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<main class="wrap">
<header class="masthead">
<p class="kicker">Phase 3 · pure inference · nothing trained</p>
<h1>Phase 3 Re-draft</h1>
<p class="lede">Hand the slots the judge rejects back to the drafter, after every judge pass (rd1) or every second pass (rd2). Same frozen 30B, same Phase 1 judge, SDAR-1.7B drafter, no expert pool.</p>
<p class="status"><span>Updated <b>{{UPDATED}} IST</b></span><span><b>{{NDONE}}</b> of {{NTOTAL}} runs finished</span><span>Run finishes about <b>{{FINISH}} IST</b></span></p>
</header>
<section id="unified" aria-labelledby="h-uni">
<h2 id="h-uni"><span class="secno">3</span>Every run, measured on this box</h2>
<p class="caption"><b>Table 0.</b> Every run, <b>all numbers measured on this 4-GPU box</b> (batch size 1, the same 4-GPU load for every row): rd1 and rd2 per benchmark, plus a <b>base</b> row, the base pipeline (SDAR-1.7B drafter + the trained 128M judge, rd's exact flags without re-draft), where that run exists. Accuracy is items correct, %, with the paired difference from the base pipeline in points (the base pipeline's per-item records are the Phase 1 ones, which this box reproduces token for token). Passes per block and 30B expert loads per token (unique expert loads summed over layers ÷ generated tokens) are counted per item. Tokens per second = total generated tokens ÷ total decode seconds; base tokens per second is on the same items as rd, and speedup = rd ÷ base tokens per second on identical items (item count in brackets). Wall is the run's wall-clock time on 4 GPUs, start to finish, model load included. <b>Reproduction:</b> on this box the base pipeline reproduces the Phase 1 records token for token (HumanEval 164/164, MBPP 257/257, 12/12 on each sampled set), with the same adapter 35805974 and 30B revision c351bbc. Where the base pipeline was decoded on only the first 12 items, the speedup (marked <span class=flag>†</span>) pairs rd with the base on those 12 items and is <b>not fully measured</b>: on HumanEval and MBPP a 12-item speedup differed from the full-set answer by up to 13%, and the 12-item base alone has a bootstrap 90% range of −6.5% to +8.0% (HumanEval) and −3.8% to +3.9% (MBPP). Nothing in this table is extrapolated; Phase 1 box numbers are in section 6.</p>
<div class="tbl-wrap">
<table class="bt" style="min-width:1150px">{{UNI}}</table>
</div>
</section>
<section id="table" aria-labelledby="h-table">
<h2 id="h-table"><span class="secno">4</span>Results</h2>
<p class="caption"><b>Table 1.</b> The same measurements arranged against the Phase 2 page. <b>Tokens per second are measured on this box</b>: rd1, rd2 and the base pipeline were all decoded here, and speedup = rd tokens per second ÷ base tokens per second on identical items. HumanEval and MBPP have a full-set base run, so those speedups are fully measured; where the base was decoded on only 12 items the speedup is marked <span class=flag>†</span> and is not fully measured (see Table 0 for its uncertainty). Stock, SDAR-1.7B, CoDA-1.7B and Qwen3-0.6B columns are <b>Phase 2 records</b>: accuracy copied from the Phase 2 page, speed measured on the Phase 1 box and listed in section 6, not here. Accuracy deltas are against stock. Highlighted: best in the row.</p>
<div class="tbl-wrap">
<table class="bt">
<thead><tr>
<th class="l" scope="col">Benchmark</th><th class="l" scope="col">Measure</th>
<th scope="col"><i class="sw" style="background:var(--s-stock)"></i>Stock 30B<span class="sub">Phase 2 records</span></th>
<th scope="col"><i class="sw" style="background:var(--s-sdar)"></i>SDAR-1.7B + judge<span class="sub">Phase 2 records</span></th>
<th scope="col"><i class="sw" style="background:var(--s-coda)"></i>CoDA-1.7B + judge<span class="sub">Phase 2 records</span></th>
<th scope="col"><i class="sw" style="background:var(--s-qwen)"></i>Qwen3-0.6B + judge<span class="sub">Phase 2 records</span></th>
<th scope="col" class="new"><i class="sw" style="background:var(--s-sdar)"></i>Base pipeline<span class="sub">measured on this box</span></th>
<th scope="col" class="new"><i class="sw" style="background:var(--s-rd1)"></i>rd1<span class="sub">re-draft every pass</span></th>
<th scope="col" class="new"><i class="sw" style="background:var(--s-rd2)"></i>rd2<span class="sub">re-draft every 2 passes</span></th>
</tr></thead>
<tbody>{{ROWS}}</tbody>
{{ALLROW}}
</table>
</div>
<div class="notes">
<p><b>Tokens per second</b> = total generated tokens (to end of answer) ÷ total decode seconds over the items, timed with <code>perf_counter</code> and CUDA synchronized at both ends, so it includes prompt prefill, every 30B and drafter forward and the KV flush, and excludes scoring and file writing. The fully-measured row pools only benchmarks with a full-set base run and both rd runs finished ({{ALLNOTE}}).</p>
</div>
</section>
<section id="figures" aria-labelledby="h-figs">
<h2 id="h-figs"><span class="secno">5</span>Figures</h2>
<div class="figwrap" id="fig1">
<span class="fig-no">Figure 1</span><h3>Speedup over the base pipeline, measured on this box</h3>
<ul class="legend" id="lg1"></ul>
<div class="smgrid" id="sm1"></div>
<figcaption>Tokens per second ÷ the base pipeline's, both decoded on this box (4 GPUs busy), full pipeline (30B, judge, drafter and re-draft all counted). Higher is better. Dashed line: the base pipeline at 1×. HumanEval and MBPP: rd and base on every item. Values marked † use only the 12-item base run and are not fully measured. Stock and the other Phase 2 drafters were not measured on this box and are not shown. Nothing in the figures is extrapolated.</figcaption>
</div>
<div class="figwrap" id="fig2">
<span class="fig-no">Figure 2</span><h3>Accuracy by benchmark</h3>
<ul class="legend" id="lg2"></ul>
<div class="smgrid" id="sm2"></div>
<figcaption>Items correct, %, one panel per benchmark with its own y-range; Stock, CoDA and Qwen3 are Phase 2 records, the base pipeline is its Phase 1 records (reproduced token for token on this box), rd1 and rd2 are measured here. Whiskers on rd1 and rd2: 95% CI of the paired difference from the base pipeline, 2,000 bootstrap resamples, centred on the point.</figcaption>
</div>
</section>
<section id="extrap" aria-labelledby="h-ext">
<h2 id="h-ext"><span class="secno">6</span>Extrapolated to the Phase 1 box (8× RTX PRO 6000 Server)</h2>
<p class="caption"><b>EXTRAPOLATED — based on the extrapolation using the measured numbers on 4× GPUs for this dataset for this model, using reference from the runs from this model (the base pipeline measured on the Phase 1 8× box).</b></p>
<p class="caption"><b>Formula.</b> Phase 1 box tokens per second for rd = the base pipeline's tokens per second <b>measured on the Phase 1 box</b> (Phase 2 records) × the speedup <b>measured here</b> on this dataset (rd ÷ base tokens per second, identical items, Table 0); the Calculation column shows the two factors. † = the base pipeline was decoded here on only the first 12 items of this benchmark, so the speedup is estimated by the box-ratio method (rd's tokens per second over all its items here × the base pipeline's Phase 1 box tokens per second ÷ its tokens per second here, both on those 12 items): not fully measured, and a 12-item estimate can be off by up to about 13%. Δ = extrapolated rd − the base pipeline measured on the Phase 1 box. × stock = extrapolated tokens per second ÷ the stock 30B's, measured on the Phase 1 box (Phase 2 page). The 8-GPU wall time replays this box's per-item times over 8 shards through the Phase 2 per-component box ratios and cost model, so it is modelled, not measured. The <b>base pipeline row is not extrapolated</b>: its Phase 1 box value was measured on that box.</p>
<div class="tbl-wrap">
<table class="sm">
<thead><tr><th class="l">Benchmark</th><th class="l">Setup</th><th>Calculation<br>base tok/s (Phase 1 box) × speedup (here)</th><th>Tokens / s<br>on the Phase 1 box</th><th>Δ vs base pipeline<br>(tokens / s)</th><th>× stock<br>(Phase 1 box)</th><th>Wall on 8 GPUs</th></tr></thead>
<tbody>{{XTABLE}}</tbody>
</table>
</div>
<h3 class="sub3">Reference: Phase 2 records, <b class=mt style="display:inline">measured on the Phase 1 box</b></h3>
<p class="caption"><b>Table 2b.</b> Tokens per second from the Phase 2 page (× = speedup over stock). These are measurements on the Phase 1 box, not extrapolations; SDAR-1.7B + judge is the base pipeline.</p>
<div class="tbl-wrap">
<table class="sm">
<thead><tr><th class="l">Benchmark</th><th>Stock 30B</th><th>SDAR-1.7B + judge<br>(base pipeline)</th><th>CoDA-1.7B + judge</th><th>Qwen3-0.6B + judge</th></tr></thead>
<tbody>{{REF2}}</tbody>
</table>
</div>
</section>
<section id="progress" aria-labelledby="h-progress">
<h2 id="h-progress"><span class="secno">7</span>Progress</h2>
<p class="caption">The {{NTOTAL}} runs in the order the script runs them (it alternates which setup goes first on each benchmark); <b>base</b> is the base pipeline decoded in full on this box, which makes that benchmark's speedup fully measured. Finish times are estimates for this box, which has 4 GPUs; “running” means the benchmark is still in progress.</p>
<div class="tbl-wrap">
<table class="sm">
<thead><tr><th class="l">Setup</th><th class="l">Benchmark</th><th>Items done / total</th><th>Finish (IST)</th><th class="l">State</th></tr></thead>
<tbody>{{PROGRESS}}</tbody>
</table>
</div>
</section>
<section id="diag" aria-labelledby="h-diag">
<h2 id="h-diag"><span class="secno">8</span>Where the speed comes from</h2>
<p class="caption">Everything here is measured on this box, per architecture: passes per block and 30B expert loads per token (unique expert loads summed over layers, per generated token) do not depend on the machine; drafter forwards per token counts every SDAR-1.7B forward (first draft and re-drafts); tokens per second is wall time on this box. In brackets: stock 30B from the Phase 2 records. Speedup is rd ÷ base pipeline on identical items; † = only the 12-item base run.</p>
<div class="tbl-wrap">
<table class="sm">
<thead><tr><th class="l">Benchmark</th><th class="l">Setup</th><th>Items</th><th>Passes / block<br>(stock)</th><th>30B expert loads / token<br>(stock)</th><th>Drafter forwards / token</th><th>Tok/s this box</th><th>Speedup vs base</th></tr></thead>
<tbody>{{DIAG}}</tbody>
</table>
</div>
<div class="notes">
<p><b>Baseline.</b> The base pipeline was decoded here under the same 4-GPU load as rd: every item of the benchmarks that have a full base run (HumanEval and MBPP so far, plus any marked base in Table 0), the first 12 items of the others. On this box it reproduces the Phase 1 records token for token (HumanEval 164/164, MBPP 257/257, 12/12 on each sampled set), with the same adapter 35805974 and 30B revision c351bbc, so the work is identical across boxes. The 12-item baselines are small: per-item speed varies a lot, and a 12-item pairing on HumanEval or MBPP would have been off by up to 13% against the full answer.</p>
<p><b>Cost model.</b> The Phase 2 cost model enters only the modelled 8-GPU wall times in section 6; no measured number on this page depends on it.</p>
<p>Timing: per-item seconds are measured from before prefill to after the last forward with CUDA synchronized at both ends; no polling or sleeps are involved.</p>
</div>
</section>
<footer>Data: Hugging Face dataset Arushhh/phase3-redraft and branch phase3-redraft on GitHub (results/phase3). This page is rebuilt after every backup.</footer>
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