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<title>RobotFlowLabs — Foundation Models for Real Robots</title>
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<div class="container">
<!-- HERO -->
<div class="hero">
<div class="hero-label">/// RobotFlowLabs</div>
<h1><span>Foundation Models</span><br>for Real Robots</h1>
<p class="hero-tagline">
We optimize vision, language, and action models for real-time edge deployment.
Every model here is compressed, benchmarked, and ready for production robotics.
</p>
<div class="hero-stats">
<div class="stat">
<div class="stat-number">16+</div>
<div class="stat-label">Models</div>
</div>
<div class="stat">
<div class="stat-number">58</div>
<div class="stat-label">ANIMA Modules</div>
</div>
<div class="stat">
<div class="stat-number">4.5x</div>
<div class="stat-label">Max Compression</div>
</div>
<div class="stat">
<div class="stat-number">ROS2</div>
<div class="stat-label">Native</div>
</div>
</div>
</div>
<!-- MISSION -->
<section>
<h2>Mission</h2>
<p class="mission-text">
The robotics community deserves <strong>production-ready models</strong>, not just research checkpoints.
We take the best open foundation models — CLIP, SAM2, DINOv2, Qwen, Depth Anything — and make them
<strong>actually deployable</strong> on the hardware robots use: Jetson Orin, industrial PCs, edge GPUs.
</p>
<p class="mission-text" style="margin-top: 16px;">
Every model is quantized (INT4/INT8), exported (ONNX/SafeTensors/TorchScript), and benchmarked on
real hardware. No guesswork, no "should work in theory" — <strong>measured performance on real silicon</strong>.
</p>
</section>
<!-- COLLECTIONS -->
<section>
<h2>Model Collections</h2>
<p>Organized by capability for the ANIMA robotics stack.</p>
<div class="collection-grid">
<a class="collection-card" href="https://huggingface.co/collections/robotflowlabs/anima-vision-69bc77ca7ce15b06bbdd21bd">
<div class="tag">Perception</div>
<h3>ANIMA Vision</h3>
<p>Segmentation, features, depth estimation, and visual grounding for robotic scene understanding.</p>
<div class="models">SAM2 · DINOv2 · CLIP · SigLIP · Depth Anything</div>
</a>
<a class="collection-card" href="https://huggingface.co/collections/robotflowlabs/anima-language-69bc77ca29dccc3f68f8c7fd">
<div class="tag">Reasoning</div>
<h3>ANIMA Language</h3>
<p>INT4 quantized language models for instruction following, planning, and robotic reasoning.</p>
<div class="models">Qwen2.5-7B · SmolLM2-1.7B</div>
</a>
<a class="collection-card" href="https://huggingface.co/collections/robotflowlabs/anima-vlm-69bc77ca53ae84ac21b0f012">
<div class="tag">Understanding</div>
<h3>ANIMA VLM</h3>
<p>Vision-language models for visual QA, scene description, and grounding language to observations.</p>
<div class="models">Qwen2.5-VL-7B · Qwen2.5-VL-3B</div>
</a>
<a class="collection-card" href="https://huggingface.co/collections/robotflowlabs/anima-vla-69bc77cbf1b8aa40002920bb">
<div class="tag">Action</div>
<h3>ANIMA VLA</h3>
<p>Vision-Language-Action models for end-to-end robotic control and manipulation.</p>
<div class="models">SmolVLA · RDT2-FM · FORGE Students</div>
</a>
</div>
</section>
<!-- FORGE PIPELINE -->
<section>
<h2>FORGE — Compression Pipeline</h2>
<p>Our 4-stage pipeline takes any 7B+ VLA model down to <2GB for real-time edge deployment.</p>
<div class="pipeline">
<div class="pipeline-step">
<div class="step-name">Teacher Labels</div>
<div class="step-detail">5 teachers, multi-GPU</div>
</div>
<div class="pipeline-arrow">▶</div>
<div class="pipeline-step">
<div class="step-name">Distillation</div>
<div class="step-detail">KD + curriculum</div>
</div>
<div class="pipeline-arrow">▶</div>
<div class="pipeline-step">
<div class="step-name">Compression</div>
<div class="step-detail">Prune + quantize</div>
</div>
<div class="pipeline-arrow">▶</div>
<div class="pipeline-step">
<div class="step-name">Export</div>
<div class="step-detail">ONNX / TRT / MLX</div>
</div>
</div>
<p style="color: var(--dim); font-size: 12px; text-align: center;">
Automated hyperparameter optimization via Optuna · 400+ trials across 4 GPUs · W&B experiment tracking
</p>
</section>
</div>
<!-- FOOTER -->
<footer>
<div class="container">
<p>
<a href="https://huggingface.co/robotflowlabs">RobotFlowLabs</a>
· Building the future of robotic intelligence
· 2026
</p>
<p style="margin-top: 8px; color: #444;">
Models compressed with FORGE · Benchmarked on NVIDIA L4 · All weights open
</p>
</div>
</footer>
</body>
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