SkillsMay 13, 2026·2 min read

models — TUI for AI Models and Benchmarks

models is a Rust TUI and CLI for browsing roughly 4,000 AI models, 85+ providers, and 400 benchmark entries with local commands instead of browser tabs.

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Agent ready

This asset can be read and installed directly by agents

TokRepo exposes a universal CLI command, install contract, metadata JSON, adapter-aware plan, and raw content links so agents can judge fit, risk, and next actions.

Native · 98/100Policy: allow
Agent surface
Any MCP/CLI agent
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Install
Single
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Trust: Established
Entrypoint
Asset
Universal CLI install command
npx tokrepo install b2ce1986-1294-58f8-89e7-04ba2cf049ca
install contractmetadata JSONadapter planraw content
Intro

models is a Rust TUI and CLI for browsing roughly 4,000 AI models, 85+ providers, and 400 benchmark entries with local commands instead of browser tabs.

Best for: developers comparing model providers, pricing, coding-agent support, and benchmark posture without juggling many dashboards

Works with: macOS, Linux, Windows, Homebrew or Cargo installs, terminal workflows, local model/provider research

Setup time: 5-8 minutes

Key facts (verified)

  • GitHub: 418 stars · 17 forks · pushed 2026-05-13.
  • License: MIT; owner avatar verified from GitHub API for reyamira.
  • Entry point checked from README: brew install models.

Main

models is not a serving layer; it is a decision surface. The value is that provider, benchmark, and status information can be queried locally while you work inside a repo.

Because the README ships multiple install channels, it is easy to standardize across teams that do not all share the same workstation setup.

The 4,000-model and 85+ provider scope matters: this tool is useful when model choice changes weekly and you need a fast terminal-native way to see what shifted.

Source-backed notes

  • README highlights roughly 4,000 models across 85+ providers.
  • The project also surfaces around 400 benchmark entries from Artificial Analysis.
  • Install paths include Homebrew, Cargo, Scoop, and AUR.

FAQ

Q: Does it host models? A: No. It helps you browse and compare model and benchmark data from a terminal interface.

Q: What is the fastest install path? A: Homebrew on macOS/Linux or Cargo on any platform, both documented in the README.

Q: Why use it instead of websites? A: It keeps model research close to terminal-based workflows and reduces dashboard context switching.

🙏

Source & Thanks

Source: https://github.com/reyamira/models > License: MIT > GitHub stars: 418 · forks: 17

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