Platform comparison

AgentSky vs Modal

Modal is a Python-native serverless platform for GPU-intensive ML workloads and batch inference. AgentSky gives you a complete running cloud agent behind one call. Modal is infrastructure; AgentSky runs on top.

What is Modal

Modal is a Python-native serverless compute platform — specify GPU type, container image, memory, and concurrency via Python decorators, and Modal handles scheduling, autoscaling, and billing. It is built for ML training, inference, batch processing, and interactive workloads, with Sandboxes added for isolated code execution in agent-style pipelines.

What is AgentSky

AgentSky is a cloud agent platform — the OpenRouter for agents. One API call selects a harness (Claude Code, Codex, Hermes, or five others) and a model; the platform provisions a persistent, crash-resistant computer with optional 2000+ channel connectors on the same call, and tracks each task through completion or failure.

Feature comparison

How they compare

Cloud agent platformAgentSkyServerless GPU computeModal
What you getA running cloud agent — harness, model, persistent state, and channels — behind one API callServerless compute primitives (functions, Sandboxes, Volumes, Queues) that you wire into agent behavior in Python
Primary use caseDelegating multi-step agentic tasks to maintained, crash-resistant harnesses with built-in channel integrationsML training, batch inference, large-scale data processing, and GPU-intensive serverless workloads
Time to first agent runSeconds — pick harness and model, call the APIImplementation-dependent — define the workload, wire the LLM, and own agent lifecycle and recovery
State and persistencePersistent computer; survives crashes, network loss, and laptop closure; resumes mid-task automaticallyModal Volumes provide durable storage; Sandboxes are stateless by default; crash recovery is your application code's responsibility
Model choice8 harnesses x any supported model; BYO Claude or ChatGPT subscription reduces model cost to $0Model-agnostic for custom inference; own token-metered Shared API launched July 2026; bring any model at API rates
Channels and connectors2000+ built-in connectors (Gmail, Sheets, Slack, GitHub, Linear, and more) declared as add-ons on the same API callApplication integrations are functions or services your product deploys on Modal compute
Pricing modelPay per task at list pricing, no card required to sign up; BYO subscription cuts model cost to $0Starter: free with $30/month credits; Team: $250/month; GPU from $1.10/hr (A10) to $3.95/hr (H100 SXM5); CPU $0.0000131/core/sec
Best forRunning agents immediately without building or operating agent infrastructureGPU-intensive ML workloads, custom inference servers, fine-tuning, and serverless compute for non-agent use cases

Product details reflect public information. Verify changing facts in the competitor's official docs and current pricing.

When to choose Modal

Modal is the right choice for these workloads

Choose Modal for fine-tuning models, running batch inference, or deploying a GPU inference server with autoscaling and per-second billing. It is also the right fit for Python-native teams needing dedicated GPU hardware (T4 through B200) for compute-intensive workloads outside of agentic task execution.

FAQ

Common questions

Complete agent infrastructure

The agent and its computer. One API.