FloydHub vs Baseten

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FloydHub

FloydHub was a managed training and deploying platform for deep learning experiments that simplified data mounting jobs metrics and collaboration but it permanently shut down in 2021.

Pricing Discontinued
Category specialized
Difficulty Beginner
Type Web App
Status Active
Baseten

Baseten

Serve open source and custom AI models with autoscaling cold start optimizations and usage based pricing that includes free credits so teams can prototype and scale production inference fast.

Pricing Free credits, usage based pricing
Category specialized
Difficulty Beginner
Type Web App
Status Active

Feature Tags Comparison

Only in FloydHub

mlopsdiscontinuedexperimentstrainingdeploy

Shared

None

Only in Baseten

inferenceservingautoscalinggpuusagemodel-apis

Key Features

FloydHub

  • • Reproducible environments for experiments with simple job launch and logs that reduced setup toil for fast iteration during research
  • • Dataset mounting and snapshots that kept inputs consistent across runs so results remained comparable and easy to audit for teams
  • • Team workspaces and collaboration that allowed shared projects and roles so students and startups could coordinate work simply
  • • Run metrics and comparisons that surfaced loss curves and scores so selection and reporting were faster for notebooks and papers
  • • CLI and UI control that matched developer needs so power users scripted pipelines while newcomers clicked through safe defaults
  • • Early model deployment paths that exposed inference endpoints for demos which helped small teams share progress with stakeholders

Baseten

  • • Pre optimized model APIs for rapid evaluation
  • • Bring your own weights with versioned deployments and rollback
  • • Autoscaling with fast cold starts
  • • Metrics logs and traces to monitor throughput errors and costs
  • • Background workers and batch jobs
  • • Webhooks and REST endpoints

Use Cases

FloydHub

  • → Migration planning from legacy accounts to modern notebook services with artifact export so research continuity is preserved for teams
  • → Experiment tracking adoption using current open source stacks that replicate run history dashboards and metrics for new projects
  • → Student lab environments updated to contemporary cloud notebooks that mirror the low friction FloydHub approach for coursework and demos
  • → Prototype to demo flows rebuilt on managed inference endpoints which recreate the fast shareability that FloydHub enabled for stakeholders
  • → Dataset governance modernization that replaces snapshots with versioned buckets and policies to keep experiments auditable and compliant
  • → Team collaboration standardized on workspaces and role based access in current tools to maintain the simple getting started experience

Baseten

  • → Stand up a chat backend for prototypes then scale
  • → Serve fine tuned models behind a stable API
  • → Batch process documents or images using workers
  • → Replace brittle scripts with autoscaled endpoints
  • → Evaluate multiple open models quickly
  • → Track token use latency and error spikes

Perfect For

FloydHub

teams modernizing from legacy MLOps tools educators and small research groups that need a clear path from historical FloydHub workflows to current platforms with better governance and support

Baseten

Backend engineers, ML engineers, product teams, and startups that need fast secure model serving with metrics governance and usage pricing that grows from prototype to production

Capabilities

FloydHub

Experiments and Jobs Basic
Snapshots and Datasets Basic
Shared Workspaces Basic
Modern Replacements Intermediate

Baseten

Model APIs Professional
Metrics and Traces Professional
Workers and Batches Intermediate
Governance Enterprise

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