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Not Diamond vs SuperCompress

Not DiamondSuperCompress

Bottom line: Not Diamond for teams running multiple LLMs in production; SuperCompress for developers cutting LLM API costs.

Not DiamondNot Diamond

Intelligent LLM router that picks the best model per query

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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
llm-routermodel-routingcost-optimizationai-infrastructurellmops
llmdeveloper-toolscost-optimization
Best for
  • Teams running multiple LLMs in production
  • Builders of coding and AI agents
  • Cost-sensitive LLM applications
  • Developers cutting LLM API costs
  • RAG pipelines with oversized retrieved context
  • Teams running coding agents
Pros
  • Directly targets cost savings without quality loss
  • Supports custom routers trained on your own data
  • Low added router latency (cited ~100-150ms)
  • Free early-access tier to evaluate
  • Works with major providers and coding agents
  • 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
  • Routing benefits depend heavily on your specific workload
  • Exact per-token pricing is not fully published
  • Vendor-cited savings figures need independent validation
  • Adds an external dependency and network hop
  • Crowded, fast-moving competitive category
  • 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

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