Develop AI for any Edge Application
On-premise and cloud solutions for Edge AI developers
The Embedl Physical AI Platform
Streamlining the path from development workflows to hardware-ready deployments.
Our features for developing efficient on-device AI
Tools that fits any team size and skill level.
On-prem or SaaS
Integrated edge AI workflows behind one interface
Errors & Debugging
Compare model graphs and on-device latency
Device Farms
Verify and benchmark with on-prem and cloud device farms
Integrations
Safety, verification and compliance optimization
Embedl Models
Popular models made compatible and highly optimized for specific edge hardware.
Explore modelsRun-ready packages
Full code, kernels and recipes to run models on specific devices
Find the best model
Try out different models before fine-tuning and licensing
Save time, cost & power
Reduce time to market, unit costs and power consumption.
GenAI focus
The latest generative models for tomorrow's edge AI products
Embedl Studio
Standalone Edge AI model visualizer and profiling app.
Learn moreGraph & problem analysis
Visualize the changes compilation introduces in each step
Performance analysis
Compare latency, quantization precision and operation type
Compare model versions
See how quantization and compiler settings affect the graph
One tool to rule them all
1 tool for visualizing multi-step compilation and benchmark data
Embedl Deploy
Edge AI conversion, compilation and quantization to easily get models running on hardware.
Learn moreSimple setup & workflow
Simple compilation/quantization for various devices and toolchains.
Hardware-aware
Hardware-aware PyTorch ops with built-in compiler constraints.
Quantization
Predictable performance after quantization.
Faster time-to-market
Design for edge performance and compatibility from day one.
Target domains for scalable Edge AI deployments
Enabling embedded intelligence for any use case.
Discover our benchmark results
A selection of our optimization results across different model and hardware targets.
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VMoveNet2.3xspeed upI want this → -
Gemma 3 270M1.43xspeed upI want this → -
Vision Transformer1.85xspeed upI want this → -
Llama 3.2 1B3.73xspeed upI want this → -
SSDLite MobileNet-V26xspeed upI want this → -
Qwen 7B2.27xspeed upI want this → -
MobileNetV319xspeed upI want this → -
Gemma 3 1B2.27xspeed upI want this →
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ResNet-50 Panoptic-DeepLab1.3xspeed upI want this → -
Llama 3.2 3B3.28xspeed upI want this → -
Ultra Fast Lane Detection3xspeed upI want this → -
Llama 3.2 1B3.73xspeed upI want this →
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VMoveNet2.3xspeed upI want this → -
Gemma 3 270M1.43xspeed upI want this → -
Vision Transformer1.85xspeed upI want this → -
Llama 3.2 1B3.73xspeed upI want this → -
SSDLite MobileNet-V26xspeed upI want this → -
Qwen 7B2.27xspeed upI want this → -
MobileNetV319xspeed upI want this → -
Gemma 3 1B2.27xspeed upI want this →
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ResNet-50 Panoptic-DeepLab1.3xspeed upI want this → -
Llama 3.2 3B3.28xspeed upI want this → -
Ultra Fast Lane Detection3xspeed upI want this → -
Llama 3.2 1B3.73xspeed upI want this →
Outstanding innovation honored by the Swedish Royal Academy.
One of Sweden’s 33 most promising tech startups two years in a row.
Global ranking of the top 100 most promising private AI startups worldwide. startups.
Excellence in high-performance and embedded computing.
Top 100 Startups in the Tech Arena Startup & Scaleup competition.
European leader driving industrial digital transformation.
Compiled notes from the team
Stay updated on Embedl’s latest insights and industry events.
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Feb 13, 2026Cosmos Reason 2, Quantized for the EdgeToday we’re releasing the first quantized version of Cosmos Reason 2, which runs efficiently on the Jetson Nano Super: ...View this post →
Jan 14, 2026The cost of running frontier AI modelsResearch groups pushing the limits of artificial intelligence are running into a new kind of barrier. The economic cost and energy ...View this post →
Dec 7, 2025Ultra-Efficient SLMs: Embedl’s Breakthrough for On-Device AIEmbedl has released a major milestone for efficient LLMs: introducing FlashHead, a training-free, hardware-friendly drop-in replacement for ...View this post →
Nov 28, 2025Intelligence per Watt: Edge versus CloudA new paper1 from a group at Stanford has set up new metrics to evaluate the energy efficiency of AI models: intelligence per watt. How ...View this post →
Oct 15, 2025EDGE AI Talks: Faster Time-To-Device with Embedl HubWatch EDGE AI Talks: Faster Time-To-Device with Embedl Hub, with Our Product Owner Andreas Ask.View this post →
Oct 6, 2025Efficiency Is the Key to Sustainable AIThe recently announced strategic partnership between OpenAI and NVIDIA has spotlighted the issue of AI energy consumption. Under this deal, ...View this post →
Sep 19, 2025Hardware Aware Model OptimizationYou probably hit a wall if you've ever trained a high-performing deep learning model and tried to deploy it to an embedded device or mobile ...View this post →
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Feb 13, 2026Cosmos Reason 2, Quantized for the EdgeToday we’re releasing the first quantized version of Cosmos Reason 2, which runs efficiently on the Jetson Nano Super: ...View this post →
Jan 14, 2026The cost of running frontier AI modelsResearch groups pushing the limits of artificial intelligence are running into a new kind of barrier. The economic cost and energy ...View this post →
Dec 7, 2025Ultra-Efficient SLMs: Embedl’s Breakthrough for On-Device AIEmbedl has released a major milestone for efficient LLMs: introducing FlashHead, a training-free, hardware-friendly drop-in replacement for ...View this post →
Nov 28, 2025Intelligence per Watt: Edge versus CloudA new paper1 from a group at Stanford has set up new metrics to evaluate the energy efficiency of AI models: intelligence per watt. How ...View this post →
Oct 15, 2025EDGE AI Talks: Faster Time-To-Device with Embedl HubWatch EDGE AI Talks: Faster Time-To-Device with Embedl Hub, with Our Product Owner Andreas Ask.View this post →
Oct 6, 2025Efficiency Is the Key to Sustainable AIThe recently announced strategic partnership between OpenAI and NVIDIA has spotlighted the issue of AI energy consumption. Under this deal, ...View this post →
Sep 19, 2025Hardware Aware Model OptimizationYou probably hit a wall if you've ever trained a high-performing deep learning model and tried to deploy it to an embedded device or mobile ...View this post →
Get started with Embedl
Start developing and optimizing your edge AI models.