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?" Part of vizcn by vibecoding.tech — agent-first SVG viz forms, no chart libraries.
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' },
]}
/>
)
}
Part of vizcn · by vibecoding.tech — browse the full library on 21st.dev.