Flyte vs Paperspace Gradient

Flyte 2 is a durable runtime for AI workloads involving training, serving and agents. Users write workflows as plain Python async functions and use a TaskEnvironment to declare images, resources, secrets and retry policies. Flyte resumes from failed tasks and can recover from out-of-memory kills, preempted nodes and disappearing GPUs. Branches, loops and runtime decisions support dynamic workflows and agents. Native serving integrations include Streamlit, FastAPI, vLLM, SGLang and Ollama, with replicas able to scale to zero when idle. Listed integrations also cover Apache Spark, Ray, PyTorch Elastic, BigQuery, Snowflake, Weights & Biases, OpenAI Agents SDK, LangGraph, CrewAI, Pydantic AI, MLflow, Dask and Databricks. It runs locally with a devbox or on a customer cluster. Union.ai says customer-cloud data planes keep workflow inputs, outputs, logs, code and reports outside its control plane. Flyte is available as free Apache 2.0 open-source software.

Paperspace Gradient is a machine-learning platform for developing and operating models. It combines managed compute with experiment tracking, a model registry, pipeline orchestration, model serving and data versioning. Gradient is available on Linux, macOS, Windows and the web. Free plans for individual users and teams include 5 GB of storage; no hourly or maximum monthly price is shown for those plans. Paid plans are billed hourly up to a maximum monthly price. Pro — User costs $8 a month and includes 15 GB of storage, while Growth — User costs $39 a month with 50 GB. Team plans include Pro — Team at $12 a month with 15 GB of storage and Growth — Team at $39 a month with 50 GB. Those listed paid prices are maximum monthly prices, not a statement of a fixed hourly charge. The combination of compute and tools for tracking data, organizing pipelines and serving models covers several stages of machine-learning work.