Leaderboard Table

Component 31

About

Want this built into your product? AI agents write the code, an engineer directs them: https://vibecoding.tech/services?utm_source=21st&utm_medium=component Book a call and say promo code 21ST to get a free 3-day development trial. Score bars with +/-std whiskers plus numeric economy columns (cost/tokens/steps), one row per model run, with version and Best/All-effort-levels toggles, model filter, and rank-morphing rows. Answers: "Who leads on score, with what confidence spread, and what does that score cost?"

Built with React and Tailwind. Copy the prompt and paste it into Claude Code, Cursor or Lovable: your agent adds Leaderboard Table to your project and fits it to your theme.

Code

How Leaderboard Table is used: the demo's code. The component's own source comes with a free account.

Usage.tsx

import { LeaderboardBars } from '@/components/ui/leaderboard-table'
import type { LeaderboardModel, LeaderboardRun } from '@/components/ui/leaderboard-table'

// vendor identity colors (color follows the entity): a vivid set that
// holds on both light and dark surfaces — same rail as frontier-board
const FAMILY_COLOR = {
  atlas: '#E8734A',
  nova: '#10A37F',
  orion: '#4285F4',
  vega: '#D946EF',
  quasar: '#5B6EE1',
} as const

/**
 * Demo: fictional models with real-leaderboard density — the same data
 * rail as the frontier-board demo (one dataset feeds both forms). Every
 * name is invented; values mirror real coding-leaderboard density.
 */

const lr = (
  variant: string | undefined,
  cost: number,
  score: number,
  extra?: Partial<LeaderboardRun>,
): LeaderboardRun => {
  const { x, ...rest } = extra ?? {}
  return {
    variant,
    score,
    std: 2,
    x: {
      cost,
      tokens: Math.round(cost * 6.8 + score * 0.4),
      steps: Math.round(cost * 2.2 + 14),
      ...x,
    },
    ...rest,
  }
}

const V11: LeaderboardModel[] = [
  {
    id: 'atlas-4',
    color: FAMILY_COLOR.atlas,
    badge: 'M',
    runs: [
      lr('max', 21.63, 70.4, { std: 4, x: { tokens: 119, steps: 88 } }),
      lr('high', 13.4, 70),
      lr('medium', 9.3, 68.7),
      lr('low', 6.2, 65.3),
      lr('minimal', 3.7, 59.6),
    ],
  },
  {
    id: 'atlas-3.5',
    color: FAMILY_COLOR.atlas,
    badge: 'M',
    runs: [
      lr('max', 13.22, 59.1, { x: { tokens: 135, steps: 120 } }),
      lr('xhigh', 8.0, 54.3),
      lr('high', 4.3, 51.7),
      lr('medium', 3.5, 48.6),
      lr('low', 2.7, 40.8),
    ],
  },
  {
    id: 'atlas-3',
    color: FAMILY_COLOR.atlas,
    badge: 'M',
    runs: [
      lr('max', 26.4, 54, { std: 4, x: { tokens: 214, steps: 268 } }),
      lr('xhigh', 11.9, 49.7),
      lr('high', 8.3, 48.3),
      lr('medium', 4.4, 39.9),
      lr('low', 2.3, 30.5),
    ],
  },
  {
    id: 'atlas-2',
    color: FAMILY_COLOR.atlas,
    badge: 'M',
    runs: [lr('high', 5.52, 30.2, { std: 4, x: { tokens: 76, steps: 134 } })],
  },
  {
    id: 'nova-5',
    color: FAMILY_COLOR.nova,
    badge: 'H',
    runs: [
      lr('xhigh', 7.23, 67.1, { std: 6, x: { tokens: 46, steps: 82 } }),
      lr('high', 4.9, 64.4),
      lr('medium', 2.6, 53.9),
      lr('low', 1.2, 27.2),
    ],
  },
  {
    id: 'nova-4',
    color: FAMILY_COLOR.nova,
    badge: 'H',
    runs: [lr('xhigh', 5.65, 51.7, { x: { tokens: 71, steps: 70 } })],
  },
  {
    id: 'orion-72b',
    color: FAMILY_COLOR.orion,
    badge: 'V',
    runs: [
      lr('max', 3.92, 43.7, { x: { tokens: 78, steps: 129 } }),
      lr('high', 2.9, 36.3),
    ],
  },
  {
    id: 'vega-flash',
    color: FAMILY_COLOR.vega,
    badge: 'S',
    runs: [lr('medium', 7.34, 37.2, { x: { tokens: 276, steps: 86 } })],
  },
  {
    id: 'vega-pro',
    color: FAMILY_COLOR.vega,
    badge: 'S',
    runs: [lr('high', 9.48, 11.8, { x: { tokens: 196, steps: 81 } })],
  },
  {
    id: 'quasar-coder',
    color: FAMILY_COLOR.quasar,
    badge: 'Q',
    runs: [lr(undefined, 2.82, 30.7, { std: 1, x: { tokens: 59, steps: 149 } })],
  },
]

/** v1 — the previous snapshot: a notch lower and cheaper, two models fewer. */
const V1: LeaderboardModel[] = V11.filter(
  (m) => m.id !== 'orion-72b' && m.id !== 'quasar-coder',
).map((m) => ({
  ...m,
  runs: m.runs.map((run) => ({
    ...run,
    score: Math.round((run.score - 4.5) * 10) / 10,
    x: {
      cost: Math.round(run.x.cost * 92) / 100,
      tokens: Math.round(run.x.tokens * 0.92),
      steps: Math.round(run.x.steps * 0.92),
    },
  })),
}))

export default function LeaderboardTableDemo() {
  return (
    <LeaderboardBars
      meta="113 tasks · updated Jul 1, 2026"
      footnote="All runs executed on the same harness with a 100-step budget; cost is the average per solved task. Fictional models, deterministic demo data."
      versions={[
        { key: 'v1.1', label: 'v1.1', models: V11 },
        { key: 'v1', label: 'v1', models: V1 },
      ]}
      columns={[
        { key: 'cost', label: 'cost', prefix: '$', decimals: 2 },
        { key: 'tokens', label: 'tokens', suffix: 'k' },
        { key: 'steps', label: 'steps' },
      ]}
    />
  )
}