// Outcomes.jsx — "Optimize for" pane between The Fix tree and the Quote. // // Two propositions, no card chrome: // 1. Better models — more hypotheses tried, only verifier-passing ones ship // 2. Faster inference — kernel/quantization/decoding optimizations on your stack // // Below: the frontier benchmark strip and a trusted-by logo bar. const Outcomes_css = ` .cB-out{background:var(--ink-900);padding:120px 40px 64px; border-top:1px solid transparent; border-image:linear-gradient(90deg,transparent,rgba(247,247,237,0.20) 50%,transparent) 1;} .cB-out__inner{max-width:1280px;margin:0 auto;} /* Section heading */ .cB-out__head{display:flex;justify-content:space-between;align-items:flex-end; margin-bottom:96px;flex-wrap:wrap;gap:20px;} .cB-out__headL{display:flex;flex-direction:column;} .cB-out__title{font-family:var(--font-display);font-size:clamp(40px,4.4vw,56px);font-weight:400; letter-spacing:-0.03em;line-height:1.05;margin:0;} .cB-out__title em{font-family:var(--font-serif);font-style:italic;} .cB-out__sub{font-family:var(--font-display);font-size:26px;font-weight:400; letter-spacing:-0.015em;line-height:1.2;margin:14px 0 0; color:rgba(247,247,237,0.55);} .cB-out__kicker{font-family:var(--font-mono);font-size:11px;letter-spacing:0.08em; text-transform:uppercase;color:rgba(247,247,237,0.5);} /* Two propositions, side by side, no boxes */ .cB-out__props{display:grid;grid-template-columns:1fr 1fr;gap:80px; margin-bottom:96px;} .cB-out__prop{display:flex;flex-direction:column;} .cB-out__propKick{font-family:var(--font-mono);font-size:11px; letter-spacing:0.08em;text-transform:uppercase;color:var(--lime-500); margin-bottom:24px;} .cB-out__propTitle{font-family:var(--font-serif);font-style:italic; font-size:clamp(56px,6vw,84px);font-weight:400;letter-spacing:-0.025em; line-height:0.95;margin:0 0 28px;color:var(--cream-50);} .cB-out__propBody{font-size:18px;line-height:1.55; color:rgba(247,247,237,0.75);margin:0;max-width:42ch;} /* ---- Variant B: Numbered slab ---- */ .cB-out__props--numbered{} .cB-out__props--numbered .cB-out__propKick{display:none;} .cB-out__props--numbered .cB-out__propNum{font-family:var(--font-mono); font-size:64px;font-weight:400;letter-spacing:-0.05em;line-height:1; color:var(--lime-500);margin:0 0 18px;} .cB-out__props--numbered .cB-out__propTitle{font-family:var(--font-display); font-style:normal;font-size:clamp(40px,4.4vw,60px);} /* ---- Variant C: Stacked rows ---- */ .cB-out__props--stacked{display:flex;flex-direction:column;gap:0;} .cB-out__props--stacked .cB-out__prop{display:grid; grid-template-columns:1fr 1.1fr;gap:64px;align-items:flex-start; padding:48px 0;border-top:1px solid rgba(193,250,29,0.22);} .cB-out__props--stacked .cB-out__prop:last-child{border-bottom:1px solid rgba(193,250,29,0.22);} .cB-out__props--stacked .cB-out__propLeft{display:flex;flex-direction:column;} .cB-out__props--stacked .cB-out__propTitle{margin:0;} .cB-out__props--stacked .cB-out__propBody{font-size:17px; margin-top:18px;max-width:54ch;} /* ---- Variant D: Accent column ---- */ .cB-out__props--accent .cB-out__prop{padding-left:28px; border-left:2px solid var(--lime-500);} /* ---- Variant E: Inline contrast ---- */ .cB-out__props--inline{display:flex;flex-direction:column;gap:48px; margin-bottom:96px;} .cB-out__inlineHead{font-family:var(--font-display);font-size:clamp(40px,4.4vw,60px); font-weight:400;letter-spacing:-0.025em;line-height:1.05;color:var(--cream-50); margin:0;max-width:24ch;} .cB-out__inlineHead em{font-family:var(--font-serif);font-style:italic; color:var(--lime-500);} .cB-out__inlineBodies{display:grid;grid-template-columns:1fr 1fr;gap:80px;} .cB-out__inlineBody{display:flex;flex-direction:column;} .cB-out__inlineBody .cB-out__propKick{margin-bottom:14px;} .cB-out__inlineBody p{font-size:17px;line-height:1.55; color:rgba(247,247,237,0.75);margin:0;max-width:42ch;} /* ---------- Dashboard variant: metrics panel ---------- */ .cB-out__dash{margin-bottom:96px;background:#1F1B2A; border:1px solid rgba(255,255,255,0.1);border-radius:14px; padding:24px 28px 26px;box-shadow:0 22px 60px -20px rgba(0,0,0,0.6); font-family:var(--font-mono);} .cB-out__dashHead{display:flex;justify-content:space-between;align-items:center; gap:24px;padding-bottom:18px;border-bottom:1px solid rgba(255,255,255,0.08); margin-bottom:22px;} .cB-out__dashTabs{display:flex;align-items:center;gap:0;flex-wrap:wrap;} .cB-out__dashTab{font-family:var(--font-mono);font-size:13px; letter-spacing:-0.01em;color:rgba(247,247,237,0.5);padding:10px 0; margin-right:28px;border:0;background:transparent;cursor:pointer; border-bottom:1.5px solid transparent;transition:color 160ms,border-color 160ms; display:inline-flex;align-items:center;gap:8px;font-weight:500;} .cB-out__dashTab:hover{color:rgba(247,247,237,0.85);} .cB-out__dashTab.is-active{color:var(--cream-50); border-bottom-color:var(--lime-500);} .cB-out__dashKicker{font-family:var(--font-mono);font-size:10.5px;letter-spacing:0.08em; text-transform:uppercase;color:rgba(247,247,237,0.5); display:inline-flex;align-items:center;gap:8px;} .cB-out__dashKicker .dot{width:6px;height:6px;border-radius:50%; background:var(--lime-500);box-shadow:0 0 6px var(--lime-500); animation:psaPulse 1.6s ease-in-out infinite;} /* Hero objective + metric */ .cB-out__dashHero{display:grid;grid-template-columns:minmax(0,1fr) auto; gap:32px;align-items:end;padding:0 0 22px; border-bottom:1px solid rgba(255,255,255,0.06);margin-bottom:18px;} .cB-out__dashObjective{display:flex;flex-direction:column;gap:8px;min-width:0;} .cB-out__dashObjLbl{font-family:var(--font-mono);font-size:10.5px;letter-spacing:0.08em; text-transform:uppercase;color:rgba(247,247,237,0.45);} .cB-out__dashObjName{font-family:var(--font-display);font-size:28px;font-weight:400; letter-spacing:-0.02em;line-height:1.1;color:var(--cream-50);} .cB-out__dashObjSub{font-family:var(--font-mono);font-size:11.5px;letter-spacing:-0.01em; color:rgba(247,247,237,0.5);} .cB-out__dashHeroR{display:flex;align-items:flex-end;gap:18px;} .cB-out__dashHeroVal{font-family:var(--font-display);font-size:48px;font-weight:400; letter-spacing:-0.025em;line-height:1;color:var(--lime-500); display:flex;align-items:baseline;gap:8px;} .cB-out__dashHeroVal .unit{font-size:18px;color:rgba(193,250,29,0.7); letter-spacing:-0.01em;font-weight:400;} .cB-out__dashSpark{flex-shrink:0;} /* Guardrail rows */ .cB-out__dashGuardLbl{font-family:var(--font-mono);font-size:10.5px;letter-spacing:0.08em; text-transform:uppercase;color:rgba(247,247,237,0.45);margin-bottom:10px; display:flex;align-items:center;gap:10px;} .cB-out__dashGuardLbl::after{content:"";flex:1;height:1px; background:rgba(255,255,255,0.06);} .cB-out__dashRows{display:flex;flex-direction:column;} .cB-out__dashRow{display:grid; grid-template-columns:10px minmax(0,1fr) 130px; align-items:center;gap:16px;padding:12px 4px; border-bottom:1px solid rgba(255,255,255,0.05); font-size:13px;letter-spacing:-0.01em;} .cB-out__dashRow:last-child{border-bottom:0;} .cB-out__dashDot{width:8px;height:8px;border-radius:50%; background:rgba(247,247,237,0.3);} .cB-out__dashDot.lime{background:var(--lime-500);box-shadow:0 0 6px rgba(193,250,29,0.55);} .cB-out__dashDot.violet{background:var(--violet-400);box-shadow:0 0 6px rgba(178,162,255,0.5); animation:psaPulse 1.6s ease-in-out infinite;} .cB-out__dashMetric{color:var(--cream-50);font-weight:500; white-space:nowrap;overflow:hidden;text-overflow:ellipsis;min-width:0; display:flex;align-items:baseline;gap:10px;flex-wrap:nowrap;} .cB-out__dashMetric .ref{color:rgba(247,247,237,0.4);font-size:11.5px; font-weight:400;letter-spacing:-0.01em; white-space:nowrap;overflow:hidden;text-overflow:ellipsis;min-width:0;} .cB-out__dashDelta{font-weight:500;letter-spacing:-0.01em;text-align:right; font-size:13px;color:var(--lime-500);} .cB-out__dashDelta.run{color:var(--violet-400);} .cB-out__dashDelta.flat{color:rgba(247,247,237,0.5);} .cB-out__dashStatus{font-family:var(--font-mono);font-size:10px; letter-spacing:0.04em;text-align:right; color:rgba(247,247,237,0.5);font-weight:400;} .cB-out__dashFoot{display:grid;grid-template-columns:repeat(3,1fr); margin-top:22px;padding-top:18px;border-top:1px solid rgba(255,255,255,0.08); gap:24px;} .cB-out__dashStat{display:flex;flex-direction:column;gap:4px;} .cB-out__dashStatVal{font-family:var(--font-display);font-size:28px; font-weight:400;letter-spacing:-0.02em;color:var(--cream-50);line-height:1;} .cB-out__dashStatLbl{font-family:var(--font-mono);font-size:10.5px; letter-spacing:0.08em;text-transform:uppercase;color:rgba(247,247,237,0.5);} @media (max-width: 760px){ .cB-out__dashHero{grid-template-columns:1fr;gap:18px;align-items:flex-start;} .cB-out__dashRow{grid-template-columns:10px minmax(0,1fr); gap:12px;} .cB-out__dashStatus{display:none;} .cB-out__dashFoot{grid-template-columns:repeat(3,1fr);} } /* ---------- Frontier benchmark strip ---------- */ .cB-out__bench{margin-top:0;padding-top:64px;position:relative;} .cB-out__bench::before{content:"";position:absolute; top:-180px;left:-200px;width:780px;height:520px; background:radial-gradient(ellipse 50% 50% at 50% 50%, rgba(247,247,237,0.12) 0%, rgba(247,247,237,0.05) 30%, rgba(247,247,237,0.02) 55%, transparent 75%); pointer-events:none;z-index:0; filter:blur(8px);} .cB-out__bench > *{position:relative;z-index:1;} .cB-out__benchHead{display:flex;justify-content:space-between;align-items:flex-end; flex-wrap:wrap;gap:20px;margin-bottom:36px;} .cB-out__benchHeadL{display:flex;flex-direction:column;gap:10px;min-width:0;} .cB-out__benchEyebrow{font-family:var(--font-mono);font-size:11px;letter-spacing:0.08em; text-transform:uppercase;color:var(--lime-500);} .cB-out__benchTitle{font-family:var(--font-display);font-size:24px;font-weight:400; letter-spacing:-0.02em;line-height:1.2;margin:0;color:var(--cream-50);} .cB-out__benchTitle em{font-family:var(--font-serif);font-style:italic;} .cB-out__benchKicker{font-family:var(--font-mono);font-size:11px;letter-spacing:0.08em; text-transform:uppercase;color:rgba(247,247,237,0.5);} .cB-out__benchRows{display:flex;flex-direction:column;gap:14px; max-width:880px;margin-left:auto;margin-right:auto;} .cB-out__benchRow{display:grid;grid-template-columns:200px 1fr 80px; align-items:center;gap:24px;} .cB-out__benchName{font-family:var(--font-mono);font-size:13px; letter-spacing:-0.01em;color:rgba(247,247,237,0.85);} .cB-out__benchName strong{color:var(--cream-50);font-weight:500;} .cB-out__benchTrack{position:relative;height:28px; background:rgba(255,255,255,0.04);border-radius:4px;overflow:hidden;} .cB-out__benchBar{position:absolute;top:0;bottom:0;left:0; background:rgba(178,162,255,0.35);border-right:1px solid rgba(178,162,255,0.6); transition:width 600ms cubic-bezier(0.2,0.7,0.2,1);} .cB-out__benchBar.is-mira{background:linear-gradient(90deg,rgba(193,250,29,0.18), rgba(193,250,29,0.55));border-right-color:var(--lime-500); box-shadow:0 0 24px rgba(193,250,29,0.25);} .cB-out__benchVal{font-family:var(--font-display);font-size:22px;font-weight:400; letter-spacing:-0.02em;color:rgba(247,247,237,0.7);text-align:right;} .cB-out__benchVal.is-mira{color:var(--lime-500);} .cB-out__benchFoot{margin-top:24px;font-family:var(--font-mono);font-size:11px; letter-spacing:-0.01em;color:rgba(247,247,237,0.4);max-width:880px; margin-left:auto;margin-right:auto;} .cB-out__benchFoot a{color:rgba(247,247,237,0.72);text-decoration:none;} .cB-out__benchFoot a:hover{color:var(--cream-50);} /* ---------- Trusted-by bar ---------- */ .cB-out__trust{margin-top:80px;padding-top:56px; border-top:1px solid rgba(255,255,255,0.08); display:flex;flex-direction:row;align-items:center; gap:48px;flex-wrap:wrap;} .cB-out__trustLabel{font-family:var(--font-mono);font-size:11px; letter-spacing:0.14em;text-transform:uppercase;color:rgba(247,247,237,0.55); flex:0 0 auto;} .cB-out__trustLogos{display:flex;align-items:center;justify-content:flex-end; gap:64px;flex-wrap:wrap;flex:1 1 auto;} /* ---------- Built-by bar (researcher pedigree, secondary) ---------- */ .cB-out__builtby{margin-top:32px;padding-top:32px; display:flex;flex-direction:row;align-items:center; gap:48px;flex-wrap:nowrap;} .cB-out__builtbyLabel{font-family:var(--font-mono);font-size:11px; letter-spacing:0.14em;text-transform:uppercase;color:rgba(247,247,237,0.45); flex:0 0 auto;white-space:nowrap;} .cB-out__builtbyMarquee{flex:1 1 auto;min-width:0;overflow:hidden; position:relative; -webkit-mask-image:linear-gradient(90deg, transparent 0, #000 6%, #000 94%, transparent 100%); mask-image:linear-gradient(90deg, transparent 0, #000 6%, #000 94%, transparent 100%);} .cB-out__builtbyTrack{display:inline-flex;align-items:center; width:max-content; white-space:nowrap; animation: builtbySlide 22s linear infinite; will-change:transform;} .cB-out__builtbyHalf{display:inline-flex;align-items:center;gap:64px; padding-right:64px;flex:0 0 auto;} @keyframes builtbySlide{ 0% { transform: translateX(0); } 100% { transform: translateX(-50%); } } .cB-out__builtbyLogo{height:30px;opacity:1; display:inline-flex;align-items:center;flex:0 0 auto; filter:brightness(0) invert(1); transition:opacity 200ms;} .cB-out__builtbyLogo:hover{opacity:1;} .cB-out__builtbyLogo img{height:100%;width:auto;display:block;object-fit:contain;} .cB-out__builtbyLogo.is-tall{height:34px;} .cB-out__builtbyLogo.is-short{height:22px;} .cB-out__builtbyLogo.is-google{height:48px;} .cB-out__builtbyLogo.is-anthropic{height:24px;} .cB-out__builtbyLogo.no-filter{filter:none;} /* Color-keep variants — show original logo color (slightly desaturated). */ .cB-out__builtbyLogo.is-color{filter:saturate(0.9);opacity:0.92;} @media (max-width: 760px) { .cB-out__builtby{gap:20px;} .cB-out__builtbyTrack{animation-duration:28s;} .cB-out__builtbyHalf{gap:40px;padding-right:40px;} .cB-out__builtbyLogo{height:24px;} .cB-out__builtbyLogo.is-tall{height:28px;} .cB-out__builtbyLogo.is-google{height:38px;} .cB-out__builtbyLogo.is-anthropic{height:22px;} } .cB-out__trustLogo{height:28px;opacity:0.85;color:rgba(247,247,237,0.9); transition:opacity 200ms;display:inline-flex;align-items:center; filter:grayscale(1);} .cB-out__trustLogo:hover{opacity:1;} .cB-out__trustLogo svg{height:100%;width:auto;display:block;} .cB-out__trustLogo img{height:100%;width:auto;display:block;object-fit:contain;} @media (max-width: 900px) { .cB-out__props{grid-template-columns:1fr;gap:64px;} .cB-out__props--stacked .cB-out__prop{grid-template-columns:1fr;gap:24px;} .cB-out__inlineBodies{grid-template-columns:1fr;gap:48px;} } /* ============================================================ NEW VARIANT A — "charted": each prop with its own live chart ============================================================ */ .cB-out__props--charted{display:grid;grid-template-columns:1fr 1fr; gap:0;column-gap:0;margin-bottom:96px; border-top:1px solid rgba(247,247,237,0.10); border-bottom:1px solid rgba(247,247,237,0.10);} .cB-out__props--charted .cB-out__prop{ padding:56px 56px 48px;display:flex;flex-direction:column; position:relative;} .cB-out__props--charted .cB-out__prop:first-child{ border-right:1px solid rgba(247,247,237,0.10);} .cB-out__props--charted .cB-out__propKick{margin-bottom:18px;} .cB-out__props--charted .cB-out__propTitle{ font-size:clamp(48px,5vw,68px);margin-bottom:20px;} .cB-out__props--charted .cB-out__propBody{ font-size:17px;max-width:46ch;margin-bottom:36px;} .cB-out__chartWrap{margin-top:auto;display:flex;flex-direction:column;gap:14px;} .cB-out__chartLbl{display:flex;justify-content:space-between;align-items:baseline; font-family:var(--font-mono);font-size:10.5px;letter-spacing:0.08em; text-transform:uppercase;color:rgba(247,247,237,0.45);} .cB-out__chartLbl strong{font-family:var(--font-display); text-transform:none;letter-spacing:-0.02em; font-size:22px;font-weight:400;color:var(--lime-500);} .cB-out__chart{width:100%;height:120px;display:block;} .cB-out__chartFoot{font-family:var(--font-mono);font-size:10.5px; letter-spacing:0.04em;color:rgba(247,247,237,0.4); display:flex;justify-content:space-between;} @media (max-width: 900px){ .cB-out__props--charted{grid-template-columns:1fr;} .cB-out__props--charted .cB-out__prop:first-child{ border-right:0;border-bottom:1px solid rgba(247,247,237,0.10);} } /* ============================================================ NEW VARIANT B — "unified": one hero pareto graphic, props below ============================================================ */ .cB-out__paretoWrap{margin-bottom:80px; border:1px solid rgba(247,247,237,0.10);border-radius:14px; background:linear-gradient(180deg,rgba(247,247,237,0.02),transparent 60%); padding:32px 40px 28px;position:relative;overflow:hidden;} .cB-out__paretoHead{display:flex;justify-content:space-between;align-items:flex-start; gap:24px;margin-bottom:18px;flex-wrap:wrap;} .cB-out__paretoEyebrow{font-family:var(--font-mono);font-size:10.5px; letter-spacing:0.08em;text-transform:uppercase;color:rgba(247,247,237,0.5);} .cB-out__paretoTitle{font-family:var(--font-display);font-size:22px; font-weight:400;letter-spacing:-0.015em;color:var(--cream-50); margin:6px 0 0;line-height:1.25;} .cB-out__paretoLegend{display:flex;gap:20px;align-items:center; font-family:var(--font-mono);font-size:11px;letter-spacing:-0.01em; color:rgba(247,247,237,0.6);} .cB-out__paretoLegend .swatch{display:inline-block;width:8px;height:8px; border-radius:50%;margin-right:6px;vertical-align:middle;} .cB-out__pareto{width:100%;height:340px;display:block;} .cB-out__paretoFoot{font-family:var(--font-mono);font-size:10.5px; letter-spacing:-0.01em;color:rgba(247,247,237,0.4);margin-top:8px; display:flex;justify-content:space-between;flex-wrap:wrap;gap:12px;} .cB-out__props--unified{display:grid;grid-template-columns:1fr 1fr; gap:80px;margin-bottom:96px;} .cB-out__props--unified .cB-out__prop{display:flex;flex-direction:column; padding-top:18px;border-top:1px solid rgba(247,247,237,0.10);} .cB-out__props--unified .cB-out__propKick{margin-bottom:18px;} .cB-out__props--unified .cB-out__propTitle{ font-size:clamp(44px,4.6vw,60px);margin-bottom:20px;} .cB-out__props--unified .cB-out__propBody{font-size:17px;max-width:46ch;} @media (max-width: 900px){ .cB-out__props--unified{grid-template-columns:1fr;gap:48px;} .cB-out__pareto{height:260px;} } /* ============================================================ NEW VARIANT C — "metric": typographic with a single big number ============================================================ */ .cB-out__props--metric{display:grid;grid-template-columns:1fr 1fr; gap:0;margin-bottom:96px;} .cB-out__props--metric .cB-out__prop{padding:0 56px; border-left:1px solid rgba(247,247,237,0.10); display:flex;flex-direction:column;gap:0;} .cB-out__props--metric .cB-out__prop:first-child{padding-left:0;border-left:0;} .cB-out__props--metric .cB-out__propKick{margin-bottom:14px;} .cB-out__props--metric .cB-out__propTitle{ font-size:clamp(44px,4.6vw,60px);margin-bottom:18px;} .cB-out__props--metric .cB-out__propBody{font-size:16.5px;max-width:42ch; margin-bottom:32px;} .cB-out__metricBig{font-family:var(--font-display);font-weight:400; letter-spacing:-0.035em;line-height:0.92;color:var(--cream-50); font-size:clamp(72px,8vw,112px); display:grid;grid-template-columns:auto 1fr;align-items:end; column-gap:24px; border-top:1px solid rgba(247,247,237,0.10);padding-top:28px; margin-top:auto;} .cB-out__metricBig em{font-family:var(--font-serif);font-style:italic; color:var(--lime-500);} .cB-out__metricNum{display:block;white-space:nowrap;} .cB-out__metricUnit{font-family:var(--font-mono);font-size:13px; letter-spacing:0.04em;text-transform:uppercase; color:rgba(247,247,237,0.55);font-weight:400; padding-bottom:18px;line-height:1.5; align-self:end;} .cB-out__metricSpark{display:flex;align-items:center;gap:14px;margin-top:14px; font-family:var(--font-mono);font-size:10.5px;letter-spacing:0.06em; text-transform:uppercase;color:rgba(247,247,237,0.45);} /* ============================================================ NEW VARIANT D — "pickyourmetric": grid of objectives, two highlighted ============================================================ */ .cB-out__pym{display:grid;grid-template-columns:380px 1fr;gap:80px; align-items:start;margin-bottom:96px;} .cB-out__pymLead{display:flex;flex-direction:column;gap:18px; position:sticky;top:120px;} .cB-out__pymLeadKick{font-family:var(--font-mono);font-size:11px; letter-spacing:0.08em;text-transform:uppercase;color:var(--lime-500);} .cB-out__pymLeadTitle{font-family:var(--font-display);font-size:36px; font-weight:400;letter-spacing:-0.025em;line-height:1.1; color:var(--cream-50);margin:0;} .cB-out__pymLeadTitle em{font-family:var(--font-serif);font-style:italic;} .cB-out__pymLeadBody{font-size:16px;line-height:1.55; color:rgba(247,247,237,0.7);margin:0;max-width:38ch;} .cB-out__pymLeadBody strong{color:var(--cream-50);font-weight:500;} .cB-out__pymGrid{display:grid;grid-template-columns:1fr 1fr; gap:0;border-top:1px solid rgba(247,247,237,0.10); border-left:1px solid rgba(247,247,237,0.10);} .cB-out__pymCell{padding:28px 28px 32px; border-right:1px solid rgba(247,247,237,0.10); border-bottom:1px solid rgba(247,247,237,0.10); display:flex;flex-direction:column;gap:10px; position:relative;min-height:172px;} .cB-out__pymCellKick{font-family:var(--font-mono);font-size:10.5px; letter-spacing:0.08em;text-transform:uppercase; color:rgba(247,247,237,0.45); display:flex;align-items:center;gap:8px;} .cB-out__pymCellKick .num{color:rgba(247,247,237,0.35);} .cB-out__pymCellTitle{font-family:var(--font-display);font-size:28px; font-weight:400;letter-spacing:-0.022em;line-height:1.05; color:var(--cream-50);margin:0;} .cB-out__pymCellBody{font-size:14.5px;line-height:1.5; color:rgba(247,247,237,0.6);margin:0;} .cB-out__pymCellMeta{margin-top:auto;padding-top:8px; display:flex;justify-content:space-between;align-items:baseline; font-family:var(--font-mono);font-size:10.5px;letter-spacing:0.04em; color:rgba(247,247,237,0.4);} .cB-out__pymCellMeta .lift{color:var(--lime-500); font-family:var(--font-display);font-size:14px;letter-spacing:-0.01em; text-transform:none;} /* Featured cells */ .cB-out__pymCell.is-featured{background:#1F1B2A;} .cB-out__pymCell.is-featured .cB-out__pymCellKick{color:var(--lime-500);} .cB-out__pymCell.is-featured .cB-out__pymCellTitle{ font-family:var(--font-serif);font-style:italic; font-size:42px;letter-spacing:-0.02em;line-height:0.98;} .cB-out__pymCell.is-featured .cB-out__pymCellBody{ color:rgba(247,247,237,0.78);} .cB-out__pymCell.is-featured::before{content:"";position:absolute; top:0;left:0;width:3px;height:100%;background:var(--lime-500);} @media (max-width: 1100px){ .cB-out__pym{grid-template-columns:1fr;gap:48px;} .cB-out__pymLead{position:static;} } @media (max-width: 720px){ .cB-out__pymGrid{grid-template-columns:1fr;} } `; const PROPS = [ { kick: "Quality", title: "Smarter models.", body: "Mira tries every promising hypothesis on your training stack. Only the variants that beat your baseline on your verifier ship. The frontier shifts up — without a quality regression." }, { kick: "Speed", title: "Faster inference.", body: "Quantization, attention kernels, speculative decoding, distillation. Mira sweeps the inference pareto on your serving stack and ships only what holds up under your eval." }]; // Dashboard data — workflow stages, each with a primary objective and guardrails. // Plain-English metric names, with technical refs as captions. const DASH_TABS = [ { id: "pretrain", label: "Pretrain" }, { id: "posttrain", label: "Post-train" }, { id: "serve", label: "Serve" }, { id: "eval", label: "Eval" }]; // Sparkline shapes (0–1 normalized). Keep them short — implies improvement. const SPARK_UP = [0.40, 0.42, 0.45, 0.48, 0.55, 0.62, 0.71, 0.83, 0.92, 1.00]; const SPARK_DOWN = [1.00, 0.96, 0.88, 0.82, 0.74, 0.62, 0.51, 0.38, 0.24, 0.18]; const DASH_DATA = { pretrain: { objLbl: "Optimizing for", objName: "Loss curve quality", objSub: "validation perplexity on your held-out tokens", heroVal: "−12.4", heroUnit: "% perplexity", spark: SPARK_DOWN, guards: [ { metric: "Tokens / GPU-hour", ref: "throughput", delta: "+18%", since: "+24% vs v0.4" }, { metric: "Loss spike rate", ref: "stability monitor", delta: "0 events", since: "7d clean", flat: true }, { metric: "Long-context recall", ref: "32k haystack", delta: "+6.4 pts", since: "+9.1 pts QoQ" }, { metric: "Mixed-precision overflow", ref: "fp8 master weights", delta: "−0.4%", since: "−2.1% vs v0.4" }] }, posttrain: { objLbl: "Optimizing for", objName: "Answer accuracy", objSub: "your held-out eval set · weighted by use-case", heroVal: "+5.4", heroUnit: "pts pass-rate", spark: SPARK_UP, guards: [ { metric: "Reasoning quality", ref: "GSM8K · MATH", delta: "+3.1 pts", since: "+5.8 pts QoQ" }, { metric: "Hallucination rate", ref: "factuality probe", delta: "−18%", since: "−31% vs v0.4" }, { metric: "Instruction-following", ref: "if-eval v2", delta: "+2.7 pts", since: "+4.2 pts QoQ" }, { metric: "Refusal calibration", ref: "safety harness", delta: "+1.4 pts", since: "+2.0 pts QoQ" }] }, serve: { objLbl: "Optimizing for", objName: "Speed at the same quality", objSub: "tokens/sec under your live serving load", heroVal: "+22", heroUnit: "% throughput", spark: SPARK_UP, guards: [ { metric: "Time to first token", ref: "p50 latency", delta: "−41%", since: "−58% vs v0.4" }, { metric: "Tail latency", ref: "p99 under load", delta: "−27%", since: "−44% vs v0.4" }, { metric: "Quality regression", ref: "vs. baseline eval", delta: "none", since: "30d clean", flat: true }, { metric: "GPU memory headroom", ref: "paged kv-cache", delta: "+31%", since: "+47% vs v0.4" }] }, eval: { objLbl: "Optimizing for", objName: "Cost per million tokens", objSub: "blended training + serving cost on your stack", heroVal: "−38", heroUnit: "% $ / 1M tok", spark: SPARK_DOWN, guards: [ { metric: "GPU-hours / run", ref: "selective ckpt", delta: "−24%", since: "−37% vs v0.4" }, { metric: "Quality at lower cost", ref: "int4 awq · vs fp16", delta: "−0.1 pts", since: "30d clean", flat: true }, { metric: "Batch utilization", ref: "continuous batching", delta: "+19%", since: "+28% vs v0.4" }, { metric: "Cold-start cost", ref: "weight-streaming", delta: "−16%", since: "−29% vs v0.4" }] } }; const DASH_STATS = [ { val: "+5.4 pts", lbl: "Eval lift this quarter" }, { val: "−38%", lbl: "Cost / 1M tokens" }, { val: "110", lbl: "Experiments / week" }]; const BENCH = [ { name: "Mira", sub: "this work", value: 96, mira: true }, { name: "Average ML team", sub: "human baseline", value: 50, mira: false }, { name: "OpenEvolve", sub: "open-source SOTA", value: 32, mira: false }, { name: "Claude Code", sub: "general-purpose", value: 11, mira: false }]; // ---------- Variant D: Pick your metric ---------- const PYM_OBJECTIVES = [ { kick: "Quality", title: "Smarter models.", body: "Mira tries every promising hypothesis on your training stack. Only variants that beat your baseline on your verifier ship.", lift: "+5.4 pts pass-rate" }, { kick: "Speed", title: "Faster inference.", body: "Quantization, attention kernels, speculative decoding, distillation. Mira sweeps the inference pareto on your serving stack.", lift: "−27% p99 latency" }, { kick: "Footprint", title: "Smaller models.", body: "Distill to the smallest size that still passes your eval. Ship the same quality on a fraction of the parameters.", lift: "−68% params" }, { kick: "Cost", title: "Resource efficiency.", body: "Compute budgets, memory headroom, batch sizing. Mira finds the cheapest training and serving config that meets your SLOs.", lift: "−38% cost / prediction" }, { kick: "Data", title: "Sample efficiency.", body: "Curriculum, data mixing, active learning. Reach the same accuracy on fewer labeled examples — useful when labels are scarce.", lift: "2.1× fewer labels" }, { kick: "Capability", title: "New feature support.", body: "New input signals and feature columns. Mira folds the feature into training, verifies it lifts your eval, and confirms nothing else regressed.", lift: "+12 features · 0 regressions" }]; const PropsPickYourMetric = () =>
What Mira optimizes

You name the metric.
Mira optimizes for it.

Smarter, faster, smaller, cheaper, more sample-efficient — Mira works against your eval, whatever you decide that means. Pick the axis. We'll push it.

{PYM_OBJECTIVES.map((o, i) =>
{String(i + 1).padStart(2, "0")} {o.kick}

{o.title}

{o.body}

verified · your eval {o.lift}
)}
; const Outcomes = () => { const PropsBlock = PropsPickYourMetric; return (