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  1. index.html +19 -14
index.html CHANGED
@@ -77,6 +77,7 @@
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  <strong>Why this exists.</strong> The community deserves a single place to compare tiny LMs fairly.
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  We include every model with verifiable benchmarks β€” ours, our competitors', yours.
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  <a href="https://huggingface.co/spaces/CompactAI-O/Tiny-ML-Leaderboard/discussions" target="_blank">Submit a model via PR.</a><br>
 
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  </div>
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  <h2 class="section-title">Detailed Results</h2>
@@ -162,7 +163,7 @@ const models = [
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  params: '51.8M',
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  blimp: 76.3,
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  arc: 52.2,
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- wiki: null,
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  tokens: '20B',
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  links: { card: 'https://huggingface.co/SupraLabs/Supra-50M-Instruct', base: 'https://huggingface.co/SupraLabs/Supra-50M-Base' }
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  },
@@ -291,8 +292,8 @@ const models = [
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  org: 'compactai',
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  params: '54.5M',
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  blimp: null,
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- arc: null,
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- wiki: null,
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  tokens: '~20B',
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  links: { card: 'https://huggingface.co/CompactAI-O/Shard-1' }
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  },
@@ -330,9 +331,9 @@ const models = [
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  name: 'StorySupra-10M',
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  org: 'supralabs',
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  params: '12.6M',
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- blimp: null,
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- arc: null,
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- wiki: null,
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  tokens: 'β€”',
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  links: { card: 'https://huggingface.co/SupraLabs/StorySupra-10M' }
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  },
@@ -341,8 +342,8 @@ const models = [
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  org: 'supralabs',
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  params: '289K',
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  blimp: null,
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- arc: null,
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- wiki: null,
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  tokens: 'β€”',
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  links: { card: 'https://huggingface.co/SupraLabs/DistillSupra-0.2M' }
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  },
@@ -350,9 +351,9 @@ const models = [
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  name: 'MicroSupra-1k',
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  org: 'supralabs',
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  params: '1K',
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- blimp: null,
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- arc: null,
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- wiki: null,
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  tokens: 'β€”',
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  links: { card: 'https://huggingface.co/SupraLabs/MicroSupra-1k' }
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  }
@@ -534,13 +535,15 @@ function buildEfficiencyChart() {
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  const sorted = [...valid].sort((a, b) => a.paramsNum - b.paramsNum);
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  const regData = [];
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  const thresholdData = [];
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  const steps = 100;
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- const logMin = 4;
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- const logMax = 9;
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  for (let i = 0; i <= steps; i++) {
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- const lx = logMin + (logMax - logMin) * (i / steps);
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  regData.push({ x: Math.pow(10, lx), y: intercept + slope * lx });
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  thresholdData.push({ x: Math.pow(10, lx), y: intercept + slope * lx + thresholdShift });
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  }
@@ -621,6 +624,8 @@ function buildEfficiencyChart() {
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  scales: {
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  x: {
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  type: 'logarithmic',
 
 
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  title: { display: true, text: 'Parameters', color: '#8b949e' },
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  grid: { color: 'rgba(255,255,255,0.06)' },
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  ticks: {
 
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  <strong>Why this exists.</strong> The community deserves a single place to compare tiny LMs fairly.
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  We include every model with verifiable benchmarks β€” ours, our competitors', yours.
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  <a href="https://huggingface.co/spaces/CompactAI-O/Tiny-ML-Leaderboard/discussions" target="_blank">Submit a model via PR.</a><br>
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+ <em style="color:#8b949e;font-size:.85rem">Updated 2026-05-27: TBD entries filled via automated eval (lm-eval-harness, same methodology). Shard-1 used custom ToyLM adapter. Glint models not evaluable β€” TinyMemoryLM code not yet published.</em>
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  </div>
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  <h2 class="section-title">Detailed Results</h2>
 
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  params: '51.8M',
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  blimp: 76.3,
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  arc: 52.2,
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+ wiki: 151.15,
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  tokens: '20B',
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  links: { card: 'https://huggingface.co/SupraLabs/Supra-50M-Instruct', base: 'https://huggingface.co/SupraLabs/Supra-50M-Base' }
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  },
 
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  org: 'compactai',
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  params: '54.5M',
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  blimp: null,
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+ arc: 43.94,
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+ wiki: 24.10,
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  tokens: '~20B',
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  links: { card: 'https://huggingface.co/CompactAI-O/Shard-1' }
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  },
 
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  name: 'StorySupra-10M',
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  org: 'supralabs',
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  params: '12.6M',
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+ blimp: 61.47,
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+ arc: 28.45,
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+ wiki: 78970.02,
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  tokens: 'β€”',
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  links: { card: 'https://huggingface.co/SupraLabs/StorySupra-10M' }
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  },
 
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  org: 'supralabs',
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  params: '289K',
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  blimp: null,
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+ arc: 25.17,
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+ wiki: 70687.56,
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  tokens: 'β€”',
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  links: { card: 'https://huggingface.co/SupraLabs/DistillSupra-0.2M' }
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  },
 
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  name: 'MicroSupra-1k',
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  org: 'supralabs',
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  params: '1K',
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+ blimp: 58.61,
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+ arc: 26.39,
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+ wiki: 422285.72,
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  tokens: 'β€”',
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  links: { card: 'https://huggingface.co/SupraLabs/MicroSupra-1k' }
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  }
 
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  const sorted = [...valid].sort((a, b) => a.paramsNum - b.paramsNum);
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+ const axisMin = 500;
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+ const axisMax = 100_000_000;
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+ const logAxisMin = Math.log10(axisMin);
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+ const logAxisMax = Math.log10(axisMax);
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  const regData = [];
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  const thresholdData = [];
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  const steps = 100;
 
 
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  for (let i = 0; i <= steps; i++) {
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+ const lx = logAxisMin + (logAxisMax - logAxisMin) * (i / steps);
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  regData.push({ x: Math.pow(10, lx), y: intercept + slope * lx });
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  thresholdData.push({ x: Math.pow(10, lx), y: intercept + slope * lx + thresholdShift });
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  }
 
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  scales: {
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  x: {
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  type: 'logarithmic',
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+ min: axisMin,
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+ max: axisMax,
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  title: { display: true, text: 'Parameters', color: '#8b949e' },
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  grid: { color: 'rgba(255,255,255,0.06)' },
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  ticks: {