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<meta name="description" content="PhaseMesh by Vontra Labs: compact local AI runtimes built from measured traces, phase signatures, and hard evals." />
<title>PhaseMesh by Vontra Labs</title>
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<section class="hero" aria-label="PhaseMesh by Vontra Labs">
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<p class="eyebrow">Vontra Labs</p>
<h1>PhaseMesh</h1>
<p class="lede">
Compact local AI runtime built from measured traces, phase signatures,
and hard evals.
</p>
<p class="sublede">
The public artifact pours Qwen3-4B-Instruct traces into a local
PhaseMesh memory, then serves covered coding and reasoning skills in
milliseconds with an explicit confidence gate.
</p>
<div class="actions" aria-label="Primary links">
<a class="button primary" href="https://huggingface.co/Vontra/PhaseMesh-Qwen3-4B">
Open Model
</a>
<a class="button" href="https://github.com/ashhart/PhaseMesh">
View Source
</a>
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<div class="trace trace-a"></div>
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<span>trace</span>
<strong>PhaseMesh</strong>
<span>answer</span>
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<section class="metrics-strip" aria-label="PhaseMesh-Qwen3-4B metrics">
<article>
<strong>180</strong>
<span>teacher traces</span>
</article>
<article>
<strong>65/65</strong>
<span>coverage eval</span>
</article>
<article>
<strong>~2.18 ms</strong>
<span>median PhaseMesh latency</span>
</article>
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<strong>~4,966 ms</strong>
<span>live Qwen3-4B median</span>
</article>
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<p class="section-label">Featured artifact</p>
<h2>PhaseMesh-Qwen3-4B</h2>
<p>
A PhaseMesh trace LM built from Qwen3-4B-Instruct coding and reasoning traces.
It is a fast specialist over a measured coverage set, not a raw Qwen checkpoint
or a general transformer replacement.
</p>
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<a class="artifact-card" href="https://huggingface.co/Vontra/PhaseMesh-Qwen3-4B">
<span>Hugging Face Model</span>
<strong>Vontra/PhaseMesh-Qwen3-4B</strong>
<small>Trace artifact, eval files, examples, and model card.</small>
</a>
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<p class="section-label">Research direction</p>
<h2>Build the small thing. Measure the hard thing.</h2>
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<ul class="principles">
<li>Trace-poured specialists for covered workflows</li>
<li>Phase binding and associative memory experiments</li>
<li>Auditable evals instead of screenshot claims</li>
<li>Efficient sequence kernels as the next scaling target</li>
</ul>
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