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Continue vs SuperCompress

ContinueSuperCompress

Bottom line: Continue for local-first developers; SuperCompress for developers cutting LLM API costs.

ContinueContinue

Open-source AI code assistant that plugs any model into your IDE

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SuperCompressSuperCompress

Query-aware prompt compression that cuts LLM input tokens by roughly 60% before inference.

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Votes00
PricingFreemiumFreemium
CategoryCodingCoding
Tags
open-sourceide-extensionlocal-modelsautocompletecustomizable
llmdeveloper-toolscost-optimization
Best for
  • Local-first developers
  • Teams wanting config-as-code
  • Privacy-conscious engineers
  • Developers cutting LLM API costs
  • RAG pipelines with oversized retrieved context
  • Teams running coding agents
Pros
  • Fully open-source, no required subscription
  • Supports any model, cloud or local
  • Deep customization via config-as-code
  • Works in VS Code and JetBrains
  • Autonomous agent mode added in 2026
  • Open source under the MIT license and free to self-host
  • Genuine free tier: 1M tokens/month with no credit card
  • Cheap
  • transparent usage pricing at $0.30 per 1M tokens
  • Runs on CPU with no GPU or model download (~60ms per compression)
Cons
  • Steeper setup than plug-and-play tools
  • Quality depends on chosen models
  • Evolving product direction can shift features
  • Local models need capable hardware
  • Less hand-holding than commercial assistants
  • Early-stage project with a small team and limited independent track record
  • Headline compression (~58-82%) and >98% retention figures are vendor-reported and benchmark-dependent
  • Compression is lossy
  • so aggressive settings can drop context that later turns out to matter
  • Text-only: it does not compress image or audio context

Comparison generated from each tool's listing. Add or remove tools above to change it.