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Conifer

Local-first least-cost inference router that keeps routine requests on your own hardware

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freeDR 16Distributed as a download with a separate business track; no consumer price sheet is published as of July 2026, so any commercial tier is a sales conversation.View full pricing →

About Conifer

Conifer bills itself as the front door to all inference, and its specific claim is a local-first least-cost routing system that cuts token spend by 80% or more. The idea is that most requests hitting a frontier API do not need a frontier model — a classification, a reformat, a short extraction, a routine summary. Conifer sits in front of the call and routes each request down the cheapest path that will still satisfy it, preferring local execution where the hardware in front of you can handle the job and reaching for a hosted model only when it genuinely has to. Because the routing decision happens locally, requests that never leave the machine also never leave your control, which is where the company's stated direction — private superintelligence — comes from: the cost argument and the privacy argument are the same architectural choice viewed from two sides. The product is distributed as a download with a model catalog, documentation, and a business track alongside the individual one. The site is deliberately unconventional, leading with large ASCII art over the usual feature grid, and it publishes a models list and docs rather than a marketing funnel. As a category this sits next to model gateways and routers, but the local-first default is the differentiator — most routers move traffic between hosted providers, while Conifer's first choice is not to send it anywhere.

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Key Features

Least-cost routing across local and hosted inference paths
Local-first default so routine requests never leave the machine
Published model catalog and developer documentation
Single front door for mixed local and hosted inference
Stated 80%+ reduction in token spend
Separate business track alongside individual downloads

Conifer Pros & Cons

Pros

  • +Cost and privacy improve from the same design decision
  • +Local execution removes per-token cost entirely for the requests it can absorb
  • +Slots in front of existing calls rather than replacing your stack

⚠️ Cons

  • The 80% figure depends heavily on how routine your workload actually is
  • Local routing is bounded by the hardware you happen to have
  • Presentation is unusually opaque — no pricing and an ASCII-art homepage

Who Is Conifer Best For?

👤Developers with high volumes of routine, low-complexity model calls
👤Privacy-sensitive workloads that should stay on-device by default
👤Teams whose inference bill is dominated by cheap tasks paying frontier prices

Tags

inference routinglocal llmcost optimizationprivacymodel gateway
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