XFMS - Xpansion Framework Model Source

Pick the right LLM for any task.

Community: Submitted by a user or imported; check the owner before granting accessOnlineAPI key requiredGlobalFreeCan modify data

What it can do

  • Rank: Rank LLMs for a stated purpose. Returns a shortlist with weights, scores, and plain-English rationale per pick. Use when the user wants to see and compare alternatives, not just one answer.
  • Pick: Return the single best LLM for a stated purpose. Concise output, no list. Use when the user has settled on the criteria and just wants one answer.
  • Discover: Show which quality dimensions matter for a stated purpose, WITHOUT ranking any models. Returns the inferred weights and the discovery-walk trace. Useful for understanding how XFMS interprets

What data it sees

Do you need an account

An API key from the service settings is required

Pick the right LLM for any task. XFMS infers which quality in its catalog against those dimensions, and returns a ranked shortlist with plain-English rationale per pick.

The catalog updates continuously from 8 independent third-party evaluators — no provider self-reports, no single-source benchmarks. Missing data is recorded as missing, not interpolated.

Three tools:

  • rank — ranked shortlist with weights and rationale
  • pick — single best pick
  • discover — which quality dimensions matter, without ranking

No OpenRouter key needed. The hosted endpoint covers inference; you only need a free XFMS access token from xpansion .dev/xfms/get-started. Part of the Xpansion Framework — an enforcement layer for AI-assisted work.

Server tool list (3)

Raw names from tools/list. Only developers need these.

rankRank LLMs for a stated purpose. Returns a shortlist with weights, scores, and plain-English rationale per pick. Use when the user wants to see and compare alternatives, not just one answer.
pickReturn the single best LLM for a stated purpose. Concise output, no list. Use when the user has settled on the criteria and just wants one answer.
discoverShow which quality dimensions matter for a stated purpose, WITHOUT ranking any models. Returns the inferred weights and the discovery-walk trace. Useful for understanding how XFMS interprets the purpose before committing to a pick.