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BitLens
Chrome DevTools for neural network quantization & MCU memory
Chrome DevTools for neural network quantization: profile PyTorch & ONNX models in one calibration pass, evaluate SQNR, plan MCU Flash & SRAM, and export ready-to-run configs for torchao, ON...
Hi Product Hunt! I built BitLens because quantizing neural networks for microcontrollers and edge hardware usually feels like flying blind.
When you squeeze a PyTorch or ONNX model onto an STM32H7 or edge NPU, standard post-training quantization treats the model like a black box. You quantize to INT8 or INT4, accuracy drops, or the tensor arena throws an out of memory error at runtime, with no visibility into which layer caused it.
BitLens gives you a visual DevTools experience for tensors:
1. Python Profiler: Captures 128-bin histograms, activation outliers (Omega = absmax / p99.9), kurtosis, simulated SQNR, and topological peak SRAM liveness in one calibration pass.
2. Web Studio: A zero-backend Next.js inspector preloaded with MobileNetV3, ResNet-18, and ViT-Tiny. Click any layer to see quantization grid steps overlaid on weight and activation distributions.
3. Greedy Pareto Auto-Fit: Ranks layers by SQNR loss per byte saved to fit your target memory ceiling.
4. 1-Click Code Exporter: Generates ready-to-run scripts for PyTorch torchao, ONNX Runtime, and TFLite Micro.
It is 100% open source under the MIT license. I would love feedback from fellow developers and ML engineers on the outlier heuristics and exporters!
About BitLens on Product Hunt
“Chrome DevTools for neural network quantization & MCU memory”
BitLens was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #375 on the daily leaderboard. Chrome DevTools for neural network quantization: profile PyTorch & ONNX models in one calibration pass, evaluate SQNR, plan MCU Flash & SRAM, and export ready-to-run configs for torchao, ON...
On the analytics side, BitLens competes within Open Source, Developer Tools and GitHub — topics that collectively have 633.5k followers on Product Hunt. The dashboard above tracks how BitLens performed against the three products that launched closest to it on the same day.
Who hunted BitLens?
BitLens was hunted by Dex. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of BitLens including community comment highlights and product details, visit the product overview.
Dex