Eval Library
Modal
For ModalAI PlatformCode Assistant

Volumes Image Build Cache

Modal · Modal

Modal evals — Volumes & Image Build Cache (relift v3)

About Modal

Modal is a serverless cloud platform for running GPU workloads, ML inference, data pipelines, and web apps — all from Python, with no infrastructure to manage. Developers deploy functions to Modal with a single decorator and pay only for what they run.

Employees

~50

Industry

Serverless AI Infrastructure

Headquarters

New York, NY

Website

modal.com

Sample tests· showing 3 of 10

#InputExpected behaviorCheck
01

Trainer writes checkpoints to mounted modal.Volume at /checkpoints on @app.function(volumes={...}). Evaluator on second function reads missing latest.pt; writer never called volume.commit().

Agent adds volume.commit() after each checkpoint write, documents reader must volume.reload() before read, and verifies cross-function visibility.

Pass / FailTool usecritical
02

Parallel map workers write metrics.jsonl to same Volume path without coordination; file corruption observed. Docs warn about concurrent writers; pattern uses modal.Queue or per-worker paths.

Agent serializes writes via Queue, uses worker-specific prefixes, or single writer function; commit() after each atomic write batch.

Pass / FailSafetyhigh
03

Serving @app.function reads /models/weights from Volume mounted read-only. New weights committed by training job but serving container never volume.reload(); stale inference.

Agent adds volume.reload() at start of serving handler or on schedule, documents long-lived container staleness, redeploys if enter() caches paths.

Pass / FailTool usemedium

Rubric criteria

  • Modal
  • Serverless Gpu
  • Volumes Image Build Cache

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ModalModal customers

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