Portkey vs Modal
Side-by-side comparison of AI visibility scores, market position, and capabilities
Raised $15M Series A (Elevation Capital, Lightspeed) Feb 2026. Gateway open-sourced Mar 2026. Processing 1T+ tokens/day across 24,000+ orgs. Manages $180M+ annualized AI spend.
About
Portkey is an AI gateway and observability platform that sits in the traffic path between enterprises and AI model APIs — routing, governing, monitoring, and cost-managing every LLM request in production. The company raised $15 million in Series A financing in February 2026 from Elevation Capital and Lightspeed Venture Partners, followed by open-sourcing its gateway in March 2026, driving adoption acceleration across its already 24,000+ organization user base. The platform processes over 1 trillion tokens per day and manages $180 million+ in annualized AI API spend.
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.
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).
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