. Founded in 2022 and headquartered in San Francisco, Perplexity was created by Aravind Srinivas (formerly OpenAI), Denis Yarats, Johnny Ho, and Andy Konwinski with the vision of replacing the traditional search engine's link-based results with direct, cited answers that users can trust and verify.

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

88
Overall Score
45
#1
Category Rank
#1
58
AI Consensus
55
stable
Trend
up
97
ChatGPT
38
92
Perplexity
50
99
Gemini
53
94
Claude
39
81
Grok
37

Capabilities & Ecosystem

Capabilities

Only Perplexity
AI Search API
Only Modal
Serverless ML

Track AI Visibility in Real Time

Monitor how your brand performs across ChatGPT, Gemini, Perplexity, Claude, and Grok daily.